Observed surface air temperature has been increasing since the 20th century all over Asia (high confidence1 ). Significant warming has intensified the threat to social and economic sustainability (medium confidence). Rising temperatures increase the likelihood of the threat of heatwaves across Asia, droughts in arid and semiarid areas of West, Central and South Asia, delays and weakening of the monsoon circulation in South Asia, floods in monsoon regions in South, Southeast and East Asia, and glacier melting in the Hindu Kush Himalaya region (medium confidence). {10.3.1, 10.3.3}
Asian countries are experiencing a hotter summer climate, resulting in an increase in energy demand for cooling at a rapid rate, together with the population growth (high confidence). Decrease in precipitation influences energy demand as well as desalination, underground water pumping and other energy-intensive methods are increasingly used for water supply (high confidence). More energy demands in summer seasons will exceed any energy savings from relatively lower heating demand due to warmer winter. Among 13 developing countries with large energy consumption in Asia, 11 are exposed to high-energy insecurity and industrial-systems risk (high confidence). {10.4.1}
Asian terrestrial-ecosystems change is driven by global warming, precipitation and Asian monsoon alteration, permafrost thawing and extreme events like dust storms, along with natural and human-related factors which are in interplay (high confidence). Treeline position in North Asian mountains moves upwards after the 1990s, while in Himalaya treeline demonstrates a multi-directional shift, either moves upwards or does not show upslope advance, or moves downwards. This can be explained by site-specific complex interaction of positive effect of warming on tree growth, drought stress, change in snow precipitation, land-use change (especially grazing) and other factors (high confidence). The increased considerable changes in biomes in Asia are a response to warming (medium confidence). Terrestrial and freshwater species, populations and communities are altered in line with climate change across Asia (medium to high confidence). Climate change, human activity and lightning have caused the increase in wildfire severity and area burned in North Asia after the 1990s (medium confidence). Length of plant growth season has increased in some parts of East and North Asia, while the opposite trend, or no change at all, has been observed in other parts (high confidence). Observed biodiversity or habitat losses of animals plants have been linked to climate change in some parts of Asia (high confidence). There is evidence that climate change can alter species interaction or spatial distribution of invasive species in Asia (high confidence). Changes in ecosystems in Asia during the 21st century are expected to be driven by projected climatic, natural and socioeconomic changes. Across Asia, under a range of representative concentration pathways and other scenarios, rising temperatures are expected to contribute to a northward shift of biome boundaries and an upwards shift of mountain treeline (medium confidence). {10.4.2}
Coastal habitats of Asia are diverse, and the impacts of climate change including rising temperatures, ocean acidification and sea level rise (SLR) has brought negative effects to the services and the livelihoods of people depending on it (high confidence). The degree of bleaching of coral reefs is diverse among different presences of stress-tolerant symbionts and higher thermal thresholds. The risk of irreversible loss of coral reefs, tidal marshes, seagrass meadows, plankton community and other marine and coastal ecosystems increases with global warming, especially at 2°C temperature rise or more (high confidence). Mangroves in the region continue to face threats due to pollution, conversion for aquaculture, agriculture and climate-based threats like SLR and coastal erosion. {10.4.3}
Both climatic and non-climatic drivers such as socio-economic changes have created water stress conditions in both water supply and demand in all sub-regions of Asia, except for North Asia (medium confidence). These changes in space and time directly or indirectly have affected water-use sectors and services. By mid-21st Century, the international transboundary river basins of Amu Darya, Indus, Ganges could face severe water scarcity challenges due to climatic variability and changes acting as stress multipliers (high confidence). Due to global warming, Asian countries could experience an increase in drought conditions (5–20%) by the end of this century (high confidence). {10.4.4}
The Asian glaciers were in minor-area shrinkage and mass loss during 2006–2016, resulting in the instability of water resource supply (high confidence). Glaciers in Asia are the water resources of about 220 million people in the downstream areas. The glacier melt water in the southern Tibetan Plateau increased during 1998–2007, and will further increase till 2050. The total amount and area of glacier lakes have increased during the past decade (high confidence). More glacier collapses and surges were found in western Tibetan Plateau.Glacier lake outburst flood (GLOF) will threaten the securities of the local and downstream communities (high confidence). Snowmelt water contributed 19% of the increase change in runoff of arid regions’ rivers in Xinjiang, China, and 10.6% of the upper Brahmaputra River during 2003–2014 (medium confidence). {10.4.4, Box 10.4}
Since IPCC AR5, more studies have reinforced the earlier findings on the spatio-temporal diversity of climate-change impacts on food production in Asia depending on the geographic location, agroecology and crops grown, recognising that there are winners and losers associated with the changing climate across scales (high confidence). Most of these impacts have been associated with drought, monsoon rain and oceanic oscillations, the frequency and severity of which have been linked with the changing climate. Climate-related risks to agriculture and food systems in Asia will progressively escalate with the changing climate, with differentiated impacts across the region (medium confidence). Major projected impacts of climate change in the agriculture and food sectors include decline in fisheries, aquaculture, crop production (particularly in South and Southeast Asia), reduction in livestock production in Mongolia and changes in crop, farming systems and crop areas in almost all regions, with negative implications to food security (medium confidence). In India, rice production can decrease from 10 to 30%, whereas maize production can decrease from 25 to 70% assuming a range of temperature increase from 1°C to 4°C. Similarly, rice production in Cambodia can decrease by 45% by 2080 under the high-emissions scenario. Occurrence of pests, such as the golden apple snail (Pomacea canaliculate), associated with the predicted increase in climatically suitable habitats in 2080, threatens the top Asian rice-producing countries including China, India, Indonesia, Bangladesh, Vietnam, Thailand, Myanmar, the Philippines and Japan. Increasing temperatures, changing precipitation levels and extreme climate events, such as heatwaves, droughts and typhoons, will persist in being important vulnerability drivers that will shape agricultural productivity particularly in South, Southeast and Central Asia. {10.4.5, Figure 10.6}
Asian urban areas are considered high-risk locations from projected climate change, extreme events, unplanned urbanisation and rapid land-use change (high confidence) but also sites of ongoing adaptation (medium confidence). Asia is home to the largest share of people living in informal settlements, with 332 million in Eastern and Southeast Asia, and 197 million in Central and Southern Asia. By 2050, 64% of Asia’s population will be urban. Coastal cities, especially in South and Southeast Asia, are expected to see significant increases in average annual economic losses between 2005 and 2050 due to flooding, with very high losses in East Asian cities under the high-emissions scenario (high confidence). Climate change will amplify the urban heat-island effect across Asian cities (especially South and East Asia) at 1.5°C and 2°C temperature rise, both substantially larger than under the present climate (medium evidence, high agreement ). Under the high-emissions scenario, higher risks from extreme temperature and precipitation are projected for almost all cities (medium confidence), with impacts on freshwater availability, regional food security, human health and industrial outputs. By 2080, 940 million to 1.1 billion urban dwellers in South and Southeast Asia could be affected by extreme heat lasting more than 30 d yr –1 (high confidence), with poorer populations affected the most. {10.4.6, Cross-Chapter Box URBAN in Chapter 6}
Climate change has caused direct losses due to the damage in infrastructure, disruption in services and affected supply chains in Asia (medium confidence) and will increase risk to infrastructure as well as provide opportunities to invest in climate-resilient infrastructure and green jobs (medium confidence). At higher warming, key infrastructures, such as power lines, transport by roads and railways, and built infrastructures, such as airports and harbours, are more exposed to climate-induced extreme events, especially in coastal cities (medium confidence). Evidence on urban adaptation across Asia is growing with examples of infrastructural adaptation (e.g., flood protection measures, and climate-resilient highways and power infrastructure), institutional adaptation (e.g., sustainable land-use planning, zoning plans), nature ecosystem-based solutions (e.g., mangrove restoration, restoring and managing urban green spaces, urban farming), technological solutions (e.g., smart cities, early warning systems) and behavioural adaptation (e.g., improved awareness and preparedness measures). However, adaptation actions tend to be in the initial stages and more reactive (57% of urban adaptations focus on preparatory interventions, such as capacity building, and 43% of cities report implemented adaptation interventions) (medium confidence). The degree of implementation of urban adaptation is uneven with large cities receiving more funding and priority, and smaller cities and towns, and peri-urban spaces, seeing relatively lower adaptation action (medium confidence). {10.4.6}
Climate change is increasing vector-borne and water-borne diseases, undernutrition, mental disorders and allergy-related illnesses in Asia by increasing hazards such as heatwaves, flooding and drought, and air pollutants, in combination with more exposure and vulnerability (high confidence). Sub-regional diversity in socioeconomic and demographic contexts (e.g., ageing, urban compared with agrarian society, increasing population compared with reduced birth rate, high income compared with low to middle income) and geographic characteristics largely define the differential vulnerabilities and impacts within countries in Asia. Under the medium-to-high emissions scenario, rising temperatures and extreme climate events will have an increasing impact on human health and well-being with varying types and magnitudes of impact across Asia (high confidence). More frequent hot days and intense heatwaves will increase heat-related deaths. Increased floods and droughts will have adverse impacts on food availability and the prices of food, resulting in increased undernourishment in South and Southeast Asia. Increases in heavy rain and temperature will increase the risk of diarrhoeal diseases, dengue fever and malaria in tropical and subtropical Asia. {10.4.7}
Increased climate variability and extreme events are already driving migration (robust evidence, medium agreement ) and projecting that longer-term climate change will increase migration flows across Asia (medium confidence). One in three migrants comes from Asia, and the highest ratio of outward migrants is seen from hazard-exposed Pacific countries. In 2019, Bangladesh, China, India and the Philippines each recorded more than 4 million disaster displacements. In Southeast Asia and East Asia, cyclones, floods and typhoons triggered internal displacement of 9.6 million people, almost 30% of total global displacements in 2019. {Box 10.2}
There is a small but growing literature highlighting the importance of behavioural aspects of adaptation in Asia (high confidence), but this is restricted primarily to agriculture and disaster risk reduction (DRR). Factors motivating adaptation actions include risk perception, perceived self-efficacy, sociocultural norms and beliefs, previous experiences of impacts, levels of education and awareness (high confidence). There is growing evidence on behavioural aspects of individual adaptation but lesser evidence on the socio-cognitive factors motivating governments and private-sector actors to adapt. {10.5.3}
Climate change is already causing economic loss and damage across Asian regions, and this will increase under higher warming (medium confidence). Non-material losses and damages are reported to a lesser degree, but this is due to under-reporting and methodological issues with detection and attribution to climate change (high confidence). Loss and damage represents a key knowledge gap, especially in West, Central and North Asia. Insufficient literature differentiating loss and damage under future adaptation scenarios renders a comprehensive assessment of residual damages, along with future loss and damage, difficult. {Box 10.6}
Options such as climate-smart agriculture, ecosystem-based DRR and investing in urban blue–green infrastructure meet adaptation, mitigation and Sustainable Development Goals simultaneously, presenting opportunities for climate resilient development (CRD) pathways in Asia (high confidence). Climate risks, vulnerability and adaptation measures need to be factored into decision making across all levels of governance (high confidence). To help achieve this, there is a need to advance the current understanding of climate impacts across sectors and spatio-temporal scales, and improve on the current strategies in planning and budget allocation. More accurate forecasting of extreme events, risk awareness and prioritising individual and collective decision making also need to be addressed (high confidence). Options for Asian countries are transforming the risks of climate change into opportunities for the advancement of projects in the energy sector, including promoting investment in non-fossil energies, securing local natural gas resources, enhancing water harvesting, adopting green building technologies and encouraging multi-stakeholder partnerships. However, there are significant barriers to CRD such as fragmented, reactive governance; inadequate evidence on which actions to prioritise and how to sequence them; and finance deficits. Some Asian countries and regions offer solutions to overcome these barriers: through use of advanced technologies (in situ observation and remote sensing, a variety of new sensor technologies, citizen science, artificial intelligence and machine learning tools); regional partnerships and learning; improved forecasting capabilities; and better risk awareness (high confidence). {10.5, 10.6}
Asia is defined here as the land and territories of 51 countries/regions (Figure 10.1). It can be broadly divided into six sub-regions based on geographic position and coastal peripheries (IPCC, 2014b). These are, in alphabetical order, Central Asia (5 countries), East Asia (7 countries/regions), North Asia (2 countries), South Asia (8 countries), Southeast Asia (12 countries) and West Asia (17 countries). The population of Asia was reported to be over 4.46 billion in 2016, which is about 60% of the world’s population with an estimated density of 100 people per square kilometre (UNDESA, 2017). The highest life expectancy at birth is 84 years (Japan) and the lowest is 52 years (Afghanistan) (CIA, 2017). The gross domestic product (GDP) per capita ranged from US$587 (Afghanistan) to US$81,585 (Macao, SAR, PRC) (IMF, 2018).
Figure 10.1 | Countries and regions in Asia
Box 10.1 | What Is New on Asia in AR6?
As the most populous continent, Asia is faced with a unique set of challenges that vary across its climatic zones:
Drawing upon a greater number of studies made possible by greater use of advanced research tools, such as remote sensing as well as meticulous modelling of impacts, the Fifth Assessment Report could significantly expand its coverage of pertinent issues (IPCC, 2014c). For example, the discussion on the Himalayas was expanded to cover observed and projected impacts of climate change on tourism (WGII AR5 Section 10.6.2); livelihood assets such as water and food (WGII AR5 Sections 9.3.3.1, 13.3.1.1, 18.5.3, 19.6.3); poverty (WGII AR5 Section 13.3.2.3); culture (WGII AR5 Section 12.3.2); flood risks (WGII AR5 Sections 18.3.1.1, 24.2.1); health risks (WGII AR5 Section 24.4.6.2); and ecosystems (WGII AR5 Section 24.4.2.2; IPCC, 2014b, 2014c).
Knowledge and research gaps identified in AR5 include, but are not limited to, an insufficient understanding of the impacts, vulnerability and adaptation in urban settlements, under-researched linkages between local livelihoods, ecosystem functions and land resources, and a poor understanding of the impacts of projected climate changes on the vegetation of the lowland tropics.
Climate characteristics in Asia are diverse covering all climate zones from tropical to polar, including mountain climate. Monsoonal winds and associated precipitation are dominant in South, Southeast and East Asia. Annual mean surface air temperature averaged over the sub-region ranges from coldest in North Asia (–3°C) to warmest in Southeast Asia (25°C) based on JRA-55 (Kobayashi et al., 2015) climatology for 1981–2010. Most of North Asia and higher altitude is underlain by permafrost. West Asia is the driest and Southeast Asia is the wettest, with the annual precipitation averaged over the sub-region ranging about ten times from 220 mm in West Asia to 2570 mm in Southeast Asia based on GPCC (Schamm et al., 2014) climatology for 1981–2010. Indonesia in Southeast Asia has the longest coastline in the world, causing this area (maritime continent) to be the wettest region (Yamanaka et al., 2018). The Hindu Kush Himalaya (HKH) region is a biodiversity hotspot (Wester et al., 2019) and also has significant impacts on the Asian climate because of its orographic and thermodynamic effects (Wu et al., 2012).
Extreme precipitation events and related flooding occur frequently in monsoon Asia (i.e., Southeast, South and East Asia) (Mori et al., 2021b). Tropical cyclones also affect East and South Asia with torrential rain, strong winds and storm surge. Floods and other weather-related hazards are causing thousands of casualties and millions of people are affected each year (CRED/UNISDR, 2019). On the other hand, droughts have long-lasting effects on agriculture and livestock threatening water security in West Asia, Central Asia and northern China (Ranasinghe et al., 2021; Seneviratne et al., 2021). Adaptation to such extreme events has been limited in Asia.
Observations of past and current climate in Asia are assessed in IPCC WGI AR6 (IPCC, 2021). Examples of observed impacts in Asia with attributed CIDs are shown in Figure 10.2. Surface temperature has increased in the past century all over Asia (very high confidence). Elevation-dependent warming (i.e., the warming rate is different across elevation bands is observed in HMA) (medium confidence) (Hock et al., 2019; Krishnan et al., 2019). While there is an overall trend of decreasing glacier mass in HMA, there are some regional differences and even areas with a positive mass balance due to increased precipitation (Wester et al., 2019). Rising temperatures have resulted in an increasing trend of growing-season length. The number of hot days and warm nights continues to increase in all of Asia (high confidence), while cold days and nights are decreasing except in the southern part of Siberia (Gutiérrez et al., 2021). Large increases in temperature extremes are observed in West and Central Asia (high confidence). Temperature increase is causing strong, more frequent and longer heatwaves in South and East Asia. The 2013 East China heatwaves case is such an example (Xia et al., 2016). In 2016 and 2018, extreme warmth was observed in Asia for which an event-attribution study revealed that this would not have been possible without anthropogenic global warming (medium confidence) (Imada et al., 2018; Imada et al., 2019).
Figure 10.2 | Detection and attribution of observed changes in Asia. Levels of Evidence (E), Agreement (A) and Confidence (C) are ranked by High (H), Medium (M) or Low (L). CID: climate-impact driver. References: (1) Heatwaves (Mishra et al., 2015; Rohini et al., 2016; Chen and Li, 2017; Panda et al., 2017; Ross et al., 2018); (2) Coastal urban flooding (Dulal, 2019); (3) Biodiversity and habitat loss (Wan et al., 2019); (4) Dust storms (Kelley et al., 2015; Yu et al., 2015; Alizadeh-Choobari et al., 2016; Nabavi et al., 2016); (5) Sea level rise (only for coastal cities) (Brammer, 2014; Shahid et al., 2016; Hens et al., 2018); (6) Urban heat island (UHI) effect (Choi et al., 2014; Santamouris, 2015; Estoque et al., 2017; Ranagalage et al., 2017; Kotharkar et al., 2018; Li et al., 2018a; Hong et al., 2019c); (7) Permafrost thawing (Shiklomanov et al., 2017a; Biskaborn et al., 2019); (8) Wildfire (Schaphoff et al., 2016; Brazhnik et al., 2017); (9) Extreme rainfall events (in urban areas) (Ali et al., 2014); (10) Urban drought (Gu et al., 2015; Pervin et al., 2020); (11) Primary production in ocean (Roxy et al., 2016); (12) Flood-induced damages (Fengqing et al., 2005); (13) Agriculture and food systems (Heino et al., 2018; Prabnakorn et al., 2018).
There are considerable regional differences in observed annual precipitation trend (medium confidence). Observations show a decreasing trend of the South Asian summer monsoon precipitation during the second half of the 20th century (high confidence) (Douville et al., 2021). No clear trend in precipitation is observed in high-mountain Asia (Nepal and Shrestha, 2015), while a continuous shift towards a drier condition has been observed since the early 1980s in spring over the central Himalaya (Panthi et al., 2017). Increase in heavy precipitation occurred recently in South Asia (high confidence), and in Southeast and East Asia (medium confidence) (Seneviratne et al., 2021). In Japan, there is no significant long-term trend in the annual precipitation, while significant increasing trend is observed in the annual number of events of heavy precipitation (daily precipitation ≥400 mm) and intense precipitation (hourly precipitation ≥50 mm) (JMA, 2018). Decreased precipitation and increased evapotranspiration are observed in West and Central Asia, contributing to drought conditions and decreased surface runoff.
Annual surface wind speeds have been decreasing in Asia since the 1950s (high confidence) (Ranasinghe et al., 2021). The observed changes in the frequency of sand and dust storms vary from region to region in Asia (medium confidence). The frequency and intensity of dust storms are increasing in some regions, such as West and Central Asia, due to land use and climate change (Mirzabaev et al., 2019). Significant decreasing trends of dust storms are observed in some parts of Inner Mongolia and over the Tibetan Plateau (Ranasinghe et al., 2021). In contrast, West Asia has witnessed more frequent and intensified dust storms affecting Iran and Persian Gulf countries in recent decades (medium confidence) (Nabavi et al., 2016).
There is no significant long-term trend during 1951–2017 in the numbers of tropical cyclones (TCs) with maximum winds of 66.37 km h –1 or higher forming in the western North Pacific and the South China Sea (medium confidence). There are substantial inter-decadal variations in basin-wide TC frequency and intensity in the western North Pacific (Lee et al., 2020a). Numbers of strong TCs (maximum winds of 124.93 km h –1 or higher) also show no discernible trend since 1977 when complete wind-speed data near TC centre become available (JMA, 2018). According to Cinco et al. (2016), for TCs in the Philippines there are no significant trends in the annual number of TCs during 1951–2013. Their analysis showed that the Philippines have been affected by fewer TCs above 124.93 km h –1, but affected more by extreme TCs (above 158.11 km h –1). There has been a significant northwestward shift in TC tracks since the 1980s, and a detectable poleward shift since the 1940s in the average latitude where TCs reach their peak intensity in the western North Pacific (medium confidence) (Lee et al., 2020a).
According to Bindoff et al. (2019), the oceans have warmed unabatedly since 2004, continuing the multi-decadal ocean-warming trends. Their report also summarised that there is increased agreement between coupled model simulations of anthropogenic climate change and observations of changes in ocean heat content (high confidence). Observed SLR around Asia over 1900–2018 is similar to the global mean sea level change of 1.7 mm yr –1, but for the period 1993–2018, the SLR rate increased to 3.65 mm yr –1 in the Indo-Pacific region and 3.53 m yr –1 in the Northwest Pacific, compared with the global value of 3.25 mm yr –1 (Ranasinghe et al., 2021). The extreme SLR has occurred since the 1980s along the coast of China (Feng et al., 2018b).
Ocean acidification continues with surface seawater pH values having shown a clear decrease by 0.01–0.09 from 1981–2011 along the Pacific coasts of Asia (high confidence) (Lauvset et al., 2015). For the western North Pacific along the 137°E line, the trend varies from −0.013 at 3°N to −0.021 at 30°N per decade during 1985–2017 (JMA, 2018). Ocean interior (about 150–800 m) pH also shows a decreasing trend with higher rates in the northern than the southern subtropics, which may be due to greater loading of atmospheric CO2 in the former (JMA, 2018).
Rising temperatures increase the likelihood of the threat of heatwaves across Asia, droughts in arid and semiarid areas of West, Central and South Asia, floods in monsoon regions in South, Southeast and East Asia, and glacier melting in the HKH region (high confidence) (Doblas-Reyes et al., 2021; Ranasinghe et al., 2021; Seneviratne et al., 2021). Confidence in the direction of the projected change in CIDs in Asia are summarised in Table 12.4 of WGI AR6 Chapter 12 (Ranasinghe et al., 2021).
Projections of future changes in annual mean surface air temperature in Asia are qualitatively similar to those in the previous assessments with greater warming at higher latitudes (i.e., North Asia) (high confidence) (Gutiérrez et al., 2021). Projected surface air temperature changes in the Tibetan Plateau, Central Asia and West Asia are also significant (high confidence) (Gutiérrez et al., 2021). The highest levels of warming for extremely hot days are expected to occur in West and Central Asia with increased dryness of land (high confidence) (SR1.5). Over mountainous regions, elevation-dependent warming will continue (medium confidence) (Hock et al., 2019). Glaciers will generally shrink, but rates will vary among regions (high confidence) (Wester et al., 2019). Thawing permafrost presents a problem in northern areas of Asia, particularly Siberia (Parazoo et al., 2018). Temperature rise will be strongest in winter in most regions, while it will be the strongest on summer in the northern part of West Asia and some parts of South Asia where a desert climate prevails (high confidence) (Gutiérrez et al., 2021). The wet-bulb globe temperature, which is a measure of heat stress, is likely 2 to approach critical health thresholds in West and South Asia under the RCP4.5 scenario, and in some other regions, such as East Asia, under the RCP8.5 scenario (high confidence) (Lee et al., 2021a; Seneviratne et al., 2021). The occurrence of extreme heatwaves will very likely increase in Asia. Projections show that a sizeable part of South Asia will experience heat stress conditions in the future (high confidence). It is virtually certain that cold days and nights will become fewer (Ranasinghe et al., 2021).
Projections of future annual precipitation change are qualitatively similar to those in the previous SREX and AR5 assessments (IPCC, 2021). Avery likely large percentage increase in annual precipitation is projected in South and North Asia (high confidence) (Douville et al., 2021; Lee et al., 2021a). Precipitation is projected to decrease over the northwest part of the Arabian Peninsula and increase over its southern part (medium confidence) (Gutiérrez et al., 2021). Both heavy and intense precipitation are projected to intensify and become more frequent in South, Southeast and East Asia (high confidence) (Seneviratne et al., 2021). There will be a large increase in flood frequency in these monsoon regions (Oppenheimer et al., 2019). Without further mitigation efforts, this will lead to continued loss of lives and infrastructure. SR1.5 assessed higher risk from heavy precipitation events at 2°C compared with 1.5°C of global warming in East Asia. A large ensemble-modelling study shows that future warming is expected to further increase winter precipitation, and extreme weather events, such as rain-on-snow, will result in an increase in extreme runoff in Japan (low confidence) (Ohba and Kawase, 2020). Furthermore, the earlier snowmelt will affect energy supply by hydropower.
Monsoon land precipitation likely will increase in East, Southeast and South Asia mainly due to increasing moisture convergence by elevated temperature (high confidence); however, there is low confidence in the magnitude and detailed spatial patterns of precipitation changes at the sub-regional scale in East Asia (Doblas-Reyes et al., 2021). Increasing land–sea thermal contrast and resultant lower tropospheric circulation changes, together with increasing moisture, are projected to intensify the South Asian summer monsoon precipitation (medium confidence). Anthropogenic aerosols greatly modify sub-regional precipitation changes, and their spatio-temporal changes are uncertain (Douville et al., 2021). Monsoonal winds will generally become weaker in a future warming world with different magnitudes across regions (medium confidence). Future changes in sand and dust storms are uncertain.
The global proportion of very intense TCs (category 4–5) will increase under higher levels of global warming (medium to high confidence). Mean global TC precipitation rate will increase (medium to high confidence). Models suggest a reduction in TC frequency but an increase in the proportion of very intense TCs over the western North Pacific in the future; however, some individual studies project an increase in western North Pacific TC frequency (medium confidence) (Cha et al., 2020). In the western North Pacific, some models project a poleward expansion of the latitude of maximum TC intensity, leading to a future increase in intense TC frequency south of Japan (medium confidence) (Yoshida et al., 2017).
Relative SLR associated with climate change in Asia will range from 0.3–0.5 m in SSP1-2.6 to 0.7–0.8 m in SSP5-8.5 for 2081–2100 relative to 1995–2014 (Ranasinghe et al., 2021). In coastal regions, evaluation of SLR is necessary at the regional scale to assess the impacts on coastal sectors. Liu et al. (2016c) investigated the regional-scale SLR using dynamic downscaling from the three global-climate models in the western North Pacific. In their projection in the case following the RCP8.5 scenario, the regional sea level rises along Honshu Island in Japan during 2081–2100 relative to 1981–2000 are 6–25 cm higher than the global mean SLR due to the dynamic response of the ocean circulation. For the impact assessment of coastal hazards, the total SLR included extreme events due to storm surge and high ocean waves, which are influenced by the changes in TCs (Seneviratne et al., 2021). Mori and Takemi (2016) summarised the characteristics of TCs in the western Pacific in the past and in the future, and the extreme value of significant wave height increased in several regions. There is considerable increase in the return levels along the China coast under 2.0°C warming compared with that under the 1.5°C warming scenario (Feng et al., 2018b).
Ocean acidification will continue over the 21st century (virtually certain) (SROCC). Projected decrease in global surface ocean pH from 1986–2005 to 2081–2100 is about 0.145 under RCP4.5 (Lee et al., 2021a).
Diverse and complex climate characteristics in Asia limit climate models’ ability to reasonably simulate the current climate and project its future change (Gutiérrez et al., 2021).
Ecosystems in Asia are characterised by a variety of climate and topographic effects, and can be divided into several distinct areas (Figure 10.3). In addition, valuable ecosystem services provide vital support for human well-being and sustainable development (IPBES, 2018).
Figure 10.3 | Terrestrial ecoregions, large marine ecosystems and major fishing areas of Asia. Large marine ecosystems: 26Mediterranean Sea; 32Arabian Sea; 33Red Sea; 34Bay of Bengal; 35Gulf of Thailand; 36 South China Sea; 37 Sulu-Celebes Sea; 38Indonesian Sea; 47East China Sea; 48Yellow Sea; 49Kuroshio Current; 50 Sea of Japan; 51Oyashio Current; 52 Sea of Okhotsk; 53West Bering Sea; 54Northern Bering and Chukchi seas; 56East Siberian Sea; 57Laptev Sea; 58Kara Sea; 62Black Sea. Developed after Olson et al. (2001), NOAA (2010) and FAO (2019), and made with Natural Earth. Natural Earth is a public domain map dataset archive available athttps://www.naturalearthdata.com/. The software used for generating the map was ArcGIS 10.0. Note that the map is for illustrative purposes only.
Boreal forests and tundra dominate in North Asia: deserts and xeric shrublands in Central and West Asia; and alpine ecosystems in the HKH, Tian Shan, Altai-Sayan, Ural and Caucasus mountain regions. Human-transformed landscapes occupy most parts of other sub-regions. The remaining natural ecosystems in East Asia are temperate broadleaf and mixed forests, and there are subtropical evergreen forests, deserts and grasslands in the West Asia. South Asia has tropical forests and semi-deserts in the northwest, and Southeast Asia is covered mainly by tropical forests (Figure 10.3).
Ocean and coastal regions in Asia have various ecological characteristics, such as high productivity in arctic and subpolar regions, large biodiversity in tropical regions and unique systems in marginal seas. In the atlas of WGI AR6, the ocean biomes in Asia are divided into six sub-regions (WGI AR6 Figure Atlas.4) (Gutiérrez et al., 2021). For the coastal region, the concept of the large marine ecosystem (e.g., see Sherman, 1994) provides the biological characteristics of each marginal/semi-enclosed region and the regions characterised by boundary current system.
Biodiversity and ecosystem services play a critical role in socioeconomic development as well as the cultural and spiritual fulfilment of the Asian population (IPBES, 2018). For example, species richness reaches its maximum in the ‘coral triangle’ of Southeast Asia (central Philippines and central Indonesia) (IPCA, 2017), and the extent of mangrove forests in Asia is about 38.7% of the global total (Bunting et al., 2018). These coastal ecosystems provide multiple ecosystem services related to food production by fisheries/aquaculture, carbon sequestration, coastal protection and tourism/recreation (Ruckelshaus et al., 2013).
In the six sub-regions of Asia, nature and biophysical impacts of climate change are observed in three climate-change hotspots where strong climate signals and high concentrations of vulnerable people are present, namely in semiarid, glacial-fed river basins and mega deltas (De Souza et al., 2015; Kilroy, 2015; Szabo et al., 2016b). The impacts of global climate events also have profound social implications, threatening human health and well-being, destabilising assets, weakening coping capacities and response infrastructures and substantially increasing the number of socially, economically and psychologically vulnerable individuals and communities (Ford et al., 2015).
Vulnerability to climate change varies by geography and by the economic circumstances of the exposed population (Sovacool et al., 2017). The concentration of population growth in less developed regions means that an increasing number of people live in countries with the least ability to adapt to climate change (Auffhammer and Kahn, 2018). Bangladesh with 163 million people, an example, is one of the most vulnerable countries in the world to climate risks and natural hazards, and faces severe floods, cyclones, droughts, heatwaves and storm surges on a regular basis (Dastagir, 2015; Hossain et al., 2018; Roy and Haider, 2019).
Differential human vulnerability to environmental hazards results from a range of social, economic, historical and political factors, all of which operate at multiple scales (De Souza et al., 2015; Thomas, 2019). Climate change is expected to have serious impacts on people living within these hotspot areas, as observed from loss of food crop yields to disasters such as floods, fluctuations in seasonal water availability or other systemic effects (De Souza et al., 2015). For instance, in South Asia, extreme climatic conditions are threatening food security; thus, agro-based economies, such as those of India and Pakistan, are the most vulnerable to climate change in this regard (Mendelsohn, 2014; Ahmad, 2015; Kirby et al., 2016; Ali et al., 2017).
A broad-based understanding of gender vulnerability in the context of poverty and social discrimination, as well as diverse social and cultural practices in different political, geographic and historical settings, apart from climate variability along with environmental and natural risks, is central to understanding people’s capacities to cope with, and adapt to change (Morchain et al., 2015; Yadav and Lal, 2018; Rao et al., 2019). Studies highlight the fact that disasters do not affect people equally; mostly findings show that insufficient disaster education, inadequate protection measures and powerful cultural issues, both pre- and post-disaster, increase women’s vulnerability during and after disasters (Isik et al., 2015; Reyes and Lu, 2016; Hamidazada et al., 2019). In particular, cultural issues play a role after disasters by affecting women’s security, access to disaster aid and health care (Raju, 2019). There must be more nuanced understanding and examination of gender, as well as poor, disadvantaged and vulnerable groups, in vulnerability and risk assessments (Reyes and Lu, 2016; Reyer, 2017; Xenarios et al., 2019).
Based on the ‘World Economic Situation and Prospects as of mid-2019 Report’, the region has an estimated 400 million people living in extreme poverty below the threshold of 1.90 USD d –1. At the higher international poverty line of 3.20 USD d –1, the number of poor rises to 1.2 billion people, accounting for more than a quarter of the region’s total population (Holland, 2019). Beyond monetary measures, indicators of multi-dimensional aspects of poverty, most notably in Southern Asia, indicate that a large share of the population still lacks access to basic infrastructure and services (Bank, 2017b).
For instance, South Asia illustrates that on average it could lose nearly 2% of its GDP by 2050, rising to a loss of nearly 9% by 2100 under a business-as-usual scenario (Ahmed and Suphachalasai, 2014). The relationship between economic outcomes and cross-sectional climate variation is confounded by regional heterogeneity, including historical effects of settlement and colonisation (Dell et al., 2014; Newell et al., 2018). Climate change vulnerability may also depend on sufficient employment opportunities in the risk-prone areas, land-holding size, gender, education level, and family and community size, as observed in Nepal, Thailand and Vietnam (Baul and McDonald, 2015; Lebel L., 2015; Phuong et al., 2018a).
As poor households are constrained in their ability to receive nutrition, schooling and health care for their children, this is greatly dampening progress in human capital development and productivity growth, both of which are critical imperatives for sustainable development (Carleton and Hsiang, 2016; Schlenker and Auffhammer, 2018). Studies also have shown negative impacts of climate change on several essential components of people’s livelihoods and well-being, such as water supply, food production, human health, availability of land and ecosystems (Alauddin and Rahman, 2013; Arnell et al., 2016; Roy and Haider, 2019).
Major population trends of urbanisation and urban area expansion are forecast to take place in Asia. It has been mentioned that demographic change will make humanity more vulnerable to climate change, particularly in places with high poverty rates and potentially prone to systemic disruptions in the food system (Puma et al., 2015; d’Amour et al., 2016; d’Amour et al., 2017).
The urban population of the world has grown rapidly from 751 million in 1950 to 4.2 billion in 2018. Asia, despite its relatively lower level of urbanisation, is home to 54% of the world’s urban population (United Nations, 2019). Some cities have experienced population decline in recent years. Most of these cities are located in the low-fertility countries of Asia, where overall population sizes are stagnant or declining, as observed in a few cities in Japan and the Republic of Korea (e.g., Nagasaki and Busan), which experienced a population decline between 2000 and 2018 (United Nations, 2019). By 2030, the world is projected to have 43 megacities with more than 10 million inhabitants, most of them in developing regions. However, some of the fastest-growing urban agglomerations are cities with fewer than 1 million inhabitants, many of them located in Asia and Africa (United Nations, 2019). Challenges with water supply, in many cases, have existed for decades (Dasgupta, 2015). Climate change increases these challenges (Hoque et al., 2016). As more people inhabit urban areas, the number of people vulnerable to heat stress is thus likely to rise, a problem that will be compounded by rising temperatures due to climate change (Acharya et al., 2018). Compared with rural areas, hot temperature risk is even higher in urban regions (Luo, 2018a; Ye, 2018; Setiawati Martiwi Diah, 2021).
The impact of heat in rural areas has been a blind spot so far, particularly for farmers and outdoor labourers who are increasingly exposed to high outdoor temperatures due to increased intensity in agriculture combined with changes in working hours (Tasgaonkar, 2018).
Farmers as a group have shown an increasing number of females over the years due to migration of male members into urban areas for employment, which is putting women at more severe risk in the context of climate variability (Singh, 2019). Women are required to acquire new capacities to manage new challenges, including risks from climate change, through capacity-building interventions to strengthen autonomous-adaptation measures (Banerjee et al., 2019; James, 2019; Mishra, 2019). However, the overlapping crises of climate change and the global public health crisis of COVID-19 represent a major challenge to gender equality and sustainable development (Katherine Brickell, 2020; Sultana, 2021).
For vulnerable populations, such as Indigenous Peoples, older and low-income groups, women, children, people with disabilities and minorities, the health effects of climate-change-related extreme weather events can be especially devastating (McGill, 2016). Such populations may be more susceptible to disease, have pre-existing health conditions or live in areas that do not promote good health or well-being; for instance, loss of income and food supply shortages could lead children in rural households to nutritional deprivations that can have both immediate and lifelong impacts (Gleick, 2014; UNICEF, 2015). Children, already susceptible to age-related insecurities, face additional destabilising insecurities from questions about how they will cope with future climate change (Hansen et al., 2013).
Energy consumption of Asia accounts for 36% of the global total at present. China, India and the ASEAN countries have largely contributed to the ever-growing global energy consumption. Asia is predicted to account for 80% of coal, 26% of natural gas and 52% of electricity consumption of the world by 2040 (IEA, 2018). The share of Asia in the global primary energy consumption will increase to 48% by 2050. China continues to be the world’s largest energy consumer, and the combined consumption of India and ASEAN will be similar to that of China by that time (IEEJ, 2018).
The current energy structure of Asia is dominated by fossil fuels. As the trend indicates, the share of coal in China’s primary energy consumption is forecasted to sharply decline from 60% in 2017 to around 35% in 2040 (BP, 2019). In contrast, India and ASEAN rely more on coal since coal may meet their soaring energy demand. Accordingly, more than 80% of the global coal will be consumed in Asia by 2050. China will surpass the USA in about 10 years to become the world’s largest oil consumer. India will then replace the USA to be the second largest by the late 2040s (IEEJ, 2018).
Around 60% of the incremental electricity demand globally, predicted to double by 2050, will occur in Asia. By that time, the electrification rate will increase to 30%, but 40% of electricity demand will be still covered by coal (IEEJ, 2018). Asia accounts for almost half of the growth in global renewable power generation. It is hardly possible for Japan and Republic of Korea to develop additional nuclear power plants as planned, whereas nuclear generation continues to increase quickly in China and the scale will be similar to the entire generation of OECD by 2040 (BP, 2019). India and Russia’s nuclear power sectors are also growing fast (e.g., the recent launch of the Akademik Lomonosov offshore nuclear power plant in Russia).
The rapid growth of energy demand in Asia reinforces the region’s position as the largest energy importer (BP, 2019). Around 80% of energy traded globally will be consumed in Asia, and the rate of self-sufficiency will decrease from 72 to 63% by 2050. This tendency is especially remarkable for ASEAN, which will become a net importer in the early 2020s. The self-sufficiency rate of coal will be maintained at a level of 80%, while that of oil and natural gas will decline significantly. The additional oil imports of the emerging Asian economies will be from North America, the Middle East and North Africa. The main players in Asia for the liquefied natural gas imports will extend from Japan and Republic of Korea to China and India. ASEAN has been a net exporter of natural gas but starts to expand its importation due to the increased consumption and resource depletion (IEEJ, 2018).
The increase in energy demand at a rapid rate in these countries thus cannot be attributed only to population growth and rising living standards, but also to increasingly extreme temperature variations. The decrease in precipitation influences energy demand as well, as countries are becoming more dependent on energy-intensive methods (e.g., desalination, underground water pumping) to supply water. Similarly, energy systems are influenced by the way the agriculture sector, mainly in Al Mashrek, relies increasingly on energy-intensive methods (e.g., more fertilisers, different irrigation and harvesting patterns) (Farajalla, 2013).
Climate change has direct and indirect impacts on energy and industrial systems. It has a particularly wide and profound impact on energy systems (energy development, transportation, supply, etc.). With global warming, the energy consumption for heating in winter decreases, while the energy consumption for cooling in summer significantly increases, but the overall energy demand shows an upwards trend (high confidence) (Sailor, 2001; Szabo et al., 2018). Such demands in summer seasons will by far exceed any energy savings from the decrease in heating demand due to warmer winters. Higher demand for cooling due to hotter temperatures has become a major challenge in the energy sector in all countries. Furthermore, decreased water levels due to lower precipitation reduces hydroelectric output. This is particularly the case for countries such as Syria and Iraq with large hydroelectric capacity (Hamid and Raouf, 2009). Additionally, the decrease in water levels negatively affects low-carbon energy systems such as concentrated solar power and thermal-generation plants that require regular cooling and cleaning.
Climate change adds extra pressure to current energy infrastructures in most countries where systems failures and blackouts are already common (Assaf, 2009). In the wake of extreme weather events (e.g., heatwaves), energy infrastructures remain inadequate to cope. This is particularly the case for countries such as Lebanon, Syria, Jordan and Palestine, with poor electricity infrastructures (Jordan, 2015). Extreme weather events could generate grave damage to power plants, most being located only a few metres above sea level, as well as power-transmission towers and lines. In Lebanon, a small country where there are no Indigenous energy resources, the disruption of shipping of fuel supplies due to extreme weather events is a major risk. Other extreme weather events, such as floods and sandstorms, expose energy and industrial systems in the coastal areas due to a rise in sea level. Countries of the Arabian Peninsula are projected to experience significant inland flooding as sea levels rise (Hamid and Raouf, 2009). In East Asia wet snow accretion enhanced by global warming often causes damage to electric power lines (Sakamoto, 2000; Ohba and Sugimoto, 2020).
Universal energy access is a big challenge for Asia (IEA, 2018). About 230 million Indian people lack access to electricity, and around 800 million still use solid fuels for cooking (Sharma, 2019). The average electricity access rate in South Asia was 74%, the equivalent of 417 million people without electricity and accounting for more than a third of the global 1.2 billion lacking the access (Shukla et al., 2017). With a total population of nearly 640 million in ASEAN, an estimated 65 million people remain without electricity and 250 million rely on solid biomass for cooking fuel (IEA, 2017). Universal access to electricity is expected to be achieved by 2030, while 1.6 billion people in Asia will still lack clean energy for cooking (UNESCAP, 2018b).
Asia faces an energy security problem even with the rapid growth in production and trade (IEEJ, 2018). Among 13 developing countries with large energy consumption in Asia, 11 are exposed to high energy security risk (WEC, 2018). This will be a major challenge for the sustainable development of Asia due to the vulnerability to global energy supplies and price volatility (Nangia, 2019). Asia lacks natural energy resources and has the smallest oil reserve but largely relies on fossil fuels. The dependency on fossil fuels was as high as 88.3% in China, 72.3% in India, 89.6% in Japan and 82.8% in Republic of Korea in 2013 (BP, 2014). Many countries in South Asia rely on a single source to supply more than half of the electricity (i.e., 67.9% from coal for India, 99.9% from hydropower for Nepal, 91.5% from natural gas for Bangladesh and 50.2% from oil for Sri Lanka) (Shukla et al., 2017). Additionally, cooperation in Asia to create the integrated energy systems needed for enhancing overall security is still at a very preliminary stage due to countries having different strategic plans and lack of cooperation among them on the common concerns (Kimura and Phoumin, 2013).
Even though energy efficiency is improving, the deployment of low-carbon energy, such as renewables, is not sufficient in Asia. To be consistent with the temperature goal of the Paris Agreement, the share of renewables in total energy consumption needs to reach 35% in Asia by 2030. Moreover, the financing to deploy renewables presents another considerable challenge (UNESCAP, 2018b).
In order to cope with climate change, renewable energy has become the core of energy development and transformation. Since the 1960s, the total solar radiation on the ground in Asia has shown a downwards trend as a whole, which is consistent with the change in global total solar radiation on the ground, and has experienced a phased change process of ‘first darkening and then brightening’ (high confidence). This conclusion has been further confirmed by ground station observations, satellite remote sensing inversion data and model simulation research (Wang and Wild, 2016; Qin et al., 2018; Yang et al., 2018a).
However, wind speed over most Asian regions is obviously decreasing (high confidence). Based on meteorological observation records or reanalysis data, many studies have analysed the variation of near-surface average wind speed in Asia. It is generally found that wind speed has declined since the 1970s, although the declining trend is different in different subregions. (Yang et al., 2012c; Lin et al., 2013; Liu et al., 2014b; Zha et al., 2016; Guo et al., 2017a; Torralba et al., 2017; Wu et al., 2017a; Ohba, 2019). The decline of near-surface wind speed in Asia is consistent with the general decline of global land-surface wind speeds, among which the frequency of strong winds and the decline of wind speed are more prominent (McVicar et al., 2012; Jiang et al., 2013; Blunden and Arndt, 2017; Wu et al., 2018c). Since the early 2010s, the average wind speed in the world and some parts of Asia has shown signs of increasing (Li et al., 2018d; Wu et al., 2018c; Zeng et al., 2019), which seems to be an inter-decadal variability. Whether this means a change in its trend needs the support of longer observation data.
At the same time, with the increase in the proportion of renewable energy in the power system, the power system will be more vulnerable to climate change and extreme weather and climate events, and the vulnerability and risk of the power system will greatly increase (medium confidence).
The overall solution would be to develop a resilient energy system and avoid the risk of unsustainable energy growth in developing Asia. This requires that strategic planning be consistent with the long-term climate projection, impact and adaptation (EUEI-PDF, 2017). Although no single policy package would be applicable for all the countries across the region, several measures could be addressed as the common options, including fortification of energy infrastructure and diversification of the sources by sufficient investment, improvement of energy efficiency for sector flexibility, and promotion of regional cooperation and integration for increasing energy security (UNESCAP, 2018b). Adaptation also includes promoting renewable energy resources, securing local natural gas resources, enhancing water production and adopting green-building technologies. These adaptation measures may help increase readiness for the anticipated impact of climate change.
The improvement of energy efficiency and demand-side management can alleviate supply constraints and thus lower overall required-energy capacity. Energy storage, smart grids for the electricity network as well as other flexible management measures enable this energy demand shifting. Regional integration of energy markets drives productivity increase, cost reduction, new investment, human capability and diversity of energy sources (WEC, 2018). For example, better interconnection of natural gas supply networks among the ASEAN countries enhances gas security in the region. The development of the long-planned regional power grid would make large-scale renewable projects more viable and aid the integration of rising shares of wind and solar power (IEA, 2017).
Providing enough investment in energy supply is a top priority to extend the connections to those without access to electricity and satisfy the soaring demand (IEA, 2017). The investment in non-fossil energies like renewables has been expanding to leverage the economic growth in China, India and Republic of Korea. According to the updated estimate of ADB, 14.7 trillion USD will be needed for the infrastructure development in the power sector of developing Asia over the 15 years from 2016 to 2030 (ADB, 2017a). The cumulative investment needs of ASEAN for energy supply and efficiency up to 2040 is estimated at 2.7 to 2.9 trillion USD (IEA, 2017). Mobilising investment to such a scale will require significant participation from the private sector and international financial institutions.
Diversifying energy sources increases energy security and thus the resilience of the whole system. The deployment of renewable energy is widely recognised as a crucial measure for enhancing energy access and diversity. There remains huge potential for renewable sources in Asia (i.e., India has massive solar power potential) (Shukla et al., 2017). Many renewable technologies (i.e., hydro- and wind power as well as solar photovoltaics) are becoming competitive, and their life-cycle costs may fall below those of coal and natural gas in the near term. Great progress has been made in enhanced geothermal systems (EGS), and in the conventional and unconventional fusion power that China is promoting. Conventional and underground pumped hydropower will level out supplies for intermittent renewable energy generation.
Substantial progress may be fulfilled by increasing the share of renewable energy in the overall energy consumption of Asia (ADB, 2017a). Access to energy, particularly in rural areas, can reduce climate vulnerability of developing Asia. Due to the high cost of extending the electricity network to rural regions, an alternative way is to develop the off-grid renewable energy systems in these areas. The distributed, instead of centralised, energy systems can increase energy access and resilience (EUEI-PDF, 2017).
Some countries in the Arabian Peninsula, such as the United Arab Emirates (UAE), are adopting an array of approaches to enhance the adaptive capacity of the energy infrastructure and diffuse the risk of climate change over a larger area (e.g., energy efficiency, demand management, storm planning for power plants). In Al Mashrek, building institutional capacity in the energy sector is a necessary first step to mainstream climate-change adaptation (CCA). Countries such as Lebanon and Jordan have already made progress in mainstreaming CCA into electricity infrastructure. In the UAE, buildings account for more than 80% of the total electricity consumption. There are currently a set of measures and regulations on building conditions and specifications that are being applied to increase energy efficiency in buildings, but the rehabilitation and upgrading of old buildings still require further efforts (Environment, 2015). In Kuwait, one adaptation measure to dust storms is through the reduction of the proportion of open-desert land from 75 to 51%, the increase in protected areas from 8 to 18% and greenbelt projects in desert areas (Kuwait, 2015). Addressing climate-change impact on energy systems in Lebanon, Jordan, Syria, Iraq and Palestine needs to simultaneously consider other interlinked challenges of population growth, rapid urbanisation, refugee influx, conflict and geopolitical location. To address these challenges and provide solutions for CCA, the promotion of multi-stakeholder partnerships is key to breaking the silo approach.
These CCA measures need to be broadened to fit the scope and depth of mitigation efforts by each country. Risk assessments and vulnerability assessments are in their early stages in the energy and industrial sectors, and are not currently based on a comprehensive plan of action. The first step is to undertake comprehensive national assessments of the risks associated with climate change based on existing studies on climate impacts and risks, and by making evidence-based decisions on adaptation actions.
Box 10.2 | Migration and Displacement in Asia
Migration is a key livelihood strategy across Asia and is driven by multiple factors such as socioeconomic changes, increasing climate variability and disaster incidence, and changing aspirations. Displacement denotes a more involuntary movement in reaction to climatic or non-climatic factors. There is robust evidence, medium agreement that increased climate variability and extreme events are already driving migration (Gemenne et al., 2015; Rigaud et al., 2018 ; IDMC, 2019; Jacobson et al., 2019; Siddiqui et al., 2019; IDMC, 2020; Maharjan et al., 2020) and medium evidence, medium agreement projecting that longer-term climate change will increase migration flows across Asia (Abubakar et al., 2018; Rigaud et al., 2018 ; Hauer et al., 2020; Bell et al., 2021).
Detection and attribution: Does climate change drive migration?Ascertaining the role of climate change in migration is difficult and contested (see Cross-Chapter Box MIGRATE in Chapter 7 and RKR-H in Chapter 16), with observation-based studies either linking extreme event incidence, weather anomalies and environmental change with migration numbers or drivers (McLeman, 2014; Singh et al., 2019a; Kaczan and Orgill-Meyer, 2020), and projection studies looking at particular risks such as SLR or drought by linking increasing warming (often through representative concentration pathways, RCPs) and population growth. Despite methodological disagreement on detection and attribution of migration due to climate change, there is medium confidence that higher warming and associated changes in frequency and intensity of slow-onset events (such as drought and sea level rise) and rapid-onset events (such as cyclones and flooding) will increase involuntary displacement in the future, especially under SSP3 and SSP4 pathways (Dasgupta et al., 2014a; Davis et al., 2018; Rigaud et al., 2018 ; Hauer et al., 2020). But its role is smaller than non-climatic socio-economic drivers of migration (Wodon et al., 2014; Adger et al., 2021).
Current migration and displacement. One in three migrants comes from Asia and the highest ratio of outward migrants is seen from hazard-exposed Pacific countries (Ober, 2019). In 2019, approximately 1900 disasters triggered 24.9 million new displacements across 140 countries; in particular, Bangladesh, China, India and the Philippines each recorded more than 4 million disaster displacements (IDMC, 2019). Tajikistan, Kyrgyzstan and Russia see significant disaster-associated displacements: for example, heavy rain-induced flooding in Khatlon (Tajikistan) triggered 5400 new displacements; landslides in the Jalal-Abad (Kyrgyzstan) saw 4700 new displacements; and floods in Altai, Tuva and Khakassia (Russia) displaced 1500 people. Iran reported the highest sub-regional figures with >520,000 new disaster-related displacements in 2019 (IDMC, 2019). In Southeast and East Asia, cyclones, floods and typhoons triggered internal displacement of 9.6 million people in 2019, almost 30% of total global displacements (IDMC, 2019). With most migrants in the region being temporary migrant workers, loss of jobs and wages among them have been particularly severe due to adverse economic climate triggered by COVID-19 (ESCWA, 2020). It has also resulted in large-scale returns of migrant workers, and remittances have declined drastically (Khanna, 2020; Li et al., 2021). Remittances to Eastern Europe and Central Asia are expected to decline 16.1% from 57 billion USD in 2019 to 48 billion USD in 2020. Remittances in East Asia and the Pacific are estimated to fall 10.5% over the same period, from 147 billion to 131 billion USD (United Nations, 2020). The COVID-19 pandemic has had significant impacts on migrants (Rajan, 2020) in the region, and some countries have targeted migrants in economic stimulus packages or income-support programmes; however, access to such support has been heterogeneous.
Projected migration. Regional variation is significant across Asia. By one estimate, in South Asia, internal climate migrants (i.e., those migrating due to climate change and associated impacts such as water scarcity, crop failure, SLR and storm surges) are projected to be 40 million by 2050 (1.8% of regional population) under high warming (Rigaud et al., 2018 ). While methodological critiques remain on projected migration estimates, what is certain is that some countries will be more affected that others; it is estimated that in southern Bangladesh, SLR could displace 0.9–2.1 million people by direct inundation by 2050 (Jevrejeva et al., 2016; Davis et al., 2018). In South Asia, migration hotspots include the Gangetic Plain and the Delhi–Lahore corridor, and coastal cities such as Chennai, Chittagong, Dhaka and Mumbai, which will be simultaneously exposed to climate-change impacts, major migration destinations and amplified rural–urban migration (Ober, 2019). Importantly, there is low agreement on projected numbers (see Boas et al., 2019) with uncertainties around how local policies and individual behaviours will shape migration choices. Even in high-risk places, people might choose to stay or be unable to move, resulting in ‘trapped’ populations (Zickgraf, 2019; Ayeb-Karlsson et al., 2020). There is currently inadequate evidence to ascertain the nature and numbers of trapped populations currently or in the future.
Implications of migration for adaptation. The evidence on migration and its impacts on adaptive capacity and risk reduction are mixed (Upadhyay, 2014; Banerjee et al., 2018; Szabo et al., 2018; Maharjan et al., 2020; Singh and Basu, 2020). Financial remittances help vulnerable households spread risk through better incomes, expanded networks and improved assets such as housing, education and communication technology (Jha et al., 2018; Szabo et al., 2018; Ober, 2019; Maharjan et al., 2020). Benefits from international remittances across the Asia Pacific region were approximately 276 billion USD in 2017 (UN, 2018), and in countries such as Kyrgyzstan, Tajikistan and Nepal remittances were ~25% of the national GDP in 2015. However, migration requires a minimum level of resources, and liquidity constraints impede internal migration by the poorest households often rendering them immobile (Ayeb-Karlsson et al., 2020; Maharjan et al., 2020). Furthermore, migration does not necessarily mean that people move out of risk; in fact, often they might be subjected to new risks. Notably, migrants in South and Southeast Asia have been severely affected by the compounding crises of disasters and the COVID-19 pandemic, and there is emerging evidence that inclusion of universal safety-net provisions that embed adaptation planning can reduce vulnerabilities of migrants (Sengupta and Jha, 2020; Cundill et al., 2021; Sultana, 2021).
While there is robust evidence (medium agreement ) that migration exacerbates gendered vulnerability and work burdens (Banerjee et al., 2019; Singh, 2019; Rao et al., 2020), it is well established that differential vulnerability of migrants intersects with ethnicity, age and gender; political networks and social capital; and livelihoods in destination areas (Maharjan et al., 2020; Cundill et al., 2021). Across Asia, international and internal migration are changing social norms and household structures, with significant implications for local adaptive capacity (Singh, 2019; Evertsen and van der Geest, 2020; Porst and Sakdapolrak, 2020; Rao et al., 2020).
Sub-regional diversity of ecosystems is high in Asia (Section 10.2.2). Climate-impact drivers of Asian terrestrial ecosystems (ATS) change are global warming, precipitation and Asian monsoon alteration, permafrost thawing and extreme events like dust storms. Observed and projected changes in ATS are affected by several interacting factors. Non-climatic human-related drivers are change of land use, change of human use of natural resources, including species and ecosystems overexploitation as well as other non-sustainable use, socioeconomic changes and direct impacts of rising greenhouse gases (GHGs). Ecosystem vulnerability has resulted from complex interactions of CIDs and non-climate drivers. Species interaction and natural variability of organisms, species and ecosystems is currently poorly understood, and much more work still needs to be done to unravel these multiple stressors (i.e., Berner et al., 2013; Brazhnik and Shugart, 2015).
Changes in biomes in Asia are compatible with a response to regional surface air temperature increase (Arias et al., 2021) (medium agreement, medium evidence). Expansion of the boreal forest and reduction of the tundra area is observed for about 60% of latitudinal and altitudinal sites in Siberia (Rees et al., 2020). In Central Siberia, the changes in climate and disturbance regimes are shifting the southern taiga ecotone northward (Brazhnik et al., 2017). In Taimyr, no significant changes in the forest boundary have been observed during the past three decades (Pospelova et al., 2017). For the Japanese archipelago, it is suggested that the change in tree community composition along the temperature gradient is a response to past and/or current climate changes (Suzuki et al., 2015).
Alpine treeline position in Asian mountains in recent decades either moves upwards in North Asia or demonstrates multi-directional shifts in Himalaya (high confidence). Since AR5, in North Asia new evidence has appeared of tree expansion into mountain tundra and steppe, of intensive reproduction and increase in tree stands productivity in the past 30–100 years at the upper treeline in the Ural Mountains (Shiyatov and Mazepa, 2015; Zolotareva and Zolotarev, 2017; Moiseev et al., 2018; Sannikov et al., 2018; Fomin et al., 2020; Gaisin et al., 2020), in the Russian Altai Mountains (Kharuk et al., 2017a; Cazzolla Gatti et al., 2019) and in the Putorana Mountains (Kirdyanov et al., 2012; Pospelova et al., 2017; Grigor’ev et al., 2019). Lower treelines in the southernmost Larix sibirica forests in the Saur Mountains, eastern Kazakhstan, have suffered from increased drought stress in recent decades causing forest regeneration and tree growth decrease, and tree mortality increase (Dulamsuren et al., 2013). In Jeju Island, Republic of Korea, recent warming has enhanced Quercus mongolica growth at its higher distribution and has led to Abies koreana (ABKO) growth reduction at all elevations, except the highest locality. Thus, the combination of warming, increasing competition and frequent tropical cyclone disturbances could lead to population decline or even extinction of ABKO at Jeju Island (Altman et al., 2020). In the Himalaya, the treeline over recent decades either moves upwards (Schickhoff et al., 2015; Suwal et al., 2016; Sigdel et al., 2018; Tiwari and Jha, 2018) or does not show upslope advance (Schickhoff et al., 2015; Gaire et al., 2017; Singh et al., 2018c), or moves downwards (Bhatta et al., 2018). In the Tibetan Plateau, the treeline either shifted upwards or showed no significant upwards shift (Wang et al., 2019c). This can be explained by site-specific complex interaction of positive effect of warming on tree growth, and negative effects of drought stress, change in snow precipitation, inter- and intraspecific interactions of trees and shrubs, land-use change (especially grazing) and other factors (Liang et al., 2014; Lenoir and Svenning, 2015; Tiwari et al., 2017; Sigdel et al., 2018; Tiwari and Jha, 2018; Sigdel et al., 2020). It is largely unknown how broader-scale climate inputs, such as pre-monsoon droughts, interact with local-scale factors to govern treeline response patterns (Schickhoff et al., 2015; Müller et al., 2016; Bhatta et al., 2018; Singh et al., 2019b).
Since AR5, new evidence has appeared of alterations in terrestrial and freshwater species, populations and communities in line with climate change across Asia (medium to high confidence) (Arias et al., 2021). In North Asia, temperature increase and droughts have promoted spread northward of the current silk moth outbreak (has affected nearly 2.5 × 106 ha) in Central Siberia dark taiga since 2014 (Kharuk et al., 2017b; Kharuk et al., 2020). The climatic range of the Colorado potato beetle (Leptinotarsa decemlineata) in 1991–2010 expanded east- and northward in Siberia and the Russian Far East compared with the 1951–1970 range (Popova, 2014). The climatic range of Ixodes ricinus, a vector of dangerous human diseases, expanded into Central Asia and south of the Russian Far East (Semenov et al., 2020). A butterfly (Melanargia russiae) in the Middle Urals moved northward (Zakharova et al., 2017). Thrush birds in West Siberia penetrated northward up to the limits of the sparse woodlands (Ryzhanovskiy, 2019a). The increase in the length of frost-free period observed in the Ilmen Nature Reserve, Middle Urals, during recent decades is supposed to be interlinked with changes in the amplitude and frequency of population waves of bank vole (Kiseleva, 2020). In Katunskiy Biosphere Reserve, Russian Altai, in the period 2005–2015, alpine plant species have shifted towards higher altitudes by 5.3 m on average (Artemov, 2018). Wild reindeer herds in Taimyr, north of Central Siberia, migrated northward to the Arctic Sea coast in hot summers between 1999–2003 and 2009–2016 because of an earlier massive emergence of bloodsucking insects (Pospelova et al., 2017). In Yakutia, the ranges of red deer, elk and the northern pika are expanding, and the winter survival of the mouse-like rodents has increased (Safronov, 2016). In the Chukchi Sea, in recent decades the average duration polar bears spent onshore increased by 30 d (Rode et al., 2015b) in line with global warming and the rapid decline of their sea ice habitat (Derocher et al., 2013; Jenssen et al., 2015; Rode et al., 2015a).
In Central Kazakh Steppe, in line with warming, in 2018 there were more ‘southern’ sub-arid species in the communities and fewer relatively ‘northern’ boreal and polyzonal species of ground beetles (Carabidae) and black beetles (Tenebrionidae) than in 1976–1978 (Mordkovich et al., 2020). The present distribution of Asian black birch (Betula davuricaPall.) in East and North Asia was formed as a result of northward expansion during post-Last Glacial Maximum global warming (Shitara et al., 2018). Both upper and lower limits of avifauna of two New Guinean mountains, Mt. Karimui and Karkar Island, have been shifting upslope since 1965 (Freeman and Freeman, 2014). In Republic of Korea, for the past 60 years, the northern boundary line of 63 southern butterfly species has moved further north (Bae et al., 2020). The change in the butterflies’ occurrence in this period has been influenced mostly by large-scale reforestation, not by climate change (Kwon et al., 2021). Warming-driven geographic range shift was recorded in 87% of 124 endemic plant species studied in the Sikkim Himalaya in the periods 1849–1850 and 2007–2010 (Telwala et al., 2013). In Darjeeling, India, significant change in lichen community structure was shown in response to climate change and anthropogenic pollution (Bajpai et al., 2016).
The observed loss of biodiversity and habitat of animals and plants has been linked to climate change in some parts of Asia (high confidence). Climate change, together with human disturbances, have caused local extinction of some large and medium-sized mammals during the past three centuries in China (Wan et al., 2019). Climate change has shown significant impacts on subalpine plant species at low altitudes and latitudes in Republic of Korea and may impose a big threat to these plant species (Adhikari et al., 2018; Kim et al., 2019c). Climate change has caused habitat loss of amphibians (Surasinghe, 2011) and extinction of some endemic species in Sri Lanka (Kottawa-Arachchi and Wijeratne, 2017).
There is evidence that climate change can alter species interaction or spatial distribution of invasive species in Asia (high confidence). Climate warming has enhanced the competitive ability of the native species (Sparganium angustifolium) against the invasive species (Egeria densa) in China under a mesocosm experiment in a greenhouse (Yu et al., 2018e). It has also increased the non-target effect on a native plant (Alternanthera sessilis) by a biological control beetle (Agasicles hygrophila) in China due to range expansion of the beetle and change of phenology of the plant (Lu et al., 2015). Climate warming has expanded the distribution of invasive bamboos (Phyllostachys edulis and P. bambusoides) northward and upslope in Japan (Takano et al., 2017), while soil dry-down rates have been a key driver of invasion of dwarf bamboo (Sasa kurilensis) in central Hokkaido above and below the treeline (Winkler et al., 2016).
Climate change along with land-use and land-cover change influences soil organic carbon content, microbial biomass C, microbial respiration and the soil carbon cycle in the Hyrcanian forests of Iran (Soleimani et al., 2019; Francaviglia et al., 2020). In the fir forest ecosystems of the Tibetan Plateau, winter warming affects the ammonia-oxidising bacteria and archaea, thus altering the nitrogen cycle (Huang et al., 2016). Ecosystem carbon pool in the spruce forests of the northeast Tibetan Plateau was reduced by about 25% by deforestation due to recent decades of climate warming as well as wood pasture and logging (Wagner et al., 2015). In Mongolia’s forest steppe, recent decades of drought- and land-use-induced deforestation has reduced the ecosystem carbon stock density by about 40% (Dulamsuren et al., 2016). In Inner Mongolia, the predicted decreases in precipitation and warming for most of the temperate grassland region could lead to a pH change, which would contribute to a soil C-N-P decoupling that could reduce plant growth and production in arid ecosystems (Jiao et al., 2016).
In Central Asia, in the Vakhsh, Kafirnigan and Kyzylsu river basins, Tajikistan, it has been shown that temperature stimulates algal species diversity, while precipitation and altitude suppress it (Barinova et al., 2015). In line with the warming of Lake Baikal, Russia, since the 1990s in the lake’s south basin, there have been shifts in diatom community composition towards higher abundances of the cosmopolitan Synedra acus and a decline in endemic species, mainly Cyclotella minuta and Stephanodiscus meyerii, and to a lesser extent Aulacoseira baicalensis and A. skvortzowii (Roberts et al., 2018). In Gonghai Lake, North China, diatom biodiversity has increased remarkably from 1966, but began to decline after 1990 presumably in response to rapid climate warming (Yan et al., 2018).
Climate change, human activity and lightning determine increases in wildfire severity and area burned in North Asia (high detection with medium-to-low attribution to climate change). In North Asia, the extent of fire-affected areas in boreal forest can be millions of hectares in a single extreme fire year (Duane et al., 2021) and nearly doubled between 1970 and 1990 (Brazhnik et al., 2017). During recent decades, the number, area and frequency of forest fires increased in Putorana Plateau (north of Central Siberia), in larch-dominated forests of Central Siberia and in Siberian forests as a whole. This increase is in line with an increase in the average annual air temperature, air temperature anomalies, droughts and the length of fire season (Ponomarev et al., 2016; Kharuk and Ponomarev, 2017; Pospelova et al., 2017). The number of forest fires and damaged areas in Gangwon Province and the Yeongdong area in the 2000s increased by factors of 1.7 and 5.6, respectively, compared with the 1990s (Bae et al., 2020). Climate change is not the sole cause of the increase in forest fire severity (Wu et al., 2014; Wu et al., 2018d). Ignition is often facilitated by lightning (Canadell et al., 2021), and over 80% of fires in Siberia are likely anthropogenic in origin (e.g., (Brazhnik et al., 2017). Gas field development and Indigenous tundra burning practices that may get out of control contribute to fire frequency in the forest–tundra of West Siberia (Adaev, 2018; Moskovchenko et al., 2020). Climate change in combination with socioeconomic changes has resulted in an increase in fire severity and area burned in South Siberia, and illegal logging increases fire danger in forest–steppe Scots pine stands (Ivanova et al., 2010; Schaphoff et al., 2016).
In East and North Asia, satellite measurements and ground-based observations in recent decades demonstrate either an increase in the length of plant growth season over sub-regions or in some territories in line with climate warming, or do not show any significant trend in other territories (high confidence). In recent decades in China, there has been an increasing trend in annual mean grassland net primary production (NPP), average leaf area index and lengthening of the local growing season (Piao et al., 2015; Zhang et al., 2017b; Xia et al., 2019). Nevertheless, phenology patterns vary across different studies, species and parts of China. In most regions of Northeast China, start date and length of land surface phenology from 2000 to 2015 had advanced by approximately 1 d yr −1, except in the needle-leaf and cropland areas (Zhang et al., 2017d). For Inner Mongolia, it has been shown that neither the start of growing season (SOS) nor the end of growing season (EOS) presented detectable progressive patterns at the regional level in 1998–2012, except for the steppe–desert (6% of the total area) (Sha et al., 2016). In the Tianshan Mountains in China, the NPP of only 2 out of 12 types of vegetation increased in spring, and the NPP of only one type increased in autumn from 2000–2003 to 2012–2016 (Hao et al., 2019). In Republic of Korea, from 1970 to 2013, the SOS has advanced by 2.7 d per decade, and the EOS has been delayed by 1.4 d per decade (Jung et al., 2015). During the past decade, leaf unfolding has accelerated at a rate of 1.37 d yr −1, and the timing of leaf fall has been delayed at a rate of 0.34 d yr −1 (Kim et al., 2019d). Cherry blossoms are predicted to flower 6.3 and 11.2 d earlier after 2090 according to scenarios RCP4.5 and RCP8.5, respectively (Bae et al., 2020). On the Tibetan Plateau, it was found that the SOS has advanced and the EOS has been delayed over the past 30–40 years (Yang et al., 2017). Using normalised difference vegetation index (NDVI) datasets and ground-based Budburst data (Wang et al., 2017c) found no consistent evidence that the SOS has been advancing or delaying over the Tibetan Plateau during the past two to three decades. The discrepancies among different studies in the trends of spring phenology over the Tibetan Plateau could be largely attributed to the use of different phenology retrieval methods. An uncertainty exists with the relationship between land-surface phenology and climate change estimated by satellite-derived NDVI because these indices are usually composite products of a number of days (e.g., 16 d) that could fail to capture more details. Besides, due to lack of in situ observations, the SOS and EOS at large areas cannot be easy defined (Zhang et al., 2017d).
In North Asia, in Central Siberia and south of West Siberia, the growth index of Siberian larch based on tree-ring width increased with the onset of warming and changed in antiphase with aridity in the 1980s (Kharuk et al., 2018). In Mongolia and Kazakhstan, the temperature increase over the previous decade promoted radial stem increment of the Siberian larch. However, the simultaneous influence of increased temperature, decreased precipitation and increased anthropogenic pressure resulted in widespread declines in forest productivity and reduced forest regeneration, and increased tree mortality (Dulamsuren et al., 2013; Lkhagvadorj et al., 2013a; Lkhagvadorj et al., 2013b; Dulamsuren et al., 2014; Khansaritoreh et al., 2017). In Eastern Taimyr, growing season, the number of flowering shoots, annual increment, success of seed ripening and vegetation biomass have increased considerably in recent decades (Pospelova et al., 2017). In Vishera Nature Reserve, northern Ural Mountains, annual temperature has increased in recent decades in parallel with a summer temperature drop and an increase in summer frost numbers. As a result, trends in vegetation change are mostly unreliable (Prokosheva, 2017).
In Asia, the date of arrival of migrant birds to nesting areas and the date of departure from winter areas are changing consistently with climate change (medium confidence). Time of arrival of the grey crow to the Lower Ob river region, northwest Siberia, shifted to earlier dates in the period 1970–2017, which is consistent with an increase in the daily average temperatures on the day of arrival (Ryzhanovskiy, 2019b). In Ilmen Nature Reserve, Urals, an earlier arrival of the majority of nesting bird species has not been observed in recent decades. This is explained by the fact that other factors, such as the weather of each spring month of particular years, population density in the previous nesting period, the seed yield of the main feeding plants and migration of wintering species from adjacent areas, determinate the long-term dynamics of bird arrival (Zakharov, 2016; Zakharov, 2018). In Yokohama, Japan, observations since 1986 have revealed that the arrival of six winter bird species came later and the departure earlier than in the past, due to warmer temperatures (Kobori et al., 2012; Cohen et al., 2018). Some papers corroborate that earlier start and later end of phenological events in Asia are associated with global warming; however, other papers do not confirm such a connection. Comparison and synthesis of results is impeded by usage of different metrics, measurement methods and models (e.g., Hao et al., 2019). Relative contribution of climatic stress and other factors to phenology and plant growth trends are poorly understood (e.g., Andreeva et al., 2019).
Across Asia, under a range of representative concentration pathways (RCPs) and other scenarios, rising temperatures are expected to contribute to a northward shift of biome boundaries and an upwards shift of mountain treeline (medium confidence). Northward shift and area change of bioclimatic zones in Siberia (Anisimov et al., 2017; Torzhkov et al., 2019) and northeast Asia (Choi et al., 2019) are projected. Projected changes in vegetation in China at the end of the 21st century reveal that the area covered by cold–dry potential vegetation decreases as the area covered by warm–humid potential vegetation increases (Zhao et al., 2017a). Forest expansion into mountain tundra of the northern Urals is expected (Sannikov et al., 2018). In Republic of Korea, projected under RCP4.5 and RCP8.5 in the 2070s, suitable area loss of six subalpine tree species, namely, Korean fir, Khingan fir, Sargent juniper, Yeddo spruce, Korean yew and Korean arborvitae, range from 17.7 ± 20.1% to 65.2 ± 34.7%, respectively (Lee et al., 2021b). Korean fir forests would be replaced by temperate forests at lower elevations, while they would continuously persist at the highest elevations on Mt. Halla, Jeju Island and Republic of Korea (Lim et al., 2018). Himalayan birch at its upper distribution boundary either is projected to move upwards (Schickhoff et al., 2015; Bobrowski et al., 2018) or considered to downslope as a response to global-change-type droughts (Liang et al., 2014). Upwards shift in elevation of bioclimatic zones, decreases in area of the highest elevation zones and large expansion of the lower tropical and sub-tropical zones can be expected by the year 2050 throughout the transboundary Kailash Sacred Landscape of China, India and Nepal, and likely within the Himalayan region more generally (Zomer et al., 2014).
In North Asia, a shift is projected in the dominant biomes from conifers to deciduous species across Russia after 20 years of altered climate conditions (Shuman et al., 2015). In South Siberia, Brazhnik and Shugart (2015) projected a shift from the boreal forest to the steppe biome. Rumiantsev et al. (2013) also project a positive northward shift of vegetation boundaries for the greater part of West Siberia in line with warming; however, no shift for the north of West Siberia and negative shift for the southern Urals and northwest Kazakhstan are projected for 2046–2065. The replacement of forest–steppe with steppe at the lower treeline in South Siberia is projected (Brazhnik and Shugart, 2015), and retreat of larch forests from the southernmost strongholds of boreal forest in eastern Kazakhstan is expected as part of a global process of forest dieback in semiarid regions (Dulamsuren et al., 2013). In North Asia, tree growth is intertwined with permafrost, snowpack, insect outbreaks, wildfires, seed dispersal and climate (e.g., Klinge et al., 2018). It is challenging to isolate the affects of individual factors, particularly since they can interact on one another in unanticipated ways because the underlying mechanisms are not well understood (Berner et al., 2013; Brazhnik and Shugart, 2015). The accuracy of treeline-shift projections is limited because projections are based on vegetation models which do not consider all the factors (Tishkov et al., 2020). The regional vegetation model structure and parameterisation can affect model performance, and the corresponding projections can differ significantly (Shuman et al., 2015).
Considerable changes in plant and animal species distribution under warming stress are expected in Asia until 2100 (high confidence). In East Asia, Cunninghamia lanceolate, a fast-growing and widely distributed coniferous timber species in China, is projected to increase distribution, to decrease the establishment probability and to reduce total NPP by the 2050s (Liu et al., 2014c). In the monsoon regions of Asia, by the end of the 21st century, NPP is projected to increase by 9–45% (Ito et al., 2016). Under climate change on the Korean Peninsula (KP), the potential habitat for Abies nephrolepis is the northern part of KP, and A. koreana will disappear from Jeju Island and shrink significantly in the KP (Yun et al., 2018), while evergreen forests will expand to the northern part of KP (Koo et al., 2018; Lim et al., 2018). It is expected that under projected warming, fig species in China will expand to higher latitudes and altitudes (Chen et al., 2018c). In Japan, under the A1B scenario, 89% of the area currently covered by the Fagus crenata-dominant forest type will be replaced by Quercus spp.-dominant forest types (Matsui et al., 2018). Current trends of climate change will reduce distribution of tall (2–2.5 m high) herb communities in Japan, and will increase suitably for them in the Russian Far East (Korznikov et al., 2019). A range expansion of Lobaria pindarensis, an endemic epiphytic lichen in the HKH region, is projected to move to the northeast and to higher altitudes in response to climate change, although the species’ low dispersal abilities and the local availability of trees as a substratum will considerably limit latitudinal and altitudinal shifts (Devkota et al., 2019).
The climatic range of Italian locust (Calliptamus italicusL.) under RCP4.5 will expand north- and east-ward to Siberia, the Russian Far East and Central Asia (Popova et al., 2016). In Krasnoyarsk Krai, Siberia, it is projected that the needle cast disease caused by fungi from the genus LophodermiumChevall. in the Scots pine nurseries would shift northward up to 2080 under A2 and B1 scenarios (Tchebakova et al., 2016). All four RCP scenarios showed north-ward expansion of vulnerable regions to pine wilt disease in China, Republic of Korea, the Russian Far East and Japan under climate conditions in 2070 (Hirata et al., 2017), and during 2026–2050 in Japan (Matsuhashi et al., 2020). It is noteworthy that disease expansion depends not only on climatic factors but also on the dispersal capacity of insect vectors, the transportation of infected logs to non-infected regions and the susceptibility of host trees (e.g., Gruffudd et al., 2016). The suitable habitat area of the snow leopard Panthera uncia is projected to increase by 20% under the IPCC Scenario A1B by 2080: for the seven northernmost snow leopard range states (Afghanistan, Tajikistan, Uzbekistan, Kyrgyzstan, Kazakhstan, Russia and Mongolia) the suitable habitat area will increase, while habitat loss is expected on the southern slope of the Himalaya and the southeast Tibetan Plateau (Farrington and Li, 2016). Climate change projected under four RCP scenarios will not affect the distribution patterns of Turkestan Rock Agama Paralaudakia lehmanni (Nikolsky 1896; Sancholi, 2018). In Iran, among 37 studied species of plants and animals, the ranges of 30 species are expected to shrink and ranges of 7 species are expected to increase between 2030 and 2099 under climate-change stress (Yousefi et al., 2019).
Future climate change would cause biodiversity and habitat loss in many parts of Asia using modelling approaches (high confidence). Warren et al. (2018) projected that extirpation risks to terrestrial taxa (plants, amphibians, reptiles, birds and mammals) from 2°C to 4.5°C global warming in 12 ‘priority places’ in Asia, under the assumption of no adaptation (i.e., dispersal) by the 2080s, is from 12.2–26.4% to 29–56% (Table 10.1; Figure 10.4). Under different scenarios, future climate change could reduce the extent of a suitable habitat for giant pandas (Fan et al., 2014), moose (Alces alces) (Huang et al., 2016), black muntjac (Muntiacus crinifrons) (Lei et al., 2016) and the Sichuan snub-nosed monkey (Rhinopithecus roxellana) (Zhang et al., 2019d) in China; the Persian leopard (Panthera pardus saxicolor) in Iran (Ashrafzadeh et al., 2019a); the Bengal tiger (Mukul et al., 2019) in India; and four tree-snail species (Amphidromus) in Thailand (Klorvuttimontara et al., 2017). However, climate change would have little impact on the habitats of the Asian elephant, but would cause extinction of the Hoolock gibbon in Bangladesh by 2070 (Alamgir et al., 2015). Climate change would increase the distribution of the Mesopotamian spiny-tailed lizard (Saara loricate) in Iran (Kafash et al., 2016). Future climate change would reduce the suitable habitat of certain protected plants (Zhang et al., 2014) including Polygala tenuifoliaWild (Lei et al., 2016); relict species in East Asia (Tang et al., 2018); tree Abies (Ran et al., 2018) in China; two threatened medicinal plants (Fritillaria cirrhosa and Lilium nepalense) in Nepal (Rana et al., 2017); a medicinal and vulnerable plant species Daphne mucronata (Abolmaali et al., 2018) and Bromus tomentellus in Iran (Sangoony et al., 2016); a valuable threatened tree species, Dysoxylum binectariferum, in Bangladesh (Sohel et al., 2016); and plant diversity in Republic of Korea (Lim et al., 2018).
Table 10.1 | Projected extirpation risks: percentage of taxa (plants, amphibians, reptiles, birds and mammals) for 2°C and 4.5°C global warming in ‘priority places’ in Asia, without adaptation by the 2080s. (From Warren et al., 2018).
Priority places | At 2°C (%) | At 4.5°C (%) |
Mekong | 26.4 | 55.2 |
Baikal | 22.8 | 49.5 |
Yangtze | 20 | 42.6 |
Coral Triangle | 19.2 | 41.8 |
Western Ghats | 18.8 | 41.67 |
New Guinea | 19.8 | 41.2 |
Atlai-Syan | 18.6 | 37 |
Sumatra | 16.8 | 37 |
Borneo | 17.6 | 36.8 |
Amur | 14.2 | 35.6 |
Eastern Himalayas | 12.2 | 29 |
Black sea | 26.2 | 56 |
Figure 10.4 | Location of ‘priority places’ in Asia. (Modified from Warren et al., 2018).
The impact of future climate change on invasive species may be species- or region specific (medium confidence). Climate change would promote invasion of a highly invasive aquatic plant Eichhornia crassipes (You et al., 2014), Ambrosia artemisiifolia (Qin et al., 2014), alligator weed (Alternanthera philoxeroides) (Wu et al., 2016), invasive alien plant Solidago canadensis (Xu et al., 2014), three invasive woody oil-plant species (Jatropha curcas, Ricinus communis and Aleurites moluccana) (Dai et al., 2018), and 90 of ~150 poisonous plant species (Zhang et al., 2017a) in China; six mostly highly invasive species (Ageratum houstonianumMill., Chromolaena odorata (L.) R.M. King & H. Rob., Hyptis suaveolens (L.) Poit., Lantana camaraL. , Mikania micranthaKunth and Parthenium hysterophorusL.) in Nepal (Shrestha et al. 2018); 11 invasive plant species in the western Himalaya (Thapa et al., 2018); alien plants in Georgia (Slodowicz et al., 2018); the invasive green anole (Anolis carolinensis) in Japan (Suzuki-Ohno et al., 2017); the Giant African Snail in India (Sarma et al., 2015); and a major insect vector (Monochamus alternatus) of the pine wilt disease (Kim et al., 2016b) and melon thrips (Thrips palmiKarny) (Park et al., 2014) in Republic of Korea. In contrast, a few studies have projected that climate change would inhibit the invasion of one exotic species (Spartina alterniflora) (Ge et al., 2015), alien invasive weeds (Wan et al., 2017), an invasive plant (Galinsoga parviflora) (Bi et al., 2019) and an invasive species (Galinsoga quadriradiata) (Yang et al., 2018b) in China; and two invasive plants (Chromolaena odorata and Tridax procumben s) in India (Panda and Behera, 2019).
Five of 15 endemic freshwater fish species in Iran will lose some parts of their current suitable range under climate change by 2070 (Yousefi et al., 2020). In line with projected large increases in mean water temperature, the strongest increase is projected in exceeded frequency and magnitude of maximum temperature tolerance values for freshwater minnow (Zacco platypus) in East Asia for 2031–2100 (Van Vliet et al., 2013). Climate change under the A1B scenario is projected to decrease diversity (–0.1%) along with increased local richness (+15%) and range size (+19%) of stream macroinvertebrates in the Changjiang River catchment, southeast China, for the period 2021–2050, while land-use change is predicted to have the strongest negative impact (Kuemmerlen et al., 2015). The Asian clam Corbicula flumineaMüller, an invasive species native to southeast China, the Republic of Korea and southeast Russia, is projected to invade Southeast Asia under all four RCP scenarios for the 2041–2060 and 2061–2080 periods (Gama et al., 2017). Projected SLR, related aquatic salinisation and alteration in fish species composition may have a negative impact on poor households in southwest coastal Bangladesh (Dasgupta et al., 2017a).
Under regional projections for North Asia, warmer climate will increase forest fire severity by the late 21st century (medium confidence). For the southern taiga in Tuva Republic, Central Siberia, in a warmer climate, both the annual area burned and fire intensity will increase by 2100. For the central taiga in the Irkutsk region, the annual area burned as well as crown fire-to-ground fire ratiowill increase by the late 21st century compared with the historical (1960–1990) estimate. This moves forest composition towards greater contribution of hardwoods (e.g., Betula spp., Populus spp.) (Brazhnik et al., 2017). This shifting was also proved by observations in northern Mongolia, where boreal forest fires likely promote the relative dominance of B. platyphylla and threaten the existence of the evergreen conifers, Picea obovata and Pinus sibirica (Otoda et al., 2013). For Tuva Republic, warming ambient temperatures increase the potential evapotranspiration demands on vegetation, but if no concurrent increase in precipitation occurs, vegetation becomes stressed and either dies from temperature-based drought stress or more easily succumbs to insects, fire, pathogens or wind throw (Brazhnik et al., 2017). Although Torzhkov et al. (2019) also projected fire risk (FR) increase in Tuva Republic, they expect FR decrease in the Irkutsk region and Yakutia under RCP8.5, and FR decrease in major parts of Central and East Siberia under RCP4.5 for 2090–2099. This discrepancy is due to differences in models, climate projections, fire severity metrics and other assumptions. According to global projections, FR will increase in Central Asia, Russia, China and India under a range of scenarios (Sun et al., 2019).
Both natural and managed ecosystems, ecosystem services and livelihoods in Asia will potentially be substantially impacted by changing climate (Wu et al., 2018d). There will be increased risk for biodiversity, particularly many endemic and threatened species of fauna and flora already under environmental pressure from land-use change and other regional and global processes (Zomer et al., 2014; Rashid et al., 2015; Choi et al., 2019). Biomes shift not only serves as a signal of climate change but also provides important information for resources management and ecotone ecosystem conservation. A widespread upwards encroachment of subalpine forests would displace regionally unique alpine tundra habitats and possibly cause the loss of alpine species (Schickhoff et al., 2015). In North Asia, emissions from fires reduce forests’ ability to regulate climate. A warmer and longer growing season will increase vulnerability to fires, although fires can be attributed both to climate warming and to other human and natural influences. Recent field-based observations revealed that the forests in South Siberia are losing their ability to regenerate after fire and other landscape disturbances under a warming climate (Brazhnik et al., 2017). Data support the hypothesis of a climate-driven increase in fire frequency in boreal forests with the possible turning of boreal forests from a carbon sink to a carbon source (Ponomarev et al., 2016; Schaphoff et al., 2016; Brazhnik et al., 2017; Ponomarev et al., 2018); however, warming resulting from forest fire is partly offset by cooling in response to increased surface albedo of burned areas in a snow-on period (Chen and Loboda, 2018; Chen et al., 2018a; Jia et al., 2019; Lasslop et al., 2019).
Modelling of the interactions between climate-induced vegetation shifts, wildfire and human activities can provide keys to how people in Asia may be able to adapt to climate change (Kicklighter et al., 2014; Tian et al., 2020). Conservation and sustainable development would benefit from being tailored and modified considering the changing climatic conditions and shifting biomes, mountain belts and species ranges (Pörtner et al., 2021). Expanding the nature reserves would help species conservation; to facilitate species movements across climatic gradients, an increase in landscape connectivity can be elaborated by setting up habitat corridors between nature reserves and along elevational and other climatic gradients (Brito-Morales et al., 2018; D’Aloia et al., 2019; United Nations Climate Change Secretariat, 2019). Assisted migration of species should be considered for isolated habitats as mountain summits or where movements are constrained by poor dispersal ability. Introducing seeds of the species to new regions will help to protect them from the extinction risk caused by climate change (Mazangi et al., 2016). In Asian boreal forests, a strategy and integrated programmes should be developed for adaptation of the forests to global climate change, including sustainable forest management, firefighting infrastructure and forest fuel management, afforestation, as well as institutional, social and other measures in line with Sustainable Development Goal (SDG) 15 ‘Life on Land’ (Isaev and Korovin, 2013; Kattsov and Semenov, 2014; Bae et al., 2020). Improvements in forest habitat quality can reduce the negative impacts of climate change on biodiversity and ecosystem services (Choi et al., 2021). Adaptation options for freshwater ecosystems in Asia include increasing connectivity in river networks, expanding protected areas, restoring hydrological processes of wetlands and rivers, creating shade to lower temperatures for vulnerable species, assisted translocation and migration of species (Hassan et al., 2020; Chapter 2). Reduction of non-climate anthropogenic impacts can enhance the adaptive capacity of ecosystems (Tchebakova et al., 2016).
Box 10.3 | Case Study on Sand and Dust Storm, Climate Change in West Asia’s Iranian Region
The West Asia region, especially the Tigris–Euphrates alluvial plain, has been recognised as one of the most important dust-source areas in the world (Cao et al., 2015). The inhabitants of each of these settlements have experienced a decline in dust storms in recent decades, since the late 1980s at Nouakchott, since 2004 at Zabol and since the late 1970s at Minqin. Iran is mostly arid or semiarid, with deserts making up at least 25 million hectares of the country (NASA, 2018). Iran is experiencing unprecedented climate-related problems such as drying of lakes and rivers, dust storms, record-breaking temperatures, droughts and floods (Vaghefi et al., 2019). There are three key factors responsible for the generation of sand and dust storms: strong wind, lack of vegetation and absence of rainfall (EcoMENA, 2020). It seems that all of this is closely related to the heating surface and the occurrence of local dry instabilities (Ghasem et al., 2012). According to EcoMENA (2020), sand and dust storms cause significant negative impacts on society, the economy and the environment at the local, regional and global levels. The seasonality of the numbers of dusty days (NDD) in Iran shows the highest frequency in summer followed by spring and autumn (Modarres and Sadeghi, 2018). In the past decade, West Asia has witnessed more frequent and intensified dust storms affecting Iran and other Persian Gulf countries (Nabavi et al., 2016). In terms of long-term frequency of dust events, observational analyses show an overall rising trend of the frequency of Iran’s dust events in recent years (Alizadeh-Choobari et al., 2016). Results show that there has been a direct relationship between dust event, drought and years of intensive drought (Dastorani and Jafari, 2019). Compared with the period 1980–2004, in the period 2025–2049, Iran is likely to experience more extended periods of extreme maximum temperatures in the southern part of the country, more extended periods of dry (for ≥120 d: precipitation <2 mm, Tmax≥30°C) as well as wet (for ≤3 d: total precipitation ≥110 mm) conditions and a higher frequency of floods (Vaghefi et al., 2019). The slope of precipitation in West Asia shows that during the period 2016–2045 in January, February, July and August, precipitation would increase and decrease in other months of the year (Ahmadi et al., 2018). Temperatures in Central Asia have risen significantly within recent decades, whereas mean precipitation remains almost unchanged (Haag et al., 2019); however, climatic trends can vary greatly between different sub-regions, across altitudinal levels and within seasons (Haag et al., 2019).
Coastal habitats of Asia are diverse, and the impacts of climate change, including rising temperatures, ocean acidification and SLR, are known to affect the services and livelihoods of the people depending on them. The risk of irreversible loss of many marine and coastal ecosystems increases with global warming, especially at 2°C or more (high confidence) (IPCC, 2018b). In the South China Sea, coral growth and sea surface temperature (SST) have shown regional long-term trends and inter-decadal variations, while coral growth is predicted to decline by the end of this century (Yan et al., 2019). Increasing human impacts have also been found to reduce coral growth (Yan et al., 2019). In the South China Sea, nearly 571 coral species have been severely impacted by global climate changes and anthropogenic activities (Huang et al., 2015a).
The 2014–2017 global-scale coral bleaching event (GCBE) resulted in very high coral mortality on many reefs, rapid deterioration of reef structures and far-reaching environmental impacts (Eakin et al., 2019). The thermally tolerant Persian Gulf corals (Coles and Riegl, 2013) are facing an increasing frequency of mass bleaching (Riegl et al., 2018) and each event leaves a substantial long-term impact on coral communities (Burt, 2014) with low capacity for recovery indicating a bleak future for Persian Gulf reefs (Burt et al., 2019).
One of the probable results of global warming is high SLR. Scientists believe that increasing GHGs (the Earth’s temperature controllers) is the cause of this global warming, and by using satellite measurements, these scientists have forecasted on average 1–2 mm for SLR (Jafari et al., 2016). The level of thermal stress (based on a degree heating month index, DHMI) at these locations during the 2015–2016 El Niño was unprecedented and stronger than previous ones (Lough et al., 2018). In the Persian Gulf, the reef-bottom temperatures in 2017 were among the hottest on record, with mean daily maxima averaging 35.9 ± 0.10°C across sites, with hourly temperatures reaching as high as 37.7°C (Riegl et al., 2018). About 94.3% of corals were bleached, and about 66% perished, in 2017 (Burt et al., 2019). In 2018 coral cover averaged just 7.5% across the southern basin of the Persian Gulf. This mass mortality did not cause dramatic shifts in community composition as earlier bleaching events had removed the most sensitive taxa. An exception was the already rare Acropora spp. which were locally extirpated in summer 2017 (Burt et al., 2019). During 2008–2011 also the coral communities of Musandam and Oman showed changes depending on the stress-tolerance levels of the species and the local environmental disturbance level (Bento et al., 2016).
The health and resilience of corals have been found to be associated with beneficial microorganisms of coral (BMC) which alter during environmental stress. Increasing seawater temperatures have been found to affect the functioning of the symbiotic algae of corals (Lough et al., 2018; Gong et al., 2019) and its bacterial consortia leading to coral bleaching and mortality (Bourne et al., 2016; Peixoto et al., 2017; Bernasconi et al., 2019; (Motone et al., 2020).
Coral reefs were found to be affected differentially during bleaching episodes, and those species which survived had more stress-tolerant symbionts and higher tolerance to thermal changes (Majumdar et al., 2018; Thinesh et al., 2019; van der Zande et al., 2020). Rare thermally tolerant algae and host species-specific algae may play important roles in coral bleaching (van der Zande et al., 2020). Along the Indian coast, in the coral reefs of Palk Bay (Bay of Bengal), varied bleaching and recovery patterns among coral genera was observed during the 2016 bleaching episode (Thinesh et al., 2019). Bleaching was high in Acropora spp. (86.36%), followed by Porites (65.45%), while moderate to no bleaching was observed in Favites Symphyllia, Favia, Platygyra and Goniastrea.
The presence of stress-tolerant symbiont Durusdinium (Clade D) during the post-bleach period indicated the high adaptive capacity of Acropora spp. in tropical waters (Thinesh et al., 2019). Also Porites spp. were found to have higher thermal thresholds and showed better resilience to bleaching than species like Fungiid spp. (Majumdar et al., 2018). In the Philippines, during the 2010 bleaching event, the size structure of the mushroom coral was found to be affected (Feliciano et al., 2018). In Indonesia, it was found that branching coral diversity may decrease relative to massive, more resilient corals (Hennige et al., 2010). This would have large-scale impacts upon reef biodiversity and ecosystem services, and reef metabolism and net reef accretion rates, since massive species are typically slow growers (Hennige et al., 2010).
Macro-tidal coral reefs are particularly sensitive to medium- to long-term changes in sea-level Andaman trenches (Simons et al., 2019). Data compiled from 11 cities throughout East and Southeast Asia, with particular focus on Singapore, Jakarta, Hong Kong and Naha (Okinawa), highlights several key characteristics of urban coral reefs, including ‘reef compression’ (a decline in bathymetric range with increasing turbidity and decreasing water clarity over time and relative to shore), dominance by domed coral growth forms and low reef complexity, variable city-specific inshore–offshore gradients, early declines in coral cover with recent fluctuating periods of acute impacts and rapid recovery, and colonisation of urban infrastructure by hard corals (Heery et al., 2018).
In Taiwan, Province of China, the calcification rate of the model reef coral Pocillopora damicornis was higher in coral reef mesocosms featuring seagrasses under ocean acidification conditions at 25°C and 28°C. The presence of seagrass in the mesocosms helped to stabilise the metabolism of the system in response to simulated climate change (Liu et al., 2020a).
An increase in host susceptibility, pathogen abundance or virulence has led to higher prevalence and severity of coral diseases and to decline and changes in coral reef community composition (Maynard et al., 2015). Relative risk has been found to be high in the province of Papua in Indonesia, the Philippines, Japan, India, northern Maldives, the Persian Gulf and the Red Sea. For the combined disease-risk metric, relative risk was considered lower for locations where anthropogenic stress was low or medium, a condition found for some locations in Thailand (Maynard et al., 2015).
Degradation and loss of coral reefs can affect about 4.5 million people in Southeast Asia and the Indian Ocean (Lam et al., 2019). In the coral reef fisheries sector, there are about 3.35 million fishers in Southeast Asia and 1.5 million fishers in the Indian Ocean (Teh et al., 2013). The economic loss under different climate-change scenarios and fishing efforts were estimated to range from 27.78 to 31.72 million USD annually in Nha rang Bay, Vietnam. A survey conducted in Taiwan, Province of China, showed that the average annual amount that people were personally willing to pay was 35.75 USD and the total amount was 0.43 billion USD. These high values indicate the need to preserve these coral reef ecosystems (Tseng et al., 2015). In Bangladesh, the coral reef of St. Martin’s Island contributes 33.6 million USD yr –1 to the local economy, but climate change, along with other anthropogenic activities, has been identified as a threat these habitats (Rani et al., 2020 a).
Mitigation of global warming has been identified to be essential to maintain healthy coral reef ecosystems in Asia (Comte and Pendleton, 2018; Heery et al., 2018; Lam et al., 2019; Yan et al., 2019). Restoration of reefs (Nanajkar et al., 2019) and building resilience through multiple mechanisms, such as innovative policy combinations, complemented by environmental technology innovations and sustained investment (Hilmi et al., 2019; McLeod et al., 2019), are suggested.
An ecosystem-based approach to managing coral reefs in the Gulf of Thailand is needed to identify appropriate marine protected area (MPA) networks and to strengthen marine and coastal resource policies in order to build coral reef resilience (Sutthacheep et al., 2013). Broadening the scope to develop novel mitigation approaches towards coral protection through the use of symbiotic bacteria and their metabolites (Motone et al., 2018; Motone et al., 2020) has been suggested. Coral culture and transplantation within the Gulf are feasible for helping maintain coral species populations and preserving genomes and adaptive capacities of Gulf corals that are endangered by future thermal-stress events (Coles and Riegl, 2013). Greater focus on understanding the flexibility and adaptability of people associated with coral reefs, especially in a time of rapid global change (Hoegh-Guldberg et al., 2019), and a well-designed research programme for developing a more targeted policy agenda (Lam et al., 2019), is also recommended. Cutting carbon emissions (Bruno and Valdivia, 2016) and limiting warming to below 1.5°C is essential to preserving coral reefs worldwide and protecting millions of people (Frieler et al., 2013; Hoegh-Guldberg et al., 2017). Many visitors to coral reefs have high environmental awareness, and reef visitation can both help to fund and encourage coral reef conservation (Spalding et al., 2017).
The largest mangrove forests are in Asia contributing to about 42% of the world’s mangroves. This includes Sundarbans, the world’s largest remaining contiguous mangrove forest (Dasgupta et al., 2020). Mangrove ecosystems are rich in biodiversity. The ecosystems are supported and maintained by both flora and a large array of living things, which include mammals, birds, fish, crustaceans, shrimps, insects and microbes 3 . Contemporary rates of mangrove deforestation are lower than in the late 20th century (Gandhi and Jones, 2019; Friess et al., 2019); however, some areas in Asia continue the trend. Myanmar is the primary mangrove-loss hotspot in Asia, exhibiting 35% loss from 1975 to 2005 and 28% from 2000 to 2014. Rates of loss in Myanmar were four times the global average from 2000 to 2012. The Philippines is additionally identified as a loss hotspot, with secondary hotspots including Malaysia, Cambodia and Indonesia (Gandhi and Jones, 2019).
Mangrove deforestation is expected to increase as many tropical nations utilise mangrove areas for economic security. Increased river damming would reduce fluvial sediment sources to the coast making mangroves more vulnerable to SLR, and uncertain climate with extreme oscillations can create unstable conditions for survival and propagation of mangrove (Friess et al., 2019).
Valuation of ecosystem services of mangroves have indicated that they prevent more than 1.7 billion USD in damages for extreme events (i.e., one event in 50 years) in the Philippines (Menéndez et al., 2018). They reduce flooding to 613,500 people yr –1, 23% of whom live below the poverty line and avert damages up to 1 billion USD yr –1 in residential and industrial property. Mangroves have also become a very popular source of livelihood in Asia through tourism (Dehghani et al., 2010; Kuenzer and Tuan, 2013; Spalding and Parret, 2019; Dasgupta et al., 2020) and they also support fisheries (Hutchison et al., 2014).
Mangroves, tidal marshes and seagrass meadows (collectively called coastal blue carbon ecosystems) have sequestered carbon dioxide from the atmosphere continuously over thousands of years, building stocks of carbon in biomass and organic rich soils. Carbon dynamics in mangrove-converted aquaculture in Indonesia indicate that the mean ecosystem carbon stocks in shrimp ponds are less than half of the relatively intact mangroves (Arifanti et al., 2019). Conversion of mangroves into shrimp ponds in the Mahakam Delta have resulted in a carbon loss equivalent to 226 years of soil carbon accumulation in natural mangroves. In the Philippines, abandoned fishpond reversion to former mangrove has been found to be favourable for enhancing climate change mitigation and adaptation (Duncan et al., 2016). Integrated mangrove-shrimp farming, with deforested areas not exceeding 50% of the total farm area, has been suggested to support both carbon sequestration as well as livelihood (Ahmed et al., 2018).
Globally, the extent of the blue carbon ecosystem has been estimated at 120,380 km 2, with the highest spread by mangroves at 114,669 km 2 (95.3%), followed by seagrass meadows at 2,201 km 2 (1.8%) and salt marshes at 3510 km 2 (2.9%) (Himes-Cornell et al., 2018). In Asia, the total extent of these three ecosystems is 33,224 km 2, forming 27.6% of the global total with the highest spread of mangrove at 32,767 km 2, which forms 28.6% of the global mangrove coverage. The area of seagrass meadows spread in Asia has been estimated as 236 km 2 and salt marsh 220 km 2,which forms 10.8 and 6.03% of the respective ecosystems globally (Himes-Cornell et al., 2018). Found at the land–sea interface, seagrasses provide varied services apart from acting as ecosystem engineers providing shelter and habitat for several marine fauna which are fished in several Asian countries (Jeyabaskaran et al., 2018; Nordlund et al., 2018; Unsworth et al., 2019b) thereby providing livelihood to millions across the continent (UNEP, 2020).
The seagrass meadows are also good sinks of carbon (Fourqurean et al., 2012) capable of storing 19.9 petagrams (pg) of organic carbon, but with very high regional and site- and species variability (Ganguly et al., 2017; Stankovic et al., 2018; Gallagher et al., 2019; Ricart et al., 2020). As highly efficient carbon sinks, they store up to 18% of the world’s oceanic carbon, and they also reduce the impacts of ocean acidification (UNEP, 2020).
The deterioration of this ecosystem is fast, 7% yr –1 since 1990 (Waycott et al., 2009), which has led to development of restoration protocols across Asia (Paling, 2009; van Katwijk et al., 2016). In Vietnam, the loss of seagrass has been estimated as above 50% and in some regions complete loss has been observed (Van Luong et al., 2012). The seagrass meadows of Indonesia are fast deteriorating, and the need for increased local autonomy for the management of marine resources and restoration has been highlighted (Unsworth et al., 2018). Development of science-based policies for conservation, including participatory methods (Fortes, 2018; Ramesh et al., 2019; Unsworth et al., 2019a) and large-scale planting (van Katwijk et al., 2016), has been recommended to preserve the ecosystem services of these habitats.
Globally, the diversity of the plankton community has been predicted to be affected by warming and related changes (Ibarbalz et al., 2019), and these changes are expected in Asia also. Combined effects of high temperature, ocean acidification and high light exposure would affect important phytoplankton species in the SCS, Thalassiosira pseudonana (Yuan et al., 2018) and Thalassiosira weissflogii (Gao et al., 2018b). Also in the SCS the phytoplankton-assemblage responses to rising temperatures and CO2 levels were found to differ between coastal and offshore waters and the predicted increases in temperature and pCO2 may not boost surface-phytoplankton primary productivity (Zhang et al., 2018).
Ocean warming and acidification can affect the functioning and ecological services of sedentary molluscs like the bivalves (Guo et al., 2016; Zhao et al., 2017b; Cao et al., 2018; Zhang et al., 2019c; Liu et al., 2020b) and gastropods (Leung et al., 2020), and also sea urchins (Zhan et al., 2020). The oyster Crassostrea gigas becomes more vulnerable to disease when exposed to acidification conditions and pathogen challenge indicating incapability for supporting long-term viability of the population (Cao et al., 2018). More tolerance and benefits to rising pCO2 was observed in clam species like Paphia undulate which has been attributed to adaptation to its acidified sediment habitat (Guo et al., 2016). Warming boosted the energy budget of marine calcifiers like the gastropod Austrocochlea concamerata, by faster shell growth and greater shell strength, making them more mechanically resilient while acidification negatively affected shell building thereby impacting the physiological adaptability (Leung et al., 2020). It is expected that there will be transgenerational acclimation to changes in ocean acidification in marine invertebrates (Lee et al., 2020b).
Assessment of the potential impacts and the vulnerability in marine biodiversity in the Persian Gulf under climate change has suggested a reduction of up to 35% of initial species richness and habitat loss for hawksbill turtles in the southern and southwest parts of the Persian Gulf (Wabnitz et al., 2018).
Seaweeds are an important biotic resource capable of capturing carbon and used widely as food, medicine and as raw material for industrial purposes. Warming and altered pH can affect seaweeds in different ways (Gao et al., 2016; Gao et al., 2017; Gao et al., 2018a; Wu et al., 2019b). Outbreak of intense blooms of species like Ulva rigida (Gao et al., 2017) and Ulva prolifera (Zhang et al., 2019 f) have increased due to varied factors including climate change. These blooms have created huge economic losses in the Yellow Sea affecting local mariculture, tourism and the functioning of the coastal and marine ecosystems (Zhang et al., 2019 f). Increased temperature was found to enhance the dark respiration and light compensation point of Ulva conglobate, which thrives in the mid-intertidal to upper subtidal zones, while the altered pH showed a limited effect (Li et al., 2020). Elevated temperature significantly enhanced growth, photosynthetic performances and carbon-use efficiency of Sargassum horneri in both elevated and ambient CO2 levels suggesting that the present greenhouse effect would benefit the golden tide blooming macroalgae Sargassum horneri, which might enhance both the frequency and scale of golden tide (Wu et al., 2019b).
The vulnerabilities to disaster in coastal regions with high population densities are reported in several studies (Sajjad et al., 2018) that have assessed the vulnerabilities of coastal communities along the Chinese coast and shown that roughly 25% of the coastline, and more than 5 million residents, are in highly vulnerable coastal areas of mainland China, and these numbers are expected to double by 2100. Husnayaen et al. (2018) assessed the Semarang coast in Indonesia and showed that 20% of the total coastline (48.7 km) is very highly vulnerable. Mangroves continue to face threats due to pollution, conversion for aquaculture, agriculture, apart from climate-based threats like SLR and sea erosion (Richards and Friess, 2016; Romañach et al., 2018; Wang et al., 2018b; Friess et al., 2019). Hypersalinity, storm effects on sediment deposition, fishery development and land erosion are responsible for most of the Sunderban mangrove degradations leading to loss of livelihood (Uddin, 2014; Paul, 2017). In the Sunderbans of Asia, climate change is expected to increase river salinisation, which in turn could significantly negatively impact the valued timber species, Heritiera fomes (Dasgupta et al., 2017b). Augmented potential for honey production is also predicted, which could increase the conflict between humans and wildlife (Dasgupta et al., 2017b).
Destruction by natural hazards was found to remove the above-ground C pool, but the sediment C pool was found to be maintained (Chen et al., 2018b). In the Andaman and Nicobar Islands, the 2004 Indian Ocean tsunami severely impacted mangrove habitats at the Nicobar Islands (Nehru and Balasubramanian, 2018), although new inter-tidal habitats suitable for mangrove colonisation did develop. Mangrove species with a wide distribution and larger propagules showed high colonisation potential in the new habitats compared with other species (Nehru and Balasubramanian, 2018). Mangrove sites in Asia are predominantly minerogenic, so continued sediment supply is essential for the long-term resilience of Asia’s mangroves to SLR (Lovelock et al., 2015; Balke and Friess, 2016; Ward et al., 2016a; Ward et al., 2016b).
Primary production in the western Indian Ocean showed a reduction by 20% during the past six decades, attributed to rapid warming and ocean stratification which restricted nutrient mixing (Roxy et al., 2016). Variation in secondary-production zooplankton densities and biomass in the East Asian Marginal Seas affected the recruitment of fishes due to mismatch in spawning period and larval-feed availability during the last three climate regime shifts (CRS) in the mid-1970s, late 1980s and late 1990s, which were characterised by the North Pacific index and the Pacific Decadal Oscillation index (Kun Jung et al., 2017). In the western North Pacific, climate change has affected recruitment and the population dynamics of pelagic fishes, such as sardine and anchovy (Nakayama et al., 2018), and also shifts in the spawning ground and extension of the spawning period of the chub mackerel Scomber japonicas (Kanamori et al., 2019).
Varied responses to CRS in the China seas have been observed for small pelagic fishes (Ma et al., 2019) and cephalopods (Ichii et al., 2017). The winter and summer SSTs have shown evidence of decadal variability with abrupt changes from cold to warm in substantial association with climate indices to which coastal cephalopods in the China seas respond differentially, with some benefiting from warmer environments while others respond negatively (Pang et al., 2018). In the western and eastern North Pacific marine ecosystem, it is indicated that groundfish may suffer more than pelagic fish (Yati et al., 2020). Habitat Suitability index models using SST, chlorophyll-a, sea surface height anomaly (SSHA) and sea surface salinity (SSS), as well as fishing effort, strongly indicate that Neon flying squid is affected by interannual environmental variations and undertakes short-term migrations to suitable habitat, affecting the fisheries (Yu et al., 2015). The 2015–2016 El Niño was found to impact coral reefs of shallower regions (depth of 5–15 m) in South Andaman, India, more than those beyond 20 m (Majumdar et al., 2018). On the southeast coast of India, with bleaching largely mediated by the SST anomaly and during the recovery period, macroalgae outgrowth has been observed (2.75%) indicating impacts on the benthic community (Ranith and Kripa, 2019). In the South China Sea, the increase in SST was found to be higher than predicted in recent decades, while the pH decreased at a rate of 0.012–0.014 yr –1, more than the predicted level, due to high microbial respiratory processes releasing CO2 (Yuan et al., 2019). Simulation experiments have shown differential adaptation capacity of common species (Zheng, 2019; Yuan et al., 2019).
The UN’s (2019) report on climate action and support trends highlights that the impacts of climate change on coastal ecosystems are mainly increased risks due to flooding, inundation due to extreme events, coastal erosions, ecosystem processes and, in the case of fisheries, variations in population or stock structures due to ocean circulation pattern, habitat loss degradation and ocean acidification. Analysis of data on the occurrence of varied natural hazards from 1900 to 2019 has shown that tropical cyclones, riverine floods and droughts have increased significantly, and the impacts of these events on coastal communities are also severe and destructive. The UN’s average score for SDG Goal 14 (Life Under Water) for Asia was estimated as 46 among the scores of 40 nations, and the Ocean Health Biodiversity index was comparatively high (average 87.9); however, the indices show that more region-specific action plans are required to achieve the UN 2030 goal for Life Under Water.
Apart from the human impacts, the ecology and resource abundance of coastal waters have been found to be impacted by extreme events. During tropical cyclones ecological variations, like lowering of SST, an increase in chlorophyll-a and a decrease in oxygen (Chacko, 2019; Girishkumar et al., 2019) have been observed. Global analyses of such events have indicated that they may have an impact on the fishery directly by creating unfavourable ecological conditions and destruction of critical habitats indirectly by affecting the eggs and larvae as well as subsequent fishery recruitment (McKinnon et al., 2003; Bailey and Secor, 2016). In the South China Sea in July 2000, during a 3-day cyclone period, an estimated thirtyfold increase in surface chlorophyll-a concentration was observed (Lin et al., 2003). The estimated carbon fixation resulting from this event alone is 0.8 Mt, or 2–4% of the SCS’s annual new production (Lin et al., 2003). Since an average of 14 cyclones pass over this region annually, the contribution of cyclones to the annual new production has been estimated to be as high as 20–30% (Lin et al., 2003).
Water pollution and climate stressors have been considered major challenges to ecosystem sustainability, and now it has been shown that the combined effect these two stressors would be more damaging (Buchanan et al., 2019). For seagrass beds the pollution stress was found to increase by 2.6% (from 39.7 to 42.3%) when climate factors were added. Assuming the pollution levels remain at the 2014 levels, different scenarios including RCP2.6 and RCP8.5 were worked out for the Bohai Sea, and the results indicated amplification of the impacts on the ecosystem. Pollutants like petroleum hydrocarbons, dissolved inorganic nitrogen and soluble reactive phosphorus were the major pollution stressors (Lu et al., 2018). In the future, policies that focus strictly on pollution control should be changed and take into account the interactive effects of climate change for better forecast and management of potential ecological risks (Lu et al., 2018).
Projected changes in catch potential (in percent) by 2050 and 2100 relative to 2000 under RCP2.6 and RCP8.5, based on outputs from the dynamic bioclimate envelop model and the dynamic size-based food-web models, indicate that the marine and coastal resources of most Asian countries will be impacted with varying intensity (FAO, 2018b).
Better management of resources through projections of resource distribution, abundance and catch is required; however, lack of data (e.g., oceanographic surveys) and scientific knowledge is a constraint to this aim (Maung Saw Htoo et al., 2017). Effective forecasts of areas of resource abundance based on habitat preference have to be worked out for Asian regions.
Modelling and assessment of the vulnerability and habitat suitability of the Persian Gulf for 55 species to climate change indicated that there is a high rate of risk of local extinction in the southwest part of the Persian Gulf, off the coast of Saudi Arabia, Qatar and the United Arab Emirates (UAE). Likelihood of reduced catch was observed, and Bahrain and Iran were found to be more vulnerable to climate change (Wabnitz et al., 2018). Projected changes in fish catches can impact the supply of fish available for local consumption (i.e., food security) and exports (i.e., income generation) (Wabnitz et al., 2018). As per (UNESCAP, 2018a), over 40% of coral reefs and 60% of coastal mangroves in the Asia-Pacific region have already been lost, and approximately 80% of the region’s coral reefs are currently at risk.
Regionally, the escalation in thermal stress estimated for the different global warming scenarios is greatest for Southeast Asia and least for the Pacific Ocean (Lough et al., 2018). For the 100 reef locations examined here and given current rates of warming, the 1.5°C global warming target represents twice the thermal stress they experienced in 2016 (Lough et al., 2018).
In the Southeast Asia region threats from both warming and acidification has indicated that by 2030, 99% of reefs will be affected, and by 2050, 95% are expected to be in the highest levels of the ‘threatened’ category (Burke et al., 2011), similar to global corals (Frieler et al., 2013; Bruno and Valdivia, 2016). Modelling results indicate that even under RCP scenarios, the functional traits of coral reefs can be affected (van der Zande et al., 2020) and coral communities will mainly consist of small numbers of temperature-tolerant and fast-growing species (Kubicek et al., 2019). Increases in temperature (+3°C) and pCO2 (+400 matm) projected for this century can reduce the sperm availability for fertilisation, which along with adult population decline either due to climate change or anthropogenic impacts (Hughes et al., 2017) can affect coral reproductive success thereby reducing the recovery of populations and their adaptation potential (Albright and Mason, 2013; Hughes et al., 2018; Jamodiong et al., 2018). In the southern Persian Gulf, increased disturbance frequency and severity has caused progressive reduction in coral size, cover and population fecundity (Riegl et al., 2018), and this can lead to functional extinction. Connectivity required to avoid extinctions has increased exponentially with disturbance frequency and correlation of disturbances across the metapopulation. In the Philippines experiments have also proved that scleractinian corals, such as A. tenuis, A. millepora and F. colemani, which spawn their gametes directly into the water column, may experience limitations from sperm dilution and delays in initial sperm–egg encounters that can impact successful fertilisation (de la Cruz and Harrison, 2020).
Apart from these threats, natural hazards have also been found to affect coral reefs of Asia. The extensive and diverse coral reefs of Muscat, Oman, in the northeast Arabian Peninsula were found to have long-term effects from Cyclone Gonu, which struck the Oman coast in June 2007, more than coastal development (Coles et al., 2015).
Sandy beaches are subject to highly dynamic hydrological and geomorphological processes, giving them more natural adaptive capacity to climate hazards (Bindoff et al., 2019). Progress is being made towards models that can reliably project beach erosion under future scenarios despite the presence of multiple confounding drivers in the coastal zone (Chapter 3). Assuming minimal human intervention and projected impacts of SLR by 2100 under RCP8.5-like scenarios, 57–72% of Thai beaches (Ritphring, 2018), at least 50% loss of area on around a third of Japanese beaches (Mori, 2018) will disappear.
Marine heatwaves (MHWs) in Asia have been making changes to the structure and functioning of coastal and marine ecosystems (Kim and Han, 2017; Oliver et al., 2017; Frölicher and Laufkötter, 2018; Oliver et al., 2019; Smale et al., 2019), affecting resources like copepods (Doan et al., 2019) and coral reefs (Zhang et al., 2017c). Coral reefs of the southeast Indian Ocean have been affected by MHWs (Zhang et al., 2017c).
Simulation of RCP scenarios have shown that continued warming can drive a poleward shift in distribution of the seaweed Ecklonia cava of Japan, and under the lowest-emissions scenario (RCP2.6) most populations may not be impacted, but under the highest-emissions scenario (RCP8.5) the existing habitat may become unsuitable and it can also increase predation by herbivorous fishes (Takao et al., 2015).
The UN (2019) has identified establishment of protected areas, restoring ecosystems like mangroves and coral reefs, integrating coastal-zone management practices, sand banks and structural technologies, and implementing local monitoring networks for increasing adaptive capacity and protecting the biodiversity of the coastal ecosystem. In Asia, management of marine sites by earmarking protected areas (SDG 14) has been found to be low with only 27% of areas being protected. In India, detailed CCA guidelines for coastal protection and management has been prepared considering various environmental and social aspects (Black et al., 2017). The Ocean Health index for clean waters was also low (54.6), and the threat to the ecosystem due to the combined effects of pollution and climate change was high. Table 10.2 shows the ocean and MPAs.
Table 10.2 | Status of ocean health and mean of marine protected areas (MPA)a
Ocean Health index: Clean waters (0–100) | Fish stocks overexploited or collapsed (%) | Ocean Health index: Fisheries (0–100) | Fish caught by trawling (%) | Ocean Health index: Biodiversity (0–100) | Mean MPA (%) | |
Eastern Asia | 54.0 | 29.1 | 49.5 | 39.8 | 89.6 | 32.5 |
Southeast Asia | 54.1 | 28.5 | 54.9 | 34.7 | 84.6 | 25.0 |
Western Asia | 54.3 | 28.3 | 46.2 | 20.4 | 89.4 | 18.3 |
Southern Asia | 50.3 | 17.4 | 51.0 | 15.1 | 88.3 | 41.2 |
Northern Asia | 91.6 | 55.4 | 57.6 | 60.0 | 93.4 | 30.0 |
Asia (whole) | 54.6 | 26.9 | 50.3 | 27.3 | 87.9 | 27.0 |
(a) Data are from Sachs et al. (2018).
Conservation and restoration of mangroves were found to be effective tools for enhancing ecosystem carbon storage and an important part of Reducing Emissions from Deforestation and forest Degradation plus (REDD+) schemes and climate-change mitigation (Ahmed and Glaser, 2016). In East Asia, restoration success has been attributed to choosing the right geomorphological locations (Van Cuong et al., 2015; Balke and Friess, 2016) and co-management models (Johnson and Iizuka, 2016; Veettil et al., 2019).
In South Asia, restoration programmes have been largely successful (Jayanthi et al., 2018) but in some regions partly a failure due to inappropriate site selection, poor post-planting care and other issues (Kodikara et al., 2017). Using remote sensing it has been observed that there are high recovery rates of mangroves in a relatively short period (1.5 years) after a powerful typhoon, indicating that natural recovery and regeneration would be a more economically and ecologically viable strategy. Better mangrove management through mapping is suggested (Castillo et al., 2018; Gandhi and Jones, 2019). Statistical tools developed for modelling biomass and timber volume (Phan et al., 2019), and allometric models to estimate above-ground biomass and carbon stocks (Vinh et al., 2019), will be useful in estimating stocks in mangroves. Future mangrove loss may be offset by increasing national and international conservation initiatives that incorporate mangroves, such as the SDGs, Blue Carbon, and Payments for Ecosystem Services (Friess et al., 2019). Since seagrass meadows and marine macroalgae are important habitats capable of combating impacts of climate change, the need for a global networking system with participation of stakeholders has been suggested (Duffy et al., 2019).
In Asia, freshwater resources, an important component of ecosystem services, are widely used for agriculture, domestic, irrigation, navigation, energy and industry. Freshwater availability is changing at the global scale because of unsustainable use of surface water and groundwater, pollution and other environmental changes. These changes in space and time, directly or indirectly, affect water-use sectors and services (Wheater and Gober, 2015; Rodell et al., 2018). About 82% of the global population served by freshwater provisions from upstream areas are exposed to high threat (Green et al., 2015). Given that some of the fastest-growing economies in the world are in Asia, and the geographies of development are highly uneven, both CIDs and non-climate drivers, such as socioeconomic changes, have contributed to water stress conditions in both water supply and demand in diverse sub-regions of Asia. In the case of Asia, therefore, the entanglement between the non-climate drivers and CIDs makes it difficult to attribute environmental changes—both present and projected—neatly and exclusively to CIDs.
Immerzeel et al. (2020) have ranked all mountain-dependent water towers according to their water-supplying role and the downstream dependence of ecosystems, societies and economies. The resulting Global Water Tower index indicates that the upper Indus basin is both the most important and the most vulnerable water tower unit (WTU) in the world. A WTU is defined as ‘the intersection between major river basins and a topographic mountain classification based on elevation and surface roughness’. Whereas all important transboundary WTUs in Asia remain highly vulnerable, it is the Indus WTU (inhabited by approximately 235 million people in the basin in 2016 (which is projected to increase by 50% by the middle of 21st century) where the average annual temperature is projected to increase by 1.9°C between 2000 and 2050, with wide-ranging consequences and trans-sectoral spillovers. The Indus WTU faces a deep risk produced by a combination of factors including water stress, ineffective governance, hydropolitical tensions, population growth and density, urbanisation and social transformations, with a significant bearing on SDG 6 on water, SDG 2 on food and SDG 7 on energy.
Across Asia and its various sub-regions, the key drivers behind an increasingly inadequate supply of freshwater resources, affecting the livelihood security of millions, are varied, complex and intersect with multiple social, cultural, economic and environmental stressors (Luo et al., 2017; Tucker et al., 2015; Kongsager et al., 2016). Water stress has been defined as the situation ‘when the demand for water exceeds its supply, during a certain period of time, or when poor quality restricts its use’(Felberg et al., 1999; see also Figure 4.32 in Lee et al., 2021a).
Freshwater resources in Asia, which include both surface water and groundwater, are considerably strained, and changing climate is likely to act as a major stress multiplier (Dasgupta et al., 2015 ; Fant et al., 2016; Gao et al., 2018c; Mack, 2018). In Southern and Eastern Asia (SEA) nearly 200 million people are at risk of serious water-stressed conditions. Effective mitigation might reduce the additional population under threat by 30% (60 million people), but still there is a 50% chance that 100 million people across SEA might face a 50% increase in water stress and a 10% chance that water stress will almost double in the absence of wide-ranging, multi-scalar adaptive measures (Gao et al., 2018c). With Millennium Development Goal 7c, which aimed to halve the population that had no sustainable access to water and basic sanitation before 2015, not having been fully realised, and Sustainable Development Goal 6 on water and sanitation not having been effectively operationalised, the water stress is likely to increase by the end of 2030 (Weststrate et al., 2019).
In Asia and elsewhere the interplay between the challenge of sustainability and climate change poses major policy challenges (von Stechow et al., 2016). The pursuit of SDG 6—protection and restoration of water-related ecosystems, universal and equitable access to safe and affordable drinking water for all, improvement in water quality by reducing pollution, elimination of dumping and significant reduction in release of hazardous chemicals and materials, and treatment of waste water through recycling and safe reuse globally—could be directly or indirectly challenged and undermined by climate change (Parkinson et al., 2019). Dissolved organic materials from sewage can enhance CO2 emissions, especially in rapidly urbanising river systems which receive untreated waste water and/or sewage across developing countries (Kim et al., 2019b). Conversely, policy interventions aimed at significant augmentation in water-use efficiency across all sectors, ensuring sustainable withdrawals and supply of freshwater to address water scarcity and a significant reduction in the number of victims of water scarcity, especially the poor and marginalised, could mitigate vulnerabilities caused by climate change. More interdisciplinary research is needed on highly precarious future pathways and the intersection between CIDs and non-climate drivers in order to anticipate and mitigate diverging and uncertain outcomes.
According to a quantitative scenario assessment for future water supply and demand in Asia to 2050, based on global climate change and socioeconomic scenarios (Satoh et al., 2017), water demand in sectors such as irrigation, industry and households will increase by 30–40% around 2050 in comparison with 2010. Water stress is likely to be more pronounced in Pakistan, and northern parts of India and China. By mid-21st Century, the international transboundary river basins of Amu Darya, Indus, Ganges could face severe water scarcity challenges due to climatic variability and changes acting as stress multipliers (high confidence). Within a country as well, the water scarcity could be exacerbated, such as in India and China, due to various drivers like population increase and climate change. Research on the differentiated impacts of climate change on freshwater sources across the Asian sub-regions remains inconclusive and requires assessment at the sub-regional scale (IPCC, 2014b; Wester et al., 2019).
The climate-change impact on different parts of freshwater ecosystems (Section 10.4.2) has affected water supply in various sub-regions of Asia. While headwater zones are susceptible to change in snow cover, permafrost and glaciers, the downstream plain areas of these river systems are vulnerable to the increasing high demand of freshwater which will affect water availability in space and time. The observed impact of climate change has also been seen in direct physical losses such as precipitation (Mekong Delta), floods (Vietnam) and saltwater intrusion leading to low agricultural productivity (Mora et al., 2018; Almaden et al., 2019a; Pervin et al., 2020).
The HKH region extends 3,500 km from Afghanistan in the west to Myanmar in the east. It is a source of major river systems originating in Asia, supporting livelihoods, energy, agriculture and the ecosystem for 240 million people in the mountains and hills and 1.65 billion people in the plains (Sharma et al., 2019). The HKH region stores about half of the ice mass in HMA, provisioning freshwater to almost 869 million people in the Indus, Tarim, Ganges and Brahmaputra river basins. While the warming climate increases the melt-water runoff enhancing water supply, it is indeed at the cost of glacier-mass reduction that would eventually reduce melt water and impact the people’s livelihood downstream in the future (Nie et al., 2021). The melt runoff from the region plays an important role in downstream agriculture such as in the case of Indus where two-thirds of total irrigation withdrawal is from melt runoff in the pre-monsoon season (Biemans et al., 2019). Changes in cryosphere and other environmental changes have already impacted people living in high-mountain areas and are likely to introduce new challenges for water, energy and food security in the future (Borodavko et al., 2018; Adler et al., 2019; Bolch, 2019; Hoelzle et al., 2019; Rasul and Molden, 2019; Shen et al., 2020).
With climate-change impacts resulting in the shrinking and melting of snow, ice, glacier and permafrost, and correspondingly causing an increase in melt water, the incidences of flash floods, debris flow, landslides, snow avalanches, livestock diseases and other disasters in the HKH region have become more frequent and intense. Some of the key factors that get in the way of assigning confidence levels to climate-change impacts include lack of sufficient observed data on factors such as river discharges, precipitation and glacier melt (You et al., 2017). Climate-change impacts cryospheric water sources in the Hindu Kush, Karakoram and Himalayan ranges which, in turn, carry consequences for the Indus, Ganges and Brahmaputra basins.
The combined impacts of climate change and non-climate drivers on hydrological processes and water resources in transboundary rivers in diverse regions of Asia were well noted in AR5. In Central Asia, withdrawal is approximately equal to water availability, with Turkmenistan and Uzbekistan as the most water-stressed countries in the region (Karthe et al., 2017; Russell, 2018). A study on water availability in mainland South Asia has pointed in the direction of decreasing precipitation trends in recent years, which have also contributed to the increasing incidence and severity of droughts (Liu et al., 2018b). There are reports of increase in occurrence and severity of different forms of droughts in the Koshi River basin (Central Himalaya) (Wu et al., 2019a; Hamal et al., 2020; Dahal et al., 2021; Nepal et al., 2021). Figure 10.5 shows the water stress in the HKH region. The water stress is relatively higher in the western region compared with the central and eastern regions.
Figure 10.5 | Water stress in the Hindu Kush Himalaya (HKH) region according to Wester et al. (2019) and Hu and Tan (2018).
Climate change is also having an impact on stream flows. The changes in snowmelt water can explain 19% of the variations in rivers of arid regions like Xinjiang, China (Bai et al., 2018) (medium confidence), and the 10.6% of the runoff of the upper Brahmaputra River was contributed by snow during 2003–2014 (Chen et al., 2017c) (medium confidence). A recent study (Chen et al., 2018 f) has shown that with the average temperature after 1998 being 1.0°C higher than that during 1960–1998 in the Tienshan Mountains, the process of glacier shrinkage and decreases in snow cover are causing earlier peak runoff and aggravated extreme hydrological events, affecting regional water availability and adding to the future water crisis in Central Asia. The magnitude and frequency of flooding have increased across the Himalayan region, such as in the Tarim basin in China (Zhang et al., 2016c) and the higher Indus, Ganges and Brahmaputra, in the past six decades (Elalem and Pal, 2015). The latter also reported the highest number of flood disasters and greater spatial coverage in recent decades as compared with previous decades. In the Middle Yellow River basin, which has become much warmer and drier, climate variability accounts for 75.8% of streamflow decrease during 1980–2000, whereas during 2001–2016, change in land use and cover was the main factor in streamflow decrease, accounting for 75.5% of the decline (Bao et al., 2019). The changes in hydrological regime and extreme floods cause changes in river morphology and the river channel system which impact water availability.
In China, a quantitative assessment based on a multi-model dataset (six global hydrological models driven by three observation-based global forcings) during 1971–2010 suggested that climate variability dominated the changes in streamflow in more the 80% of river segments, while direct human impact dominated changes mostly in northern China (Liu et al., 2019b). In the Lancang-Mekong River basin, climate variability would have contributed 45% more flood occurrences in the middle of the basin, while reservoir operation reduced it by 36% during 2008–2016 as compared with 1985–2007 (Yun et al., 2020).
In western China, the total annual snow mass declines at a rate of 3.3 × 109 pg per decade (p< 0.05), which accounts for approximately 0.46% of the mean of annual snow mass (7.2 × 1011 pg). The loss could be valued in terms of replacement cost at 0.1 billion CN¥ (at the present value) every year (1 USD = 7 CN¥) compounded over the past 40 years (Wu et al., 2021). In the Mekong River Delta in Vietnam, climate-change impacts include a 30% annual increase in rainfall, shifting rainfall patterns, an average temperature increase of 0.5°C over the past 30 years and an average SLR of 3 mm yr –1 over the past three decades, resulting in a greater flooding threat (Wang et al., 2021a).
A recent study (Wang et al., 2021b) has shown that during 1936–2019, due largely to intensified precipitation induced by a warming climate, the streamflow of the Ob, Yenisei and Lena rivers has increased by ∼7.7, 7.4 and 22.0%, respectively. While rising temperatures can reduce streamflow via evapotranspiration, it can enhance groundwater discharge to rivers due to permafrost thawing. In permafrost-developed basins, the thawing permafrost will continue to result in increased streamflow. However, with further permafrost degradation in the future, the positive effect of permafrost thaw on streamflow would probably be offset by the negative effect of the increase in basin evapotranspiration. This could result in a situation where runoff reaches threshold level and then declines. This is clearly marked in the Ob River basin, which is characterised by the highest precipitation, whereas in the case of the Yenisei and Lena rivers, further research is needed.
The HKH region is susceptible to floods and related hazards caused by a cloud burst and other landscape-based processes such as glacial lake outburst floods, which can seriously damage property, lives and infrastructure (Shrestha et al., 2010). The likely increased frequency of hazards caused by abnormal glacier changes, such as the glacier collapses happened on two glaciers in western Tibetan Plateau in 2016 (Kääb et al., 2018), and also surges which were frequently found in this vast region (e.g. Bhambri et al., 2017; Mukherjee et al., 2017; Ding et al., 2018), threatening the security of the local and down streaming societies (high confidence).The total amount and area of glacier lakes increased during last decade (Zhang et al., 2015; Chen et al., 2017c) (high confidence). Himalayan rivers are frequently hit by catastrophic floods caused by the failure of glacial lakes (Cook et al., 2018; Ahluwalia et al., 2016). In Kedarnath, India (western Himalaya), a flash flood was triggered by glacier lake outburst flood (GLOF) released from the Chorabari glacial lake in June 2013 which caused extensive flooding, erosion of riverbanks and damage to downstream villages and towns, as well as the loss of several thousand lives (Rafiq et al., 2019; Das et al., 2015). Nepal has experienced 24 GLOF events which have caused considerable loss of life and damage to property and infrastructure (Icimod, 2011). There is high confidence that current glacier shrinkages have caused more glacial lakes to form in most mountainous regions, including HMA, but there is limited evidence that the frequency of GLOF has changed (Hock et al., 2019). Veh et al. (2018) reported no clear trend of increasing GLOF events in the Himalayan region, although the southern Himalaya was identified as a hotspot region compared with the western Himalaya. Research has shown a decrease in glacier area of 24% in Nepal between 1980 and 2010 (Bajracharya et al., 2014).
Climate-change impacts on both the quantity and quality of freshwater resources will hinder the attainment of SDG-6 (Water, 2020). Contamination of drinking water is caused by wildfires and drought that contribute to elevated levels of nutrients (nitrogen, phosphorus and sulphates), heavy metals (lead, mercury, cadmium and chromium), salts (chloride and fluorides), hydrocarbons, pesticides and even pharmaceuticals. Heavy rains and flooding also increase nutrients, heavy metals and pesticides, as well as turbidity and faecal pathogens in water supplies–especially when sewage treatment plants are overwhelmed by runoff (Mora et al., 2018). Pharmaceuticals and personal-care products (from source to disposal) are contributing to the vulnerability of urban waters. A study of vulnerability assessment of urban waters in highly populated cities in India and Sri Lanka, through analysing the concurrence of Pharmaceuticals and Personal Care Products (PPCPs), enteric viruses, antibiotic-resistant bacteria, metals, faecal contamination and antibiotic resistance genes (ARGs), also underlines the need for a resilience strategy and action plan (Rafiq et al., 2019).
Adequate water supply for various uses is crucial for millions of people living in the mountains of Asia. Particularly in the HKH region, mountain springs play an important role in generating stream flow for non-glaciated catchments and in maintaining dry-season flows across many watersheds (Scott et al., 2019; Stott and Huq, 2014). There is a good deal of evidence that the springs are drying up or yielding less discharge (Tambe et al., 2012; Tiwari and Joshi, 2014; Sharma et al., 2016), threatening local communities who depend on spring water for their lives and livelihoods. Some of the main reasons for drying springs include anthropogenic impacts (deforestation, exploitative land use), infrastructure (road construction), socioeconomic changes (increasing demand and modernisation of facilities) and climatic changes (changes in rainfall regime and higher temperature) (Stott and Huq, 2014; Tiwari and Joshi, 2014; Sharma et al., 2016).
The Ganges–Brahmaputra region also faces the threat increased frequency of flood events (Lutz et al., 2019). Floods and extreme events can impact river channel systems (Grainger and Conway, 2014). One of the challenges in South Asia is the shifting boundaries of river channels. For instance, the major floods on the Indus in July 2010 altered the river’s course in Pakistan, moving it closer to the Indian district of Kutch (Grainger and Conway, 2014). In the eastern tributary of the Ganges system, the alluvial fan of the Koshi River basin has shifted by more than 113 km to the west in the past two centuries (Chakraborty et al., 2010), which may be due to heavy sediment load from the Himalayan rivers in which about 50 million tons of sediment is deposited annually in the alluvial plains (Sinha et al., 2019; Chakraborty et al., 2010).
Asia is no exception to the global trend of lake ecosystems, which provide drinking water to millions of people, being degraded (Jenny et al., 2020) and severely threatened at the same time by climate change (Mischke, 2020). Lake surface conditions, such as ice cover, surface temperature, evaporation and water level react dramatically to this threat, and there are negative implications for water quantity and quality, food provisioning, recreational opportunities and transportation (Woolway et al., 2020). Due to substantial regional variability, the quantum of future changes in lake water storage remains uncertain. A recent study (Liu et al., 2019a) using Moderate Resolution Imaging Spectroradiometer 500-m spatial resolution global water product data, and applying the least squares method to analyse changes in the area of 14 lakes in Central Asia from 2001 to 2016, has shown that the area-shrinkage changes for all plains lakes in the study region could be attributed to climate change and human activities.
Asian and global water demands for irrigation, despite geographic variation in terms of water availability, are very likely to surpass supply by 2050 (Chartres, 2014). A regional quantitative assessment (Lutz et al., 2019) of the impacts of 1.5°C versus 2°C global warming for a major global climate-change hotspot–the Indus, Ganges and Brahmaputra river basins (IGB) in South Asia–shows adverse impacts of climate change on agricultural production, hydropower production and human health. A global temperature increase of 1.5°C with respect to pre-industrial levels would imply a ≈ 2.1°C temperature increase for IGB, whereas under a 2.0°C global temperature increase scenario, these river basins would warm by ≈ 2.7°C. Future warming is expected to further increase rain-on-snow events that can cause snowmelt flood during winter (Ohba and Kawase, 2020), affecting hydropower and resulting in river flooding, avalanches and landslides.
In the Mekong River Delta (in Vietnam), with an area of 40,500 km 2 and home to 17.8 million people in 2018, climate change is projected to increase the average temperature by 1.1–3.6°C, and the maximum and minimum monthly flow are projected to increase and decrease, respectively, and are likely to result in a high risk of food during the wet season and water shortages during the dry season (Wang et al., 2021a).
Researchers have found that the southern Tibetan Plateau has been consistently melting from 1998–2007 and is projected to continue melting until 2050 (Lutz et al., 2014b) (high confidence). In HMA, glacier ice is projected to decrease by 49 ± 7% and 64 ± 5% by the end of the century under RCP4.5 and RCP8.5 scenarios, respectively (Kraaijenbrink et al., 2017). Local- and regional-scale projections suggest that peak water will generally be reached around the middle of the century, followed by steadily declining glacier runoff thereafter (Hock et al., 2019). A global-scale projection suggests that a decline in glacier runoff by 2100 (RCP8.5) may reduce basin runoff by about 10% for at least 1 month of the melt season (Huss and Hock, 2018). Significantly, research on climate change and its impact across Asia remains inconclusive and requires an assessment at the sub-regional scale (IPCC, 2014a; Wester et al., 2019).
There is a projection of an increase in runoff until the 2050s mainly due to an increase in precipitation in the upper Ganges, Brahmaputra, Salween and Mekong basins, where it could be due to accelerated melting in the upper Indus basin. The runoff could increase in the range of 3–27% (7–12% in Indus, 10–27% in Ganges and 3–8% in Brahmaputra) by mid-century compared with the reference period (1998–2008) for Himalayan river basins depending on the different RCP scenarios (Lutz et al., 2014a). Likewise, Khanal et al. (2021) suggest contrasting responses to climate change for HMA rivers in which, on the seasonal scale, the earlier onset of melting causes a shift in magnitude and peak of water availability, whereas on the annual scale, total water availability increases for the headwaters. The future flow would increase in Nepal’s Central Himalaya region (Nepal, 2016; Ragettli et al., 2016; Bajracharya et al., 2018). These changes in water availability in space and time will have serious consequences in downstream water availability for various sectoral uses and ecosystem functioning in Asia (Nepal et al., 2014; Green et al., 2015; Arfanuzzaman, 2018; Wijngaard et al., 2018; Rasul and Molden, 2019); however, future water availability is largely uncertain due to significant variation in climate-change projections among different global climate models (Nepal and Shrestha, 2015; Lutz et al., 2016; Li et al., 2019a).
A recent study (Didovets et al., 2021) covering eight river catchments having diverse natural conditions within Central Asia, where water availability or scarcity is also a major developmental concern, and using the eco-hydrological model SWIM (including scenarios from five bias-corrected GCMs under RCP4.5 and RCP8.5) has show an increase in mean annual temperature in all catchments for both RCPs to the end of the 21st century. The projected changes in annual precipitation indicate a clear trend to increase in the Zhabay and decrease in the Murghab catchments, and for other catchments, they were smaller. Both the projected trends for river discharge and precipitation show an increase in the northern and decrease in the southern parts of the study region, whereas seasonal changes include a shift in the peak of river discharge up to one month, a shortening of the snow accumulation period and a reduction in discharge during the summer months.
The intensity and frequency of extreme discharges are very likely to increase towards the end of the century. The future of the upper Indus basin water availability is highly uncertain in the long term due to uncertainty surrounding precipitation projections (Lutz et al., 2016). The future hydrological extremes of the upper Indus, Ganges and Brahmaputra river basins suggest an increase in the magnitude of extremes towards the end of the 21st century by applying RCP4.5 and RCP8.5 scenarios, mainly due to an increase in precipitation extremes (Wijngaard et al., 2017). In the Brahmaputra, Ganges and Meghna, including the downstream component, the runoff is projected to increase by 16, 33 and 40%, respectively, under the climate-change scenarios by the end of the century during which the changes in runoff are larger in the wet seasons than the dry seasons (Masood et al., 2015). In the Mekong River basin also, extremely high-flow events are likely to increase in both magnitude and frequency, which can exacerbate flood risk in the basin (Hoang et al., 2016); however, uncertainty is high regarding future hydrological response due to large variation in precipitation projections, modelling approaches and bias-correction methods (Nepal and Shrestha, 2015; Lutz et al., 2016; Li et al., 2019a).
Current research on the adverse relationship between climate change and river flows suggests that there is a high possibility that some of the river basins affected by floods could be Brahmaputra, Congo, Ganges, Lena and Mekong, with a return period of 10 years (Best, 2018).
In most parts of the upper Ganges and Brahmaputra rivers, the 50-year return level flood is likely to increase and to a lesser degree in Indus River. Similarly, the extreme precipitation events are also expected to increase to a higher degree in the Indus than the Ganges and Brahmaputra basins (Wijngaard et al., 2017). Increase in extreme precipitation events is likely to cause more flash-flood events in the future (medium confidence). In the case of the Indus, increasing temperature trend in the future may lead to accelerated snow and ice melting which may increase the frequency and intensity of floods in the downstream areas (Hayat et al., 2019). The Ganges–Brahmaputra region also faces the threat of increased frequency of flood events (Lutz et al., 2019). Additionally, the Ganges basin also shows a higher sensitivity to changes in temperature and precipitation (Mishra and Lilhare, 2016).
Assessing the impact of climate change on water resources in nine alpine catchments in arid and semiarid Xinjiang of China (Li et al., 2019a), it has been noted that even though the total discharge revealed an overall increasing trend in the near future, the impact of climate change on different hydrological components indicated significant spatio-temporal heterogeneity in terms of the area, elevation and slope of catchments, which could be usefully factored into climate-adaptation strategies.
It was noted early on (Singh et al., 2011) that the main drivers that influence the provisioning of ecosystem services and human well-being in the HKH region are a mix of environmental change in general and climate change in particular, but much more data and knowledge on the HKH region are needed in order to develop either a regional or global understanding of climate-change processes.
Climate change impacts cryospheric water sources in the Hindu Kush, Karakoram and Himalayan ranges which in turn carry consequences for the Indus, Ganges and Brahmaputra basins. The impact of climate change on spring-fed rivers in the HKH is under-researched and therefore makes projections difficult. Further research is needed for understanding the impact of deforestation, urbanisation, development and introduction of water infrastructures, such as tube wells, in the hill region (Aayog, 2017). This in turn calls for greater investment in research and development for the HKH by both the national and regional organisations. There is high confidence that due to global warming, Asian countries could experience an increase in drought conditions (5–20%) by the end of this century (Prudhomme et al., 2014; Satoh et al., 2017).
Soil erosion in high-mountain areas is particularly sensitive to climate change. A recent study (Wang et al., 2020) that focused on the mid-Yarlung Tsangpo River, located in the southern part of the Tibetan Plateau, has revealed dramatic land surface environment changes due to climate change during recent decades. It has further shown that increasing precipitation and temperature would lead to increasing soil-erosion risk in ~2050 based on the Coupled Model Intercomparison Project (CMIP5) and RUSLE models.
High-resolution climate-change simulations suggest that due to deadly heatwaves projected in some of the densely populated agricultural regions of South Asia (i.e., the Ganges and Indus river basins), those regions are likely to exceed the critical threshold of wet-bulb temperature of 35°C under the business-as-usual scenario of future GHG emissions (Im et al., 2017).
In Asia and its diverse sub-regions, the challenge of adaptation to climate change at diverse sectors, sites and scales of vulnerability in the domain of freshwater resources is compounded by the nexus between long-standing non-climatic vulnerabilities and climatic impacts, both observed and projected. Water insecurities in Asia are increasing due to excessive freshwater withdrawals (Satoh et al., 2017), economic and population growth (Gleick and Iceland, 2018), urbanisation and peri-urbanisation (Roth et al., 2019), food insecurity (Demin, 2014) and lack of access to clean and safe drinking water (Cullet, 2016), which mostly affects the health of the most vulnerable members of society.
Significantly, climate change will add to already existing vulnerabilities. In the case of the Yellow River basin in China, underlining the interface between future water scarcity and hydroclimatic and anthropogenic drivers, a recent study expects moderate-to-severe water scarcity over six Yellow River sub-catchments under the RCP4.5 scenario, and anticipates that human influences on water scarcity will be worse than that of climate change, with water availability in the downstream being impacted by concurrent changes in land use and high temperature (Omer et al., 2020). Nearly 8% of internationally shared or transboundary aquifers (TBAs), ensuring livelihood security for millions of people through sustaining drinking water supply and food production, are currently overstressed due to human overexploitation (Wada and Heinrich, 2013). The Asia Pacific region has the highest annual water withdrawal due to its geographic size, growing population and irrigation practices, and water for agriculture continues to consume 80% of the region’s resources (Taniguchi et al., 2017b; Visvanathan, 2018).
In South Asia, surface water and groundwater resources are already under stress (both in terms of quality and quantity) due to population growth, economic development, poor governance and management, and poor efficiency of use in economic production. In the past 40 years, there has been an increasing reliance on groundwater in South Asia for irrigation (Rodell et al., 2009; Tiwari et al., 2009; Surie and Prasai, 2015; Bhanja et al., 2016; Shrestha et al., 2016; Mukherjee, 2018; Shah et al., 2018). It is noteworthy that India, Bangladesh, Pakistan and China together account for more than 50% of the world’s groundwater withdrawals (Scott et al., 2019). A study conducted in the Shahpur and Maner districts of Bihar, India, in which drinking water sourced from the groundwater of 388 households was tested, showed that 70–90% of the sampled household’s drinking water contained either arsenic or iron, or both (Thakur and Gupta, 2019). Given the nexus between CIDs and non-climate drivers, an effective adaptation to the impacts of climate change would also demand sustainable development and management of shared aquifer resources, which in turn require reliable TBA inventories and improved knowledge production and knowledge sharing on the shared groundwater systems (Lee et al., 2018a).
A study of peri-urban spaces involving four South Asian cities, Khulna (Bangladesh) (Pervin et al., 2020), Gurugram and Hyderabad (India), and Kathmandu (Nepal), has shown the nexus between intensifying use and deteriorating quality of water and the impact of climate change, resulting in peri-urban water insecurity and conflict (Roth et al., 2019). The challenge of ensuring access to water resources and their (re)allocation and prioritisation for marginalised communities remains on the agenda of policy-oriented interdisciplinary research and demands effective implementation of its findings at the grassroots level by the administrative agencies. Taking water security as a key CCA goal at the urban-city scale of Bangkok, a study (Babel et al., 2020) has shown the usefulness of a generic framework with 5 dimensions, 12 indicators and a set of potential variables to support national-level initiatives and plans in diverse climatic and socioeconomic conditions across various sub-regions of Asia.
In the Kathmandu valley in Nepal, where groundwater resources are under immense pressure from multiple stresses, including overextraction and climate change, mapping groundwater resilience to climate change has been demonstrated as a useful tool to understand the dynamics of groundwater systems, and thereby facilitate the development of strategies for sustainable groundwater management (Shrestha et al., 2020).
In the Mekong Delta, the groundwater storage is projected to decline by more than 120 and 160 million m 3 under RCP4.5 and RCP8.5 scenarios, respectively, by the end of the 21st century, in conjunction with land subsidence and SLR. This in turn calls for proactive planning and implementation of adaptation strategies that address multiple stresses in order to ensure sustainable utilisation of groundwater resources in the Mekong Delta in the context of future climatic conditions and associated uncertainties (Wang et al., 2021a). Proposed CCA strategies for the Mekong River basin include a better understanding of the complex linkages between climate change, technological interventions, land-use change, water-use change and socioeconomic developments both in the upstream and downstream riparian countries (Evers and Pathirana, 2018).
While South Asian countries have done well in attaining Goal 6 of Sustaining Development Goals, access to safe and clean drinking water remains a challenge. Taking Indian rivers as an example, it is suggested that participatory river protection and rehabilitation, based on comprehensive knowledge of the river-system dynamics, and local awareness at the community level, may act as a multiplier for river conservation measures (Nandi et al., 2016).
Hydroclimatic extremes in the HKH region could adversely impact the Ganga, Brahmaputra and Meghna basins (Wijngaard et al., 2017; Acharya and Prakash, 2019). Studies have recommended watershed or basin analysis to address the challenge of adaptation in urban spaces (Lele et al., 2018). A study of northern Bangladesh that focused on encouraging traditional ways of cultivation suggests that rural women have Indigenous knowledge and their participation can play a useful role (Kanak Pervez et al., 2015). The knowledge pertains to agriculture, soil conservation, fish and animal production, irrigation and water conservation. There has also been a focus on gendered construction of local flood-forecasting knowledge in rural communities in India living in the Gandak River basin (Acharya and Prakash, 2019). While designing the adaptation options, understanding the water–energy–food (WEF) nexus among different water-use sectors is crucial (Section 10.5.3). Understanding of the WEF nexus could be beneficial for achieving water security in developing countries in Asia (Nepal et al., 2019).
AR5 identified a number of adaptation challenges and options facing the stakeholders in the wake of climate-change-induced vulnerabilities, uncertainties and risks in the freshwater sector, and underlined the importance of an integrated management approach as well as acknowledging diverse socioeconomic contexts, differentiated capacities and the uneven pace of impacts. Further validated by recent research in terms of their usefulness, these adaptation options include building and improving capital-intensive physical water infrastructure such as irrigation channels, flood-control dams and water storage (Nüsser and Schmidt, 2017). Drawing upon customary institutions and combining Indigenous knowledge systems with scientific knowledge, innovative structures, including artificial glaciers, ice stupas and snow barrier bands, have been built by local communities in Ladakh, Zanskar and Himachal Pradesh in India (Hock et al., 2019; Nüsser et al., 2019). Communities in Solukhumbu, Nepal, in response to depleting water flow in snow-fed rivers, have chosen adaptation through changing practices by collecting water from distant sources for domestic consumption (McDowell et al., 2013). Taking the IPCC concept of climate risk as a basis for adaptation planning, a pilot study of flood risk in Himachal Pradesh, India (Allen et al., 2018), integrating assessment of hazard, vulnerability and exposure in the complementary domains of CCA and DRR, has identified stakeholder consultation, knowledge exchange and institutional capacity building as key steps in adaptation planning. Aquifer storage and recovery has been proposed as an ‘alternative climate-proof freshwater source’ for deltaic regions in Asia, particularly those with a history of saline groundwater aquifers (Hoque et al., 2016). It is further argued (Hadwen et al., 2015) that water, sanitation and hygiene objectives would need to be addressed as a component of a wider integrated water resource management (IWRM) framework.
Ensuring sustainability of the rivers and ecosystems requires coordinated and collaborative action on the part of all countries, with the long-term goal of synergising political, social, cultural and ecological facets associated with the riverine system. Daunting as this challenge is, evidence suggests that a long-term view of transboundary basins is not very optimistic as big rivers of Asia contribute heavily towards urban and agricultural activities, and are experiencing challenges of increasing sedimentation, large-scale damming and pollution, among others (Best, 2018). In the case of China, Sun et al. (2016) have shown that the localised vulnerabilities within the Yangtze River basin prompt an ‘integrated basin-wide approach’ that is able to account for the specific needs of each of its sub-basins.
In HMA, factors that undermine effective adaptation to climate change include both sudden-onset and slow-paced disasters along with the knowledge deficit regarding cryospheric change and its adverse impacts on water resources and also the agriculture and hydropower sectors. Other key barriers include a sectoral approach, overemphasis on structural approaches and the lack of context-sensitive, community-centric understanding of how these changes influence perceptions, options and decisions about migration, relocation and resettlement (Rasul et al., 2020; Hock et al., 2019). More interdisciplinary research is needed on highly precarious future pathways and the intersection between CIDs and non-climate drivers in order to anticipate and mitigate diverging and uncertain outcomes.
Box 10.4 | Case Study on Climate Vulnerability and Cross-Boundary Adaptation in Central Asia
In Central Asia, water scarcity has been ranked in the top five global risks (Gleick, 1993; Zhupankhan et al., 2018). Cross-boundary adaptation remains critically important in this region with abundant glaciers in the Pamir Plateau of Tajikistan (Hu et al., 2017) and areas with severe glacier retreat in the Tianshan Mountains (Liu and Liu, 2015). The spatial variations of glacier and other climate variables have added to uncertainty related to the dynamic of the water cycle. The headwater regions, such as Pamir area, would be significantly affected by the climate parameters, such as the stronger rainfall intensity, more frequent rainfall and higher temperature (Luo et al., 2019). The water resources in the Pamir Plateau will range from −0.48 to 5.6% (Gulakhmadov et al., 2020), and the crop phenological period in Tajikistan and Kyrgyzstan will be about 1–2 weeks earlier. The threat of agricultural water stress is increasing as well. The oasis in downstream areas will face more complex water resource fluctuations, water crisis and desertification. In particular, rain-fed agriculture in northern Kazakhstan, Uzbekistan and western Turkmenistan is particularly dependent on water resources. Under the RCP2.6 and RCP4.5 scenarios, considering CO2 fertilisation effects and land-use projections, the increase in CO2 atmospheric concentration and accumulated temperature can contribute to a 23% increase in cotton yield in Central Asia (Tian and Zhang, 2019), but extreme climate, such as drought, heatwaves and rainstorms, will have a 10% negative impact on agricultural production and the ecological environment (Zhang and Ren, 2017). High-efficiency water-saving technology will help the upstream and downstream water resource management in Central Asian countries to adapt to the variation in water resources quantity, frequency and spatial pattern.
Asia accounts for 67% of global agricultural production (Mendelsohn, 2014) and employs a large portion of the population in many developing countries and regions (Briones and Felipe, 2013; ADB, 2017b; ILO, 2017a). Since the release of IPCC AR5, more studies have reinforced the earlier findings on the spatio-temporal diversity of climate-change impacts on food production in Asia depending on the geographic location, agroecology and crops grown (Hoegh-Guldberg et al., 2018; Ahmad et al., 2019), recognising that there are winners and losers associated with the changing climate across scales (Dasgupta et al., 2013a; Yong-Jian et al., 2013; Bobojonov and Aw-Hassan, 2014; Hijioka et al., 2014; Li et al., 2014a; Prabnakorn et al., 2018; Trisurat et al., 2018; Matsumoto, 2019). Despite the observed increase in total food production in terms of crops and food yields from 1990 to 2014 in Asia (FAO, 2015), there is high confidence that overall, at the regional level, the projected total negative impacts will far outweigh the expected benefits, with India emerging as the most vulnerable nation in terms of crop production (Figure 10.6). Recent evidence also indicates that climate-related risks to agriculture and food security in Asia will progressively escalate as global warming reaches 1.5°C and higher above pre-industrial levels (IPCC, 2018b) with differentiated impacts across the Asian continent.
Figure 10.6 | Projected impacts of climate change to agriculture and food systems in sub-regions of Asia based on post-IPCC-AR5 studies. The figure illustrates the spatio-temporal diversity of projected future impacts on food production highlighting that there are winners and losers associated with the changing climate at different scales. AGRI: agriculture; E: east; N: north; NRCP: no RCP analysis; Pre: precipitation; PY: production yield; RCP: representative concentration pathway; S: south; Temp: temperature; W: west. (Refer to Table SM10.2 for details and supporting references.)
There remains a paucity of data for observed climate-change impacts on Asian agriculture and food systems since the release of IPCC AR5. Most of these impacts have been associated with drought, monsoon rain and oceanic oscillations, the frequency and severity of which have been linked with the changing climate (Heino et al., 2018; Heino et al., 2020). In general, major impacts to agricultural production, such as those observed by the farmers in the Philippines and Indonesia, include among others delays in crop harvesting, declining crop yields and quality of produce, increasing incidence of pests and diseases, stunted growth, livestock mortality and low farm income (Stevenson et al., 2013). In South Asia, the series of monsoon floods from 2005 to 2015 contributed to a high level of loss in agricultural production with peaks in 2008 and 2015 (FAO, 2018a). Similarly, in Pakistan, farmers are experiencing a decline in crop yields and increasing incidence of crop diseases as a result of climate extremes, particularly floods, droughts and heatwaves (Fahad and Wang, 2018; Ahmad et al., 2019).
Limited studies have quantified the actual impacts of climate change on agricultural productivity and the economy. In a study in the Mun River basin, northeast Thailand, yield losses of rice due to past climate trends covering the period 1984–2013 was determined to be in the range of < 50 kg ha –1 per decade or 3% of actual average yields with a high possibility of more serious yield losses in the future (Prabnakorn et al., 2018). Likewise, in China, an economic loss of 595–858 million USD for the corn and soybean sectors was computed from 2000 to 2009 (Chen et al., 2016b). On the other hand, the intensive wheat–maize system in China seems to have benefited from climate change with the northward expansion of the northern limits of maize and multi-cropping systems brought about by the rising temperatures (Li and Li, 2014).
There is high agreement in more recent studies that linked the frequency and extent of the El Niño phenomenon with global warming (Thirumalai et al., 2017; Wang et al., 2017a; Hoegh-Guldberg et al., 2018) that can trigger substantial loss in crop and fishery production. The 2004 El Niño caused the Philippines an 18% production loss during the dry season and a 32% production loss during the wet season (Cruz et al., 2017). In the 2015 El Niño event, the Indian oil sardine fishery declined by more than 50% of previous years (Kripa et al., 2018) severely impacting coastal livelihoods and economies (Shyam et al., 2017). The 2015–2016 El Niño also inflicted adverse impacts on agricultural productivity and food security, especially affecting the rural poor in middle- and lower-income countries in Southeast and South Asia (UNDP ESCAP OCHA RIMES APCC, 2017).
The fisheries and aquaculture production from Asia in 2019 was estimated at 159.67 mmt contributing to 74.7% of the global production (FAO, 2020). This sector provides employment to an estimated 50.46 million people where fishing and aquaculture are important socioeconomic activities and fish products are a substantial source of animal protein (Bogard et al., 2015; Azad, 2017; FAO, 2018c). The economic contribution could be as high as 44% of the coastal communities’ GDP as in the case of Sri Lanka (Sarathchandra et al., 2018). Five Asian countries (i.e., China, Indonesia, India, Vietnam and Japan) are in the top ten of global fish producers, representing a cumulative share of 36% in 2018 (FAO, 2020). As a top producer with 15% global share, China also remains a top exporter of fish and fish products with 14% global market share.
There is high agreement in the literature that Asian fisheries and aquaculture, including the local communities depending on them for livelihoods, are highly vulnerable to the impacts of climate change. Asia has been impacted by SLR (Panpeng and Ahmad, 2017), a decrease in precipitation in some parts (Salik et al., 2015) and an increase in temperature (Vivekanandan et al., 2016), all of which have drastic effects on fisheries and aquaculture (FAO, 2018c). Its coastal fishing communities is exposed to disasters, which are predicted to increase (Esham et al., 2018). Fisheries in most of South Asia and Southeast Asia involve small-scale fishers who are more vulnerable to climate-change impacts compared with commercial fishers (Sönke Kreft et al., 2016; Blasiak et al., 2017), although there is a general decreasing trend in the number of small units (Fernandez-Llamazares et al., 2015; ILO, 2015). A regional study of South Asia forecast large decreases in potential catch of two key commercial fish species (hilsa shad and Bombay duck) in the Bay of Bengal (Fernandes et al., 2016), which forms a major fishery and food source for coastal communities. About 69% of the commercially important species of the Indian marine fisheries were found to be impacted by climate change and other anthropogenic factors (Dineshbabu et al., 2020). Likewise, water salinisation brought about by SLR is expected to impact the availability of freshwater fish in southwest coastal Bangladesh with adverse implications to poor communities (Dasgupta et al., 2017a). Analysis of fishery has indicated that there will be a continued decrease in catch impacting the seafood sector in the Philippines, Thailand, Malaysia and Indonesia (Nong, 2019). Climate change is predicted to decrease total productive fisheries potential in South and Southeast Asia, driven by a temperature increase of approximately 2°C by 2050 (Barange et al., 2014).
Like fisheries, Asian aquaculture is highly vulnerable to climate change. Shrimp farmers and fry catchers of Bangladesh are frequently affected by extreme climatic disruptions like cyclones and storm surges that severely damage the entire coastal aquaculture (Islam et al., 2016a; Kais and Islam, 2018). The majority of shrimp farmers also observed that weather has changed abruptly during the past 5 years and that high temperature is most detrimental because it lowers growth rate, increases susceptibility to diseases, including deformation, and affects production (Islam et al., 2016a). Low production in shrimp farming is also attributed to variation and intensity of rainfall perceived by the majority of farmers as part of climate-change impacts (Ahmed and Diana, 2015; Islam et al., 2016a; Henriksson et al., 2019). In Vietnam, small-scale shrimp farmers are likewise vulnerable to climate change, although those who practise an extensive type of farming with low inputs are more vulnerable compared with those who practise a more intensive type with more capital investment (Quach et al., 2015; Quach et al., 2017). Seaweed farming in Asia is very popular, and the significance of seaweed aquaculture beds in capturing carbon is recognised, but most of the farmed seaweeds are susceptible to climate change (Chung et al., 2017a; Duarte et al., 2017).
Marine heatwaves are a new threat to fisheries and aquaculture (Froehlich et al., 2018; Frölicher and Laufkötter, 2018) including disease spread (Oliver et al., 2017), live feed culture (copepods) (Doan et al., 2018) and farming of finfishes like Cobia (Le et al., 2020). Predicting MHWs is considered a prerequisite for increasing the preparedness of farmers (Frölicher and Laufkötter, 2018). In Southeast Asian countries more than 30% of aquaculture areas are predicted to become unsuitable for production by 2050–2070 and aquaculture production is predicted to decrease 10–20% by 2050–2070 due to climate change (Froehlich et al., 2018).
Since IPCC AR5, more studies have been done on different scales from local to global that focus on the differentiated projected impacts of climate change on the production and economics of various crops with rice, maize and wheat among the major crops receiving more attention. New research findings affirm that climate-change impacts, and will continue to significantly affect, crop production in diverse ways in particular areas all over Asia (Figure 10.6). An increasing number of sub-regional and regional studies using various modelling tools provide significant evidence on the overall projected impacts of climate change on crop production at the sub-regional and regional scales with clear indications of winners and losers among and within nations (see, for instance, Mendelsohn, 2014; Cai et al., 2016; Chen et al., 2016b; Schleussner et al., 2016).
Beyond the usual research interest in crop yields which has dominated the current literature, recent studies, such as those in Japan, focus on the impacts of climate change on the quality of crops (see, for instance, Sugiura et al., 2013, for apple; as well as Morita et al., 2016, and Masutomi et al., 2019, for rice). A large-scale evaluation by Ishigooka et al. (2017) shows that the increased risk in rice production brought about by temperature increase may be avoided by selecting an optimum transplanting date considering both yield and quality. More studies of this nature have to be conducted for other crops in different locations to better understand and adapt to the negative impacts of the changing climate on the quality of crops (Ahmed and Stepp, 2016).
New studies have projected the likely negative impact of pests in Asian agriculture. The golden apple snail (Pomacea canaliculate), which is among the world’s 100 most notorious invasive alien species, threatens the top Asian rice-producing countries, including China, India, Indonesia, Bangladesh, Vietnam, Thailand, Myanmar, the Philippines and Japan, with the predicted increase in climatically suitable habitats in 2080 (Lei et al., 2017). Similarly, a study by (Shabani et al., 2018) in Oman projected that the pest of date palm trees, Dubas bug (Ommatissus lybicusBergevin), could reduce the crop yield by 50% under future climate scenarios.
While there is general agreement that CO2 promotes growth and productivity of plants through enhanced photosynthesis, there remains uncertainty on the extent to which carbon fertilisation will influence agricultural production in Asia as it interacts with increasing temperatures, changing water availability and the different adaptation measures employed (Ju et al., 2013; Jat et al., 2016; ADB, 2017b). As global warming compounds beyond 1.5°C, however, the likelihood of adverse impacts on agricultural and food security in many parts of developing Asia increases (Mendelsohn, 2014; IPCC, 2018b). There is a growing trend towards more integrated studies and modelling that combines biophysical and socioeconomic variables (including management practices) in the context of changing climate to reduce uncertainty associated with future impacts of climate change on the agriculture sector (see, for instance, Mason-D’Croz et al., 2016; Smeets Kristkova et al., 2016; Gaydon et al., 2017).
There is hardly any mention about the impacts of climate change on livestock production in the Asia chapter of AR5 due to limited studies on this area. This scarcity of information persists to the current assessment with very scant information on the projected impacts and adaptation aspects of livestock production (Escarcha et al., 2018a). The use of scenarios and models to determine alternative futures with participatory engagement processes has been recommended for informed policy and decision making with potential application in the livestock sector (Mason-D’Croz et al., 2016). Of the limited assessment available, a study on the smallholders’ risk perceptions of climate change impacts on water-buffalo production systems in Nueva Ecija, the Philippines, identified feed availability and animal health as the production aspects most severely affected by multiple weather extremes (Escarcha et al., 2018b). In the Mongolian Altai Mountains, early snowmelt and an extended growing season have resulted in reduced herder mobility and prolonged pasture use, which has in turn initiated grassland degradation (Lkhagvadorj et al., 2013a). Furthermore, reduced herder mobility has increased the pressure on forests resulting in increased logging for fuel and construction wood and reduced regeneration due to browsing damage by increasing goat populations (Khishigjargal et al., 2013; Dulamsuren et al., 2014).
In terms of direct impacts, climate-change-induced heat stress and reduced water availability are likely to generally have negative effects on livestock (ADB, 2017b). In the HKH region, climate change has induced severe impacts on livestock through degradation of rangelands, pastures and forests (Hussain et al., 2019). However, indirect effects may be positive such as in Uzbekistan and South Asia where alfalfa and grassland productivity is expected to improve under warming conditions, which have beneficial effects on livestock production (Sutton et al., 2013; Weindl et al., 2015).
At the global level, analysis involving 148 countries in terms of the potential vulnerability of their livestock sector to climate and population change shows that some Asian nations, particularly Mongolia, are likely to be the most vulnerable while South Asia is the most vulnerable region (Godber and Wall, 2014).
There is new evidence since AR5 that farming systems and crop areas will change in many parts of Asia in response to climate change. In South Asia, a study in Nepal showed that farmers are inclined to change practices in cropland use to reduce climate-change risk (Chalise and Naranpanawa, 2016). In India, climate change is also predicted to lead to boundary changes in areas suitable for growing certain crops (Srinivasa Rao et al., 2016). A study in Bangladesh revealed a shift in crop choices among farmers, implying changes in the future rice-cropping pattern. Specifically, a temperature increase will compel farmers to choose irrigation-based Boro, Aus and other crops in favour of the rain-fed Aman rice crop (Moniruzzaman, 2015).
In the coastal area of Odisha in India, adverse impact on the agriculture sector is anticipated considering the increasing temperature trends over the past 30 years for all the seasons (Mishra and Sahu, 2014). In a national study that groups Bangladesh into 16 sub-regions with similar farming areas, simulations of a 62 cm rise in mean sea level project damages to production because of area loss in excess of 31% in sub-region 15 and nearly 40% in sub-region 16 (Ruane et al., 2013). Also in Bangladesh, a study on predicting the design of water requirements for winter paddy rice under climate change conditions shows that agricultural water resource management will help minimise drought risk and implement future agricultural water resource policies (Islam et al., 2018) that may have important implications for crop areas and production.
In East Asia, the observed changes in agricultural flooding in different parts of China could influence farming systems and crop areas (Zhang et al., 2016b) as extreme events intensify in the context of changing climate. Agricultural management practice in China may also change to optimise soil organic carbon sequestration (Zhang et al., 2016a). A study on projected irrigation requirements under climate change using a soil-moisture model for 29 upland crops in the Republic of Korea showed that water scarcity is a major limiting factor for sustainable agricultural production (Hong et al., 2016). In terms of drought, despite increasing future precipitation in most scenarios, crop-specific agricultural drought is expected to be a significant risk due to rainfall variability (Lim et al., 2019a). On the other hand, a projected rise in water availability in the Korean Peninsula using multiple regional climate models and evapotranspiration methods indicates that it will likely increase agricultural productivity for both rice and corn, but would decrease significantly in rain-fed conditions (Lim et al., 2017b). Thus, irrigation and soil-water management will be a major factor in determining future farming systems and crop areas in the country.
Global studies on climate-change-induced hotspots of heat stress on agricultural crops show that large suitable cropping areas in Central and Eastern Asia, and the northern part of the Indian subcontinent, are under heat stress risk under the A1B emissions scenario (Teixeira et al., 2013) and hence may reduce cropping areas in these regions. In Japan, the projected decline in rice yield in some areas suggests that the current rice-producing regions would be divided into suitable and unsuitable areas as temperatures increases (Ishigooka et al., 2017), with important implications regarding the possible shift in cropping area. Similarly, it has been shown that there will be change in the geographic distribution of the occurrence of poor skin colour of table-grape berries (Sugiura et al., 2019) and suitable areas for cultivation of subtropical citrus (Sugiura et al., 2014) in Japan by the middle of the 21st century.
There is emerging evidence from modelling and field experimentation that designing future farming systems and crop areas that will promote sustainable development in Asia in the context of climate change would have to incorporate not only productivity and price considerations but also how to moderate temperature increase, enhance water conservation and optimise GHG mitigation potential (Sapkota et al., 2015; Zhang et al., 2016a; Ko et al., 2017; Lim et al., 2017b). The effects of agricultural landscape change on ecosystem services also need to be understood and taken into account in designing farming systems and allocating farm areas (Lee et al., 2015b; Zanzanaini et al., 2017).
FAO (2001) defines food security as ‘a situation that exists when all people, at all times, have physical, social and economic access to sufficient, safe and nutritious food that meets their dietary needs and food preferences for an active and healthy life’. There is significant evidence that climate change significantly undermines both agricultural production and food security in Asia (ADB, 2017b). Increasing evidence from sub-regions and individual countries suggests that climate-related hazards, such as increasing temperature, changing rainfall, SLR, drought, flooding and the more frequent and intense occurrences of El Niño–Southern Oscillation events, all impact agricultural production with significant effects on food security. All these hazards interact with non-climatic factors, such as competing demand for scarce water resources, rural–urban migration, food prices and increasing food demand in the long term, and poor governance, among other things, that may worsen food insecurity in the region (Montesclaros and Teng, 2021).
In West Asia, particularly in Saudi Arabia and Yemen, increasing water scarcity brought about by temperature rise is anticipated to have a severe impact on agriculture and food production that undermines food security (Al-Zahrani et al., 2019; Baig et al., 2019). Saudi Arabia, for instance, was forced to phase out its wheat production starting in 2016 and fully rely on importation to conserve its drying fossil water resources (Al-Zahrani et al., 2019), a situation which is also linked to a water governance issue.
In Central Asia, a study using a bioeconomic farm model shows very large differences in climate change impacts across farming systems at the subnational level. Large-scale commercial farms in the northern regions of Kazakhstan will have positive income gains, while small-scale farms in arid zones of Tajikistan will experience a negative impact with likely effects on farm income security (Bobojonov and Aw-Hassan, 2014). Impacts on farmers’ income in western Uzbekistan will also significantly vary and could fall by as much as 25% depending on the extent of temperature increase and water-use efficiency (Bobojonov et al., 2016).
In a regional study among South Asian countries using an integrated assessment modelling framework, changes in rice and wheat productions brought about by climate change are anticipated to engender wild price volatilities in the markets (Cai et al., 2016). Price spikes are projected for 2015–2040 in all South Asian regions with India, Pakistan and Sri Lanka predicted to experience increasingly much higher rice and wheat prices than under the baseline scenario, creating major concerns about food affordability and food security. This will likely severely affect the overall economic growth of these countries since they are mainly agriculture-driven economies.
A study on mapping global patterns of drought risk projected an increase in drought frequency and intensity in the populated areas of South to Central Asia extensively used for crop and livestock production with serious repercussion to food security and potential civil conflict in the medium to long term (Carrão et al., 2016). In Southeast Asia, a Philippine study on the relationship between seasonal rainfall, agricultural production and civil conflict suggests that the projected change towards wetter rainy seasons and drier dry seasons in many parts of the country will lead to more civil conflict (Crost et al., 2018) with negative implications for food and human security. Similarly, floods and higher food prices are also associated with higher risks of social unrest in Asia that may undermine food security (Hendrix and Haggard, 2015; Ide et al., 2021).
Food insecurity will be localised across Asia where one part of the country or sub-region will be more food secured while the others, more insecure. This will require in-country or sub-regional trade and development cooperation to minimise the adverse impacts of food insecurity associated with the changing climate (Li et al., 2014a; Abid et al., 2016).
There is high confidence that agriculture will continue to be among the most vulnerable sectors in Asia in light of the changing climate (Mendelsohn, 2014; ADB, 2017b). Among the more vulnerable areas include mountain agriculture where fluctuation in crop production (Poudel and Shaw, 2016; Hussain et al., 2019), and food insufficiency, is more widespread than in lowland areas (Poudel and Shaw, 2015; Kohler and Maselli, 2009). Also vulnerable are flood-prone areas like the Vietnam Mekong River Delta where 39% of the total rice area is exposed to sustained flood risks (Wassmann et al., 2019a). Increasing temperatures and changing precipitation levels will persist to be important vulnerability drivers that will shape agricultural productivity particularly in South Asia, Southeast Asia and Central Asia as well as in selected areas of the region. With the increasing likelihood of extreme weather events, such as strong typhoons in the Philippines, the agriculture sector in the typhoon-prone areas of Southeast and East Asia, as well as the Indus Delta, will be more vulnerable to crop destruction (Mallari and Ezra, 2016). Projections on increasing SLR and flooding, such as those in Bangladesh and the Mekong Delta, will submerge and decrease crop production areas and severely affect agriculture and fishery sectors, but will also trigger outmigration from these areas (ADB, 2017b).
Vulnerability of aquaculture-related livelihoods to climate change was assessed at the global scale using the MAGICC/SCENGEN climate modelling tools, and Vietnam and Thailand were identified as most vulnerable in brackish-water aquaculture production (Handisyde et al., 2017). China, Vietnam and the Philippines are also ranked highly vulnerable in marine production. Moreover, a recent vulnerability assessment of Korean aquaculture based on predicted changes in seawater temperature and salinity according to RCP8.5 indicated that vulnerability was highest for seaweed, such as laver and sea mustard, while fish, shrimp and abalone are relatively less vulnerable as they are less sensitive to high water temperature and their farming environments are controllable to a large extent (Kim et al., 2019a). In Indonesia, farming of whiteleg shrimp (Litopenaeus vannamei) has been found to be vulnerable to increased rainfall and temperature decrease (Puspa et al., 2018).
Climate-change-induced vulnerability, however, is complicated by non-climate drivers. In Thailand, for instance, a 38% reduction (from 21,486 to 13,328 million at the present value (1 USD = 33.54 THB) in the export values of rice and products in the last quarter of 2011 has been attributed not only to the impact of tropical cyclone Nock-Ten on Thai rice export but also the economic slowdown in Thailand during 2011–2012 (Nara et al., 2014).
Considering the high vulnerability of Asia to climate change as a whole, there is a need to look at the drivers of vulnerability in an integrated and comprehensive manner. The increasing interest on nexus studies that links climate-change impacts on agriculture with the other sectors like water, energy, land-use change, urbanisation, poverty, economic liberalisation and others (see, for example, Takama et al., 2016; Aich et al., 2017; Eslamian et al., 2017; Duan et al., 2019b) could contribute to a systemwide vulnerability reduction and an important initial step towards a more climate-resilient future.
Since AR5, there has been a surge in the volume of literature that documents and assesses the different adaptation practices already employed in Asian agriculture as well as those that provide future adaptation options. There is robust evidence that a variety of adaptation practices already employed in agriculture and fisheries are valuable in reducing the negative effects of current climate anomalies but may not be sufficient to fully offset the adverse impacts of future climate scenarios. Recent literature, therefore, focuses on how to build on current adaptation initiatives and processes to improve current and future outcomes (Iizumi, 2019).
Asian farmers and fishers already employ a variety of adaptation practices to minimise the adverse impacts of climate change. In a recent systematic and comprehensive review of farmers’ adaptation practices in Asia, Shaffril et al. (2018) categorised these practices into different forms such as crop management, irrigation and water management, farm management, financial management, physical infrastructure management and social activities. ‘Climate-smart agriculture’–an integrated approach for developing agricultural strategies that address the intertwined challenges of food security and climate change–is increasingly being promoted in many parts of the region, especially in Southeast and South Asia, with potentially promising outcomes (Chandra et al., 2017; Khatri-Chhetri et al., 2017; Shirsath et al., 2017; Westermann et al., 2018; Wassmann et al., 2019b). Site-specific adaptations, such as those in Pakistan, include farmers’ utilisation of several adaptation techniques which include changing crop type and variety, and improving seed quality; fertiliser application and use of pesticides, and planting of shade trees; and water storage and farm diversification (Fahad and Wang, 2018), as well as the implementation of comprehensive climate information services for farming communities (World Meteorological Organization, 2017).
Adaptation measures are also beneficial to small-scale fishers and fish farmers (Miller et al., 2018), and through fisheries management plans (FMP) and Early warning systems, the Asian region is reducing climate impact (FAO, 2018c). The most common FMPs adopted in different Asian countries are limits to fishing gear, licensing schemes and seasonal closures (ILO, 2015), protection of nursery grounds, providing alternative livelihoods (Azad, 2017), limiting fish aggregating devices (FADs) and introduction of monitoring and control tools (Department of Fisheries (Thailand), 2015). Fishers’ strong sense of belonging to their place of residence and the sense of responsibility to protect the vulnerable fish stock has been advantageously used for developing cooperatives and starting community-based fisheries management (FAO, 2012; ILO, 2015; Shaffril et al., 2017), and these initiatives have yielded positive results.
In aquaculture, most households in shrimp communities rely on process-oriented multiple coping mechanisms such as consumption smoothing, income smoothing and migration that enhance farmers’ resilience to climate anomalies (Kais and Islam, 2018). Diversification and integration of varied resources and interventions in feed and husbandry are seen to help the aqua farmers increase their profits and overcome the impacts of climate change (Henriksson et al., 2019). Strategies like polyculture, integrated multitrophic aquaculture (IMTA) and recirculating aquaculture systems (RAS) have been suggested to increase aquaculture productivity, environmental sustainability and climate change adaptability (Ahmed et al., 2019c; Tran et al., 2020). In Bangladesh, several adaptation measures, such as integrated community-based adaptation strategies (Akber et al., 2017) and integrated coastal zone management (Ahmed and Diana, 2015), have been recommended to increase climate resilience among shrimp farmers.
More recently, nature-based solutions (NbS) have gained attention globally to enhance climate adaptation. In the context of agriculture, NbS are seen as cost-effective interventions that can increase resilience in food production while advancing climate mitigation and improving the environment (Iseman and Miralles-Wilhelm, 2021 ). Experiences in implementing NbS in agricultural landscapes have been documented both in agriculture and fisheries sectors that promote production while providing co-benefits such as environmental protection and sustainability (Miralles-Wilhelm, 2021).
Despite the numerous adaptation measures already employed, there is sufficient evidence that farmers’ current adaptation practices are inadequate to offset the worsening climate change impacts. A more comprehensive approach that integrates economic and social strategies with other measures is seen to reduce climate vulnerability. For instance, agriculture insurance is viewed as a promising adaptation approach to reduce risks and increase the financial resilience of farmers and herders in many Asian countries (Prabhakar et al., 2018; Matheswaran et al., 2019; Nguyen et al., 2019; Stringer et al., 2020). Similarly, participation of multiple stakeholders from all relevant sectors at different levels in adaptation planning and decision making is seen as an important factor in improving outcomes (Arunrat et al., 2017; Hochman et al., 2017; Chandra and McNamara, 2018). Moreover, while adaptation is local and context specific, the following general adaptation-related strategies are distilled from the current literature, based on the Asian experience, to enhance current and future adaptations (see Figure 10.7 for details or examples of each strategy):
Figure 10.7 | Adaptation-related strategies in Asian agriculture to enhance current and future adaptations.
Cities across Asia have large populations exposed to climate risks but also present an opportunity for concerted climate action (Revi et al., 2014; Chu et al., 2017; Revi, 2017; Khosla and Bhardwaj, 2019) and report numerous examples of adaptation actions at various stages of planning and implementation (Dulal, 2019; Singh et al., 2021b). However, challenges specific (though not exclusive) to Asian cities such as uneven economic development, rapid land-use changes, increasing inequality, growing exposure to extreme events and environmental change, such as land subsidence (with antecedent impacts on people and infrastructure), and large, socially differentiated vulnerable populations, remain key concerns as Asian cities simultaneously tackle challenges of sustainable development and equitable climate action.
By 2050, urban areas are expected to add 2.5 billion people, 90% of whom will be in Asia and Africa (UNDESA, 2018). Critically, this urban population increase will be concentrated in India, China and Nigeria, with India and China adding 416 million and 255 million urban dwellers, respectively, between 2018 and 2050 (UNDESA, 2018).
Asia is home to 54% of the world’s urban population, and by 2050, 64% of Asia’s 3.3 billion people will be living in cities. Asia is also home to the world’s largest urban agglomerations: Tokyo (37 million inhabitants), New Delhi (29 million) and Shanghai (26 million) are the top three with Cairo, Mumbai, Beijing and Dhaka home to nearly 20 million people each (UNDESA, 2018). By 2028, New Delhi is projected to become the most populous city in the world. In certain parts of Asia (e.g., some cities in Japan and the Republic of Korea), a steep decline in urban population is projected, mainly due to declining birth rates (Hori et al., 2020). Within Asia, rates of urbanisation differ sub-regionally. Eastern Asia has seen the most rapid urban growth with the percentage of urban population having more than tripled from 18 to 60% between 1950 and 2015, while rates of urbanisation have decreased in West Asia and remained steady in Central Asia (UNDESA, 2018).
Asian cities are seeing growing income inequality, with rural poverty being replaced by urban poverty (ADB, 2013). Regional studies show high and growing inequality within Indian and Chinese urban areas and decreasing rural–urban income gaps in Thailand and Vietnam (Baker and Gadgil, 2017; Imai and Malaeb, 2018). Critically, East Asia and the Asia–Pacific in general continue to house the world’s largest population of slum dwellers at 250 million, with most of them in China, Indonesia and the Philippines, and the highest rates of urban poverty in Papua New Guinea, Vanuatu, Indonesia and the Lao PDR (McIlreavy, 2015; Baker and Gadgil, 2017). A lot of urbanisation, especially in South Asia, is also ‘hidden’ due to poor, competing definitions of what is ‘urban’ and limited data (Ellis and Roberts, 2016).
In Asian cities, climatic hazards such as changes in precipitation and, during the Asian monsoon, SLR, cyclones, flooding, dust storms, heatwaves and permafrost thawing (Byers et al., 2018; Hoegh-Guldberg et al., 2018; Rogelj et al., 2018; Shiklomanov, 2019), as well as non-climatic vulnerabilities such as non-climatic hazards (e.g., seismic hazards), inadequate infrastructure and services, unplanned urbanisation, socioeconomic inequalities and existing adaptation deficits (Johnson et al., 2013; Araos et al., 2016; de Leon and Pittock, 2017; Meerow, 2017; Dulal, 2019) interact to shape overall urban risk (Shaw et al., 2016a; Rumbach and Shirgaokar, 2017; Dodman et al., 2019). Caught at the intersection of high exposure, socioeconomic vulnerability and low adaptive capacities, informal settlements in urban and peri-urban areas are particularly at risk (robust evidence, high agreement ) (Meerow, 2017; Rumbach and Shirgaokar, 2017; Byers et al., 2018).
Of the multi-hazard global average annual loss (AAL)4 of 293 billion USD, 170 billion USD (58%) is in the Asia Pacific region (UNISDR, 2017). Of the top ten highest AALs associated with multi-hazards, six are in Asia (Japan, China, Republic of Korea, India, the Philippines and Taiwan, Province of China) (UNISDR, 2017). As per Gu et al. (2015), 56% of cities with populations greater than 300,000 in 2014 are exposed to at least one of the six physical hazards (cyclones, floods, droughts, earthquakes, landslides and volcanic eruptions). Cities in areas highly exposed and vulnerable to multiple hazards were also the ones that grew rapidly in population between 1950 and 2014, implying greater infrastructural investments in climate-sensitive areas. Among 27 cities highly exposed to multiple disasters, 13 cities had a population of 1 million or more in 2014. Among them were three megacities, Tokyo (Japan), Osaka (Japan) and Manila (the Philippines), with more than 10 million inhabitants exposed to three or more hazards. Seven other cities with 1 million inhabitants or more in Asia were at high risk of three or more types of disaster. Manila is highly vulnerable to economic losses and disaster-related mortality from all six types of disasters. Moscow (Russia) is the only megacity not exposed to the risk of any of the six types of physical hazards analysed (cyclones, floods, droughts, earthquakes, landslides and volcano eruptions). Of the eight megacities most vulnerable to disaster-related mortality, seven–Tokyo, Osaka, Karachi, Kolkata, Manila, Tianjin and Jakarta, totalling 143 million people–are in Asia (Gu et al., 2015).
Urbanisation and climate change interact to drive an urban heat island (UHI) effect across Asian cities (Hauck et al., 2016; Chapman et al., 2017; also see Figure 6.4 in Chapter 6). Three regions which are expected to see higher maximum wet-bulb temperature than global averages are southwest Asia around the Persian Gulf and Red Sea, South Asia in the Indus and Ganges river valleys, and eastern China (Im et al., 2017; Perkins-Kirkpatrick et al., 2020).
Impacts of heatwaves at 1.5°C and 2°C in cities are substantially larger than under the present climate (Hoegh-Guldberg et al., 2018). In South Asia particularly, more intense heatwaves of longer durations and occurring at a higher frequency are projected with medium confidence over India (Murari et al., 2015) and Pakistan (IPCC AR6, WGI, Table 11.5; Ali et al., 2018; Nasim et al., 2018; Ali et al., 2020; IPCC, 2021). At the city level, these projections could translate into significant impacts: at 1.5°C, on average, every year Kolkata will experience heat equivalent to the 2015 record heatwaves; Karachi about once every 3.6 years; and under 2°C warming, both regions could expect such heat annually (Matthews et al., 2017). In Pakistan, Hyderabad is likely to be the hottest city by 2100 with the highest average temperature reaching 29.9°C (RCP4.5) to 32°C (RCP8.5) followed by Jacobabad, Bahawalnagar and Bahawalpur cities (Ali et al., 2020). The frequency of heatwave days (HWF) will increase by 22.8, 22.3 and 26.5 d yr –1 in northern, eastern and western Japan, respectively, with megacities such as Tokyo, Osaka and Nagoya seeing large increases in HWF and related deaths (Nakano et al., 2013).
In China’s urban agglomerations, an increase in the global warming from 1.5°C to 2°C is likely to exacerbate the intensity of extreme maximum temperature 4.1 times (Yu et al., 2018d). From 1995 to 2014 China’s urban agglomerations (Beijing–Tianjin–Hebei, Yangtze River Delta, Middle Yangtze River, Chongqing–Chengdu and Pearl River Delta) experienced no more than three heat danger d yr –1, which is projected to increase to 3–13 d by 2041–2060 and 8–67 d by 2081–2100 under high-emissions shared socioeconomic pathways SSP3-7.0 and SSP5-8.5, resulting in approximately 260 million people (19% of the total population of China) and 310 million people (39% of the total population), respectively, facing more than three heat-danger days annually (Zhang et al., 2021). This projected risk exposure is reduced under low-emissions pathways (SSP1-2.6 and SSP2-4.5), where annual heat-danger days will remain similar to current levels or increase slightly (Zhang et al., 2021).
Critically, these projections of higher temperatures will have a significant impact on heat-related morbidity and mortality, labour productivity, mental health, and health and well-being outcomes across all sub-regions of Asia (medium evidence, high confidence) (Pal and Eltahir, 2016; Im et al., 2017; Arifwidodo et al., 2019; Arshad et al., 2020). In West Asia and the North China Plain especially, extreme wet-bulb temperatures are expected to approach, and possibly exceed, the physiological threshold for human adaptability (35°C) (Pal and Eltahir, 2016; Kang and Eltahir, 2018). By the end of the century, under higher projections (RCP8.5), the daily maximum wet-bulb temperature is expected to exceed the survivability threshold across most of South Asia (Im et al., 2017). City-specific studies articulate what these regional projections will mean for urban populations. For example, at 1.5°C warming, without adaptation, annual heat-related mortality in 27 major cities across China is projected to increase from 32.1 per million inhabitants annually in 1986–2005 to 48.8–67.1 per million. This number increases to 59.2–81.3 per million for 2°C warming (Wang et al., 2019a). In the Republic of Korea, deaths from heat disorders are expected to increase approximately fivefold under the RCP4.5 and 7.2-fold under RCP8.5 by 2060 compared with the current baseline value of ~23 people per summer (Kim et al., 2016a). Importantly, heat exposure is differentiated within cities: it disproportionally affects the poorest populations (Lohrey et al., 2021) and those with lesser access to green spaces (Arifwidodo and Chandrasiri, 2020).
Warming from 1.5°C to 2°C will increase extreme precipitation events across Asia especially over East and South Asia (medium evidence, high agreement ) (Zhang et al. 2018; Supari et al., 2020; Zhang et al., 2020b). In East and Central Asia, under 1.5°C warming, extreme 1- and 5-d precipitation will increase by 28 and 15% relative to 1971–2000 (Zhang et al., 2020b). In China’s urban agglomerations, an increase in global warming from 1.5°C to 2°C is likely to increase the intensity of total precipitation of very wet days 1.8 times and double maximum 5-d precipitation (Yu et al., 2018d). Extreme rainfall has direct and increasing consequences on urban flooding risk (Dasgupta et al., 2013b), which is further exacerbated by urbanisation trends that reduce permeability, divert water flow and disrupt watersheds (Chen et al., 2015b; Duan et al., 2016).
Urban extent in drylands in expected to increase from 2000 to 2030 with large expansions in West Asia, Central Asia, South Asia and China and antecedent impacts on exposure to drought and water scarcity (Güneralp et al., 2015). Urban dryland extent in West Asia will increase from 19,400 to 67,400 km 2 (Güneralp et al., 2015). In the Haihe River basin in China, the proportion of people exposed to droughts at 1.5°C (without accounting for population growth) is projected to decrease by 30.4% but increase by 74.8% at 2°C relative to people exposed in 1986–2005 (339.65 million) (Sun et al., 2017). About 411 million people living in 330 cities above 300,000 population are exposed to drought risk, which include three Asian megacities Delhi (India), Karachi (Pakistan) and Kolkata (India). Drought-related economic losses are also high in Dhaka (Bangladesh) (Pervin et al., 2020), Istanbul (Turkey), Manila (the Philippines) and Shenzhen (China), and Manila is also highly vulnerable to drought-related mortality (Gu et al., 2015).
Increasing urban drought risk will also have cascading impacts on regions from where water is imported, exacerbating drought exposure beyond urban settlements and limiting water availability in certain regions (Chuah et al., 2018; Garrick et al., 2019; Zhang et al., 2020c; Zhao et al., 2020). There is medium evidence (high agreement ) that urban water insecurity is experienced differentially based on income, risk exposure, and assets, and that urban drought and water scarcity is causing material and non-material losses and damage (Singh et al., 2021a). Importantly, in several Asian cities, flood and drought risk is expected to occur concurrently, especially in South Asia which is projected to see the largest increase in urban land exposed to both floods and droughts (25–32% increase in flood and drought risk between 2000 and 2030).
Global assessments identify Asia as the most exposed region to SLR (see Section CCP2.2.1) in terms of the number of people living in low-elevation coastal zones and the number of people exposed to flooding from 1-in-100-years storm surge events (Neumann et al., 2015; Jevrejeva et al., 2016; Kulp and Strauss, 2019; Abadie et al., 2020; Haasnoot, 2021). Twelve of the top 20 countries exposed to SLR and associated flood events are in Asia, and of these, China, India, Bangladesh, Indonesia and Vietnam are estimated to have the highest total coastal population exposure (Neumann et al., 2015; Edmonds et al., 2020). Critically, regardless of the emissions scenario, 70% of the global population exposed to SLR and land subsidence are in eight Asian countries: China, Bangladesh, India, Vietnam, Indonesia, Thailand, the Philippines and Japan (Kulp and Strauss, 2019). This is particularly worrisome since in highly populated low-lying coastal cities across Asia, it is estimated that land subsidence could be as influential as climate-induced SLR over the 21st century (Cao et al., 2021; Nicholls et al., 2021). In East Asia and the Asia–Pacific in general (expected to see 0.2–0.5 m SLR), without adaptation, 1 million people (range of 0.3–2.2 million) are projected to be affected by submergence under RCP8.5 by 2095. Limiting warming will reduce this risk, and under RCP4.5, these numbers of people at risk will be reached by 2140. However, continuing on RCP8.5 increases risk exposure to 7 million (estimated range of 2–24 million people) (Haasnoot, 2021). Notably, assuming present-day population and adaptation (in the form of existing protection standards), East and South Asia already have a large number of people at risk of a 1-in-100-years flooding event (63 million) because of relatively lower flood protection (except in China and Malaysia).
These global scenarios will have significant impacts on national and subnational populations. For example, in Bangladesh, under 0.44 and 2 m mean SLR, direct inundation is estimated to drive migration of 0.73–2.1 million people by 2100 (Davis et al., 2018). Such migration will have direct development implications: for example, destination locations could see additional demands on jobs (594,000), housing (197,000) and food (783 × 109 calories) by mid-century as a result of those displaced by SLR (Davis et al., 2018).
Among the 20 largest coastal cities with the highest flood losses by 2050, 13 are in Asia 5 , with a regional concentration in South, Southeast and East Asia (Hallegatte et al., 2013). Furthermore, 9 of these cities (Guangzhou, Kolkata, Tianjin, Ho Chi Minh City, Jakarta, Zhanjiang, Bangkok, Xiamen, Nagoya) also have an additional risk of subsidence due to SLR and flooding (Hallegatte et al., 2013). Guangzhou, China, is estimated to be the most economically vulnerable city in the world to SLR by 2050, with estimated losses of 254 million USD yr –1 under 0.2 m SLR (Jevrejeva et al., 2016). With a 2°C warming, Guangzhou is expected to see SLR of 0.34 m; under 5°C warming, this number would rise to 1.93 m. A more recent estimate calculates expected damage in Guangzhou due to SLR under RCP8.5 to reach 331 billion USD by 2050 and 420 billion USD under the high-end scenario with figures doubling by 2070. By 2100, expected damage could reach 1.4 trillion USD under RCP8.5 and 1.8 trillion USD under the high-end scenario. Similarly, in Mumbai (India) SLR damages amount to US$ 112–162 billion by 2050 and could increase by a factor of 2.8–2.9 by 2070 (Abadie et al., 2020). In coastal cities such as Bangkok and Ho Chi Minh City, projected land subsidence rates, mainly due to excessive groundwater extraction, are comparable to, or exceed, expected rates of SLR, resulting in an additional 0.2 m SLR by 2025 (Jevrejeva et al., 2016). In Shanghai, current annual damage by coastal inundation is estimated at 0.03% of local GDP; under RCP4.5, this increases to 0.8% by 2100 (uncertainty range of 0.4–1.4%) and is further exacerbated by land subsidence and socioeconomic development (Du et al., 2020). It is important to note that these projections assume (a) no adaptation and (b) that damage repairs are undertaken and completed annually. Given these assumptions, while these estimates communicate the scale of projected impacts, they are indicators of possible damages in the absence of adaptation and not actual projections.
The SLR affects economic growth, its drivers and welfare outcomes (Hallegatte, 2012; Pycroft et al., 2016; Lee and Asuncion, 2020) through (a) permanent loss of land and natural capital, (b) loss of infrastructure and physical capital, (c) loss of social capital and migration, (d) temporary floods, food insecurity and loss of livelihoods and (e) added expenditure for coastal protection. Without adaptation, direct damage to the GDP by 2080 due to SLR would be highest in Asia (robust evidence, medium agreement ), with China losing between 64.2 billion USD (under A1B of 2.4°C by the 2050s and 3.8°C by the 2090s at 0.47 m), 95.8 billion USD (under the RAHM scenario of 1.4 m SLR by 2100 at 1.12 m) and 118.4 billion USD (at a high SLR of 2 m by 2100 at 1.75 m) in direct damages, and an additional 5.7, 4.5 and 4.5 billion USD, respectively, due to migration (Pycroft et al., 2016). Closely after China will be India, the Republic of Korea, Japan, Indonesia and Russia. Overall, Asia can experience direct losses of about 167.6 billion USD (at 0.47 m), 272.3 billion USD (at 1.12 m) or 338.1 billion USD (at 1.75 m), and an additional 8.5, 24 or 15 billion USD at the respective SLR projections, due to migration 6 .
Globally, there is high confidence that the proportion of intense tropical cyclones is expected to increase despite the total number of tropical cyclones being expected to decrease or remain unchanged (Arias et al., 2021), especially in Southeast and East Asia (Knutson et al., 2015; Yamamoto et al., 2021). Historical trends from South Asia indicate that more lives are lost due to storm surge levels than the intensity of the cyclone (Niggol and Bakkensen, 2017). The number of people exposed to 1-in-100-years storm surge events is highest in Asia. China, India, Bangladesh, Indonesia and Vietnam have the highest numbers of coastal populations exposed (Neumann et al., 2015) with Guangzhou, Mumbai, Shenzen, Tianjin, Ho Chi Minh City, Kolkata and Jakarta incurring losses of 1520 million USD due to coastal flooding in 2005 alone (Dulal, 2019), although Jakarta is exposed to monsoonal storm surge. It is projected that by 2050, without adaptation, the annual losses incurred in these cities will increase to approximately 32 billion USD (Dulal, 2019).
Globally, six of the top ten countries/places with the highest AAL associated with tropical cyclones are in Asia (Japan, Republic of Korea, the Philippines, China, Taiwan, Province of China, and India) (Mori et al., 2021a). The AAL associated with storm surge is primarily concentrated in Japan, China, Hong Kong SAR of China, and India. The AAL associated with wind and storm surge relative to the existing capital stock in the country is highest in New Caledonia, Tonga, Vanuatu, Palau, the Philippines, Fiji and the Solomon Islands, indicating less resilience. For example, in Ise Bay, Japan, the current storm surges are estimated to lead to property and business damage of approximately 100.04 billion JPY with current adaptation (protective sea wall), but this can more than double to 236.49 billion JPY under climate-change-induced increases in storm surge intensity (Jiang et al., 2016).
Over one-third of Asian cities and about 932 million urban dwellers live in areas with high risk of flooding (Gu et al., 2015). Of 437 cities at low risk of flood exposure but highly vulnerable to flood-related economic losses, approximately half are in Asia (Gu et al., 2015).
Globally, China and India have the highest AALs associated with riverine floods, with a magnitude of 13 and 6 billion USD, respectively. Other countries from Asia among the top ten of absolute AALs are Japan, Bangladesh and Thailand. There is an increased flood risk for habitations on the deltas influenced by both riverine and coastal drivers of flooding (Szabo et al., 2016a), globally exposing 9.3% more people annually to riverine flooding than otherwise estimated without the compounded influence (Eilander et al., 2020). Simultaneously, SLR and subsidence are also expected to increase the risk due to frequent flood events for these delta regions than the longer-return periods otherwise associated with SLR (Yin et al., 2020).
In Northern Eurasia, observed and projected climate-change impacts are especially pronounced. On land, the presence of permafrost, which occupies substantial areas of eastern Russia, Mongolia and mountain regions of China, creates specific challenges for economic development and human activities. By 2050, it is likely that 69% of fundamental human infrastructure in the Pan Arctic will be at risk (RCP 4.5 scenario)(medium confidence), including more than 1200 settlements (Hjort et al., 2018). The majority of the population and the absolute majority (85%) of large settlements on permafrost are located in Russia, and 44% of those are expected to be profoundly affected by permafrost thaw by 2050 (Streletskiy et al., 2019; Ramage et al., 2021). Under RCP8.5, the climate-induced decrease of bearing capacity and, in regions with ice-rich permafrost, thaw subsidence, is projected to affect 54% of all residential buildings on permafrost with a combined worth of 20.7 billion USD; 20% of commercial and industrial structures and 19% in critical infrastructure with a total worth of 84.4 billion USD (Streletskiy, 2019). Transport infrastructure in Russia and China are impacted by thaw subsidence and, to a lesser degree, from frost heave, which add significant operational costs and limit accessibility to remote settlements (Porfiriev et al., 2019; Ni et al., 2021).
Especially in Russia, significant populations and fixed infrastructure assets are located in urban centres on permafrost that is degrading significantly. Two major risks associated with permafrost degradation are loss of permafrost bearing capacity and ground subsidence (Streletskiy et al., 2015). The former determines the ability to support foundations of buildings and structures and is a vital characteristic of sustainability of the economic centres, while the latter impacts the ability of critical infrastructure (roads, railroads) to provide transportation and support accessibility of remote populations and economic centres on permafrost. The proximity of some settlements to the coasts or areas with uneven topography may further increase risks associated with permafrost degradation as ice-rich coasts characterised by high rates of coastal erosion, while settlements located on slopes may experience higher rates of mass wasting processes.
Changes in climate have resulted in permafrost warming and increased thaw depth in undisturbed locations (Biskaborn et al., 2019), but in built up areas these transformations have been exacerbated by human activities (Grebenets et al., 2012). Norilsk, the largest city built on permafrost above the Arctic Circle (Shiklomanov et al., 2017b), was found to have one of the highest trends of near-surface permafrost warming (Streletskiy et al., 2012). Anomalous high temperatures and earlier snowmelt in 2020 may have contributed to oil storage collapse and the resulting spill of 20,000 tons of diesel fuel in Norilsk area (Rajendan et al., 2021). The ability of foundations to support structures has decreased by 10–40% relative to the 1960s in the majority of settlements on permafrost in Russia (Streletskiy et al., 2012) and is expected to further decrease by 20–33% by 2050–2059 relative to 2006–2015 (Streletskiy et al., 2019).
South Asia and Africa bear the highest losses from unreliable infrastructure, and climate change will increase these losses due to hazards and necessitate additional infrastructure investments to address new risks (Hallegatte et al., 2019; Lu, 2019)7 . Specifically, power generation and transport infrastructure incur losses of 30 billion USD a year on average from hazards (about 15 billion USD each), with low- and middle-income countries shouldering about 18 billion USD of the total amount (Koks et al., 2019; Nicholls et al., 2019).
Among the top 20 countries that are rapidly expanding their infrastructure stock while facing high disaster risk and low infrastructure quality, the Asian countries are Lao PDR, the Philippines, Bangladesh, Cambodia, Kyrgyzstan, Bhutan and Vietnam. (UNISDR, 2017; WEF, 2018). The losses are due to direct damage to infrastructure, disruption in services and affected supply chains (Hallegatte et al., 2019). East Asia and the Pacific and South Asia have the highest adaptation deficits in coastal protection with 75 billion USD in the former and 49 billion USD in the latter (Nicholls et al., 2019). If overall damages are minimised, low- and middle-income countries may need to invest 0.1–0.5% of their GDP annually up to 2030 for protection against both coastal and river floods, varying based on level of acceptable risks, construction costs, urbanisation and climate uncertainties 8 .
Across Asia, infrastructure impacts are mixed: net importers, such as China and India, will see GDP gains, while extreme examples include Russia, a net exporter, which could see steep declines in fossil fuel production (Mercure et al., 2018). In low- and middle-income countries globally, disruption in power supply can impact firms directly (up to 120 billion USD yr –1), with coping costs (up to 65 billion USD yr –1) and other indirect impacts. Similarly, for households, the direct impact and cost of coping could be between 2.3 and 190 billion USD yr –1. Although all power outage is not due to natural hazards, there is a significant number that is attributed to disasters. Besides, outages caused by natural hazards tend to be longer and geographically larger than other causes (Hallegatte et al., 2019).
A review of urban adaptation in South, East and Central Asia found examples of 180 adaptation activities across 74 cities (Dulal, 2019). Most adaptation actions in Asia are in the initial stages (Araos et al., 2016) with 57% focused on preparatory actions, such as capacity building and vulnerability assessment, and 43% focused on implemented adaptation (see also SM10.4). Most adaptation actions were focused on disaster risk management (Dulal, 2019), although the proportion of climate finance spent on disaster preparedness is not very high (as Georgeson et al., 2016, show in the megacities of Beijing, Mumbai and Jakarta). Although key port cities across Asia are at high risk of climate impacts, it is estimated that adaptation interventions constitute only a small proportion of cities’ climate efforts (Blok and Tschötschel, 2015). Figure 10.8 shows risks and key adaptation options in select cities across Asia.
Figure 10.8 | Risks and key adaptation options in select cities across Asia. Cities were chosen to ensure coverage of different sub-regions of Asia, represent different risk profiles, different city sizes (based on current population and projected growth) and reported progress on different adaptation strategies (infrastructural, institutional, ecosystem based and behavioural). There is a full line of sight in SM10.4.
Critically, most urban adaptation in South, East and Central Asia is reactive in nature (Dulal, 2019; Singh et al., 2021b), raising questions on preparedness, proactive building of adaptive capacities and whether present actions can lock certain cities or sectors into maladaptive pathways (Friend et al., 2014; Gajjar et al., 2018; Salim et al., 2019; Chi et al., 2020). China, India, Thailand and the Republic of Korea record the most number of urban adaptation initiatives, driven mainly by supportive government policies (Lee and Painter, 2015; Dulal, 2019). The number of actors working on urban adaptation is growing: in addition to national governments and local municipalities, civil society, private-sector actors (Shaw, 2019) and transnational municipal networks (Fünfgeld, 2015) are emerging as important for knowledge brokering, capacity building and financing urban adaptation (Karanth and Archer, 2014; Chu et al., 2017; Bazaz et al., 2018).
Adaptation options include: (a) infrastructural measures such as building flood protection measures and sea walls, and climate-resilient highways and power infrastructure (Shaw et al., 2016b; Ho et al., 2017); (b) sustainable land-use planning through zoning, developing building codes (Knowlton et al., 2014; Nahiduzzaman et al., 2015; Rahman et al., 2016; Ahmed et al., 2019b); (c) ecosystem-based adaptation measures such as protecting urban green spaces, improving permeability, mangrove restoration in coastal cities, etc. (Brink et al., 2016; Fink, 2016; Yu et al., 2018d); (d) relocation and migration out of risk-prone areas (McLeman, 2019; Hauer et al., 2020; Maharjan et al., 2020); and (e) disaster management and contingency planning such as through Early warning systems (EWS), improved awareness and preparedness measures (Shaw et al., 2016a). Asian cities are also focusing on institutional adaptation measures which cut across the five categories mentioned above such as through building capacity and local networks (Anguelovski et al., 2014; Friend et al., 2014; Knowlton et al., 2014), improving awareness (Knowlton et al., 2014), and putting local research and monitoring mechanisms in place (Lee and Painter, 2015) to enable adaptation. Figure 10.9 shows the effectiveness of select adaptation options in cities across Asia.
Figure 10.9 | Effectiveness of select adaptation options in cities across Asia. Effectiveness is assessed based on the option’s ability to reduce risk as reported in the literature.
The challenge of adapting infrastructure to climate change across Asia is twofold: there are significant infrastructure deficiencies, especially in low-income countries, and key infrastructures are at high risk due to climate change (Hallegatte et al., 2019; Lu, 2019). Infrastructural adaptation options in cities attempt to enable networked energy, water, waste and transportation systems to prepare for, and deal with, climate risks better (Meerow, 2017) through interventions such as improved highways and power plants, climate-resilient housing, improved water infrastructure and so forth (ADB, 2014).
Infrastructural measures alone are seldom effective in building urban resilience as seen in the examples of the 2011 floods in Bangkok and the 2005 typhoon in Manila (Duy et al., 2019), or projected estimates by Pervin et al. (2020) who found that structural interventions in existing drainage systems reduce flooding risk by 7–19% in Sylhet (Bangladesh) and Bharatpur (Nepal); however, without proper solid waste management, areas under flood risk could increase to 18.5% in Sylhet and 7.6% in Bharatpur in five years, rendering the infrastructural interventions ineffective over time. While in some cities it is estimated that infrastructural adaptation through ‘hard’ flood protection strategies (e.g., storm surge barriers and floodwalls) is more effective than institutional or ecosystem-based adaptation by 2100, for example, Shanghai. A hybrid approach where hard strategies protect from flood risk, and soft strategies reduce residual risk from hard strategies, is suggested (Du et al., 2020). In Japan, without adaptation, estimated damage costs of floods (caused by tropical cyclones and altered precipitation) by 2081–2100 under RCP2.6 will be 28% higher (compared with 1981–2000), rising to 57% higher under RCP8.5 (Yamamoto et al., 2021). With a combination of adaptation measures (such as land-use control, piloti building and flood control measures), estimated damage costs can be reduced even below the 1981–2000 levels, and with a combination of mitigation and these adaptation measures, an estimated 69% reduction in flood damage costs are expected–demonstrating the importance of concerted and immediate climate action in reducing damage.
Infrastructural interventions can sometimes be maladaptive when assessed over longer time periods: for example, the Mumbai Coastal Road (MCR) project aimed at reducing flood risk and protecting against SLR will potentially cause damages to intertidal fauna and flora and local fishing livelihoods (Senapati and Gupta, 2017); and Jakarta’s Great Garuda project aimed at reducing flood risk is expected to increase flood risk for the poorest urban dwellers (Salim et al., 2019).
Land use in cities impacts resource use (e.g., water, energy), risk (a function of population density, service provision and hazard exposure) and adaptive capacity, all of which influence the efficacy of urban adaptation (de Coninck et al., 2018). Locally suited land-use planning and regulation (such as appropriate zoning or building codes and safeguarding land rights) can have adaptation co-benefits (Mitchell et al., 2015; Dhar and Khirfan, 2016): for example, strict building regulations can protect urban wetlands and associated ecosystem services (Jiang et al., 2015); appropriate land zoning can safeguard green spaces, ensure improvements in permeability and obviate new development in risk-prone locations (Duy et al., 2019); and ensuring tenurial security or regularising informal settlements can incentivise improvements to housing quality, thereby alleviating vulnerability of the most marginal people (Mitchell et al., 2015).
Land tenure arrangements strongly shape urban dwellers’ vulnerability and their adaptive capacities (Roy et al., 2013; Michael et al., 2018). For example, in Khulna (Bangladesh), Roy et al. (2013) found significant differences between the adaptive strategies of homeowners and renters in low-income settlements, a finding echoed in Bangalore (India) (Deshpande et al., 2018) and Phnom Penh (Cambodia) (Mitchell et al., 2015). In Riyadh (Saudi Arabia), land-based adaptation strategies include land zoning to control population and building density, demarcating environmental protection zones, and sub-urbanisation (Nahiduzzaman et al., 2015; Rahman et al., 2016). In many Asian cities, land subsidence control can serve as an adaptation strategy since it is estimated to significantly reduce relative SLR (high confidence). This has an important implication in that subsidence control would be a good and complementary measure to climate mitigation and climate adaptation in many coastal urban settings in Asia (Cao et al., 2021; Nicholls et al., 2021). Urban land-use planning, if used proactively, can incentivise adaptation–mitigation synergies and obviate unintended negative consequences of urbanisation as Xu et al. (2019) have shown in Xiamen.
The literature on urban ecosystem-based adaptation (EbA)9 , especially across Asia, has grown significantly since AR5 (Demuzere and al., 2014; Yao et al., 2015; Brink et al., 2016; Bazaz et al., 2018; de Coninck et al., 2018; Ren, 2018). This growing literature reflects the wide recognition that infrastructural adaptation can often have ecological and social trade-offs (Palmer et al., 2015) and need to be complemented by ecosystem-based actions to manage risk more effectively (Du et al., 2020), build adaptive capacity, and in some cases, meet mitigation and SDGs (Huang et al., 2020).
Illustrative examples of EbA in Asian cities include sponge cities in China for sustainable water management, flood mitigation and minimising heatwave impact (Jiang et al., 2018; Yu et al., 2018d; Wang et al., 2019a; Zhanqiang et al., 2019), Singapore’s Active, Beautiful, Clean Waters (ABC Waters) Programme, which uses bio-engineering approaches to protect river channels and prevent localised flooding, improve water quality and create community spaces, and Dhaka’s green roofs and urban agriculture (Zinia and McShane, 2018).
The EbA approaches to manage floods, capture and store rainwater, restore urban lakes and rivers, and reduce surface runoff often blend infrastructural and ecosystem-based approaches. For example, in Tokyo, stormwater management is done by sophisticated underground infrastructure and an artificial infiltration stormwater system (Saraswat, 2016; Mishra et al., 2019 ). China’s Sponge City Programme aims to reduce the impacts of flooding through low-impact development measures, urban greenery and drainage infrastructure, such that 80% of urban areas reuse 70% of rainwater by 2020, which would help ensure the resilience of these cities to floods (Li et al., 2016b; Stip et al., 2019).
Case studies on urban EbA also raise equity concerns (medium evidence, medium agreement ) such as interventions biased towards suburban areas in Haizhu District, Guangzhou (China) (Zhu et al., 2019); inadequate consideration of low-income, vulnerable populations (Blok and Tschötschel, 2015; Meerow, 2017; Mabon and Shih, 2021); and low familiarity with interventions such as artificial wetlands, water retention ponds as well as green façades and walls can restrict inclusiveness (Zinia and McShane, 2018). Furthermore, urban EbA is constrained by a range of factors such as inadequate institutional structures and processes for connecting different remits and knowledge systems along with trade-offs in land use for different purposes (Mabon and Shih, 2021; Singh et al., 2021b).
The EbA interventions are not uniform across Asian cities: in a global study on urban EbA, Brink et al. (2016) found that Eastern Asia, India and Israel report most EbA interventions and that there is variable and limited evidence on effectiveness and scalability (SM10.5). Using a risk framing (i.e., the extent to which an option reduces risk), urban EbA options in Asian cities score as being ‘low to medium’ effective (see SM10.5); however, when the assessment is expanded to include the ecosystem benefits, economic impacts and human well-being co-benefits of EbA, effectiveness increases. Figure 10.10 shows evidence of the effectiveness of EbA.
Figure 10.10 | Evidence of the effectiveness of ecosystem-based adaptation (EbA) using examples of four commonly used EbA options10 . Effectiveness is assessed qualitatively based on the evidence (for a full line of sight see SM10.5) and is examined through four framings: potential to reduce risk (e.g., reduced exposure to hazard means to reduce risk); benefits to ecosystems (through improved ecosystem health and high biodiversity); economic benefits (e.g., improved incomes, fewer man-days lost, better livelihoods); and human well-being outcomes (e.g., health, quality of life, etc.). The darker shading signifies high effectiveness and the lightest shade signifies low effectiveness of an EbA option (i.e., the option scores low on the indicator).
1 10 Assessing the effectiveness of adaptation actions is challenging because of the lack of a clear goal that signifies effective adaptation, varied conceptual framings and metrics used to assess effectiveness, and low empirical evidence on the effectiveness of implemented adaptation actions (Owen, 2020; Singh et al., 2021a).
For example, urban agriculture is identified as offering multiple benefits such as mitigating emissions associated with food transportation from rural to urban areas, improving food and nutritional security, strengthening local livelihoods and economic development, improved microclimate, soil conservation, improved water and nutrient recycling, and efficient water management (Padgham and Dietrich, 2015; Patil et al., 2019). However, it can potentially undermine ecosystem services through land-use changes, water overextraction or applying chemical fertilisers (Ackerman et al., 2014), exposure of smallholders to volatile markets and crops that are not consumed by farming households themselves (thus undermining food security) or increasing the work burdens on women, as well as health externalities (e.g. through use of untreated wastewater, or rearing poultry and livestock in unsanitary conditions). There remain gaps in understanding the differential impacts of urban agriculture at different scales as well as its effectiveness in improving adaptive capacity at scale.
There is medium evidence with high agreement that climatic risks are exacerbating internal and international migration across Asia (see Box 10.2; IDMC, 2019; Maharjan et al., 2020). In coastal cities, formal ‘retreat’ measures, such as forced displacement and planned relocation (Oppenheimer et al., 2019), are commonly considered ‘last resort’ adaptation strategies once other infrastructural and ecosystem-based protect-and-accommodate strategies are exhausted (CCP2.3) (Haasnoot et al., 2019). In contrast, migration (which can take various forms from seasonal, temporary mobility to circular or permanent movement) is a regular feature across Asian urban settlements (Box 10.2, CCB MIGRATE, Maharjan et al., 2020).
There is robust evidence (medium agreement ) that across Asia, migration (and increasingly planned relocation) will continue to be a key risk management strategy, especially in low-lying flood-prone cities (e.g., in Southeast and South Asia) and across drylands (e.g., in South and Central Asia) (Davis et al., 2018; Ajibade, 2019; Lincke and Hinkel, 2021). While there is insufficient evidence to project migration numbers under different warming levels, it is well established that migration as an adaptation strategy is not equally available to all (Ayeb-Karlsson, 2020), and climatic risks might reduce vulnerable populations’ ability to move due to loss of assets, thus reinforcing existing inequalities and differential adaptive capacities (Blondin, 2019; Zickgraf, 2019; Singh and Basu, 2020; Cundill et al., 2021; Gavonel et al., 2021).
There is medium evidence (low agreement ) about the effectiveness of migration and planned relocation in reducing risk exposure. Evidence on climate-driven internal migration shows that moving has mixed outcomes on risk reduction and adaptive capacity. On one hand, migration can improve adaptive capacity by increasing incomes and remittances as well as diversifying livelihoods (Maharjan et al., 2020); on the other, migration can expose migrants to new risks. For example, in Bangalore (India), migrants often face high exposure to localised flooding, insecure and unsafe livelihoods, and social exclusion, which collectively shape their vulnerability (Michael et al., 2018; Singh and Basu, 2020). In greater Manila (the Philippines) and Chennai (India), planned relocations to reduce disaster risk have often exacerbated vulnerability, due to relocation sites being in environmentally sensitive areas, inadequate livelihood opportunities and exposure to new risks (Meerow, 2017; Ajibade, 2019; Jain et al., 2021).
There is rich case-based evidence across Asia on urban adaptation to extreme events with relatively more evidence on rapid-onset events such as cyclones and flooding than slow-onset disasters such as drought (see Box 10.6; Ray and Shaw, 2019 ; UNESCAP, 2019; Singh et al., 2021a). Overall, there has been a growing emphasis on ‘build back better’ interventions (Mannakkara and Wilkinson, 2013; Hallegatte et al., 2018) that approach disaster management holistically through infrastructural solutions such as climate-resilient housing or sea walls and soft approaches such as strengthening livelihoods, developing EWS11, 10 increasing awareness about disaster risks and impacts, and building local capacities to deal with them (Bhowmik et al., 2021). Notably, urban disaster management is effective when land-use planning processes, including greenfield development, zoning and building codes, and urban redevelopment, are leveraged to reduce and/or obviate risk, thereby averting potential maladaptation (Kuhl et al., 2021).
There is relatively lower empirical evidence on how microenterprises and businesses are adapting to increased risk, but recent examples in Mumbai, India (Schaer and Pantakar, 2018), and Kratie, Cambodia (Ngin et al., 2020), suggest that businesses primarily adopt temporary and reactive responses rather than long-term, anticipatory adaptation measures.
A review of innovative DRR approaches notes the use of geographic information system (GIS) and drone-based technologies for mapping risk exposure and impacts, mobile-based payments for post-disaster compensation, and transnational initiatives and learning networks to promote urban resilience (Izumi et al., 2019). Furthermore, technology-based innovations, such as using big data (Yu et al., 2018b), improved warnings through mobile phones or mobilising relief through social media (Carley et al., 2016), are proving effective for disaster preparedness, relief and recovery. Community-based DRR is consistently ranked as most effective for its role in transforming DRR towards being more context relevant and inclusive. Ecosystem-based DRR (EbDRR) is also gaining prominence and includes strategies such as mangrove plantation and rejuvenation in vulnerable coastal areas. Nature-based solutions for flood protection and reducing drought incidence have emerged as an alternative to costlier ‘hard’ infrastructure (UN-Water, 2018; Zevenbergen et al., 2018; Rozenberg and Fay, 2019). Some cities are also reporting adaptation to heat risk. For example, Ahmedabad (India) has pioneered preparedness for extreme temperatures and heatwaves by developing annual Heat Action Plans, building regulations to minimise trapping heat, advisories about managing heat stress and instituting a cool-roofs policy (Ahmedabad Municipal, 2018).
Financing, regulations and institutional processes play a significant role in incentivising DRR and resilience in large-scale, city-level built infrastructure by the private sector and other actors. Currently there are gaps in these mechanisms, leading to infrastructure development in disaster-prone areas, increasing exposure to people, property, economy and systems (Jain, 2013). Both firms and governments need to take disaster risks into consideration in supply-chain management to avoid disruptions and subsequent negative effects (Abe and Ye, 2013). There are several institutional challenges faced during DRR and CCA implementation including overlapping efforts and inefficient use of scarce resources due to inappropriate funding mechanisms, a lack of coordination and collaboration, a lack of implementation and mainstreaming, scale mismatches, poor governance, the social–political–cultural structure, competing actors and institutions, and lack of information, communication, knowledge sharing, and community involvement, as well as policy gaps (Seidler et al., 2018; Islam et al., 2020).
There is growing empirical evidence of conditions enabling and constraining urban adaptation (Table 10.3) with relatively more literature from South, Southeast and East Asia. Governance and capacity-related deficits are repeatedly identified as significant barriers to urban adaptation (robust evidence, high agreement ) and interact with financial and informational constraints to mediate adaptation action.
Table 10.3 | Barriers and enablers to climate adaptation across Asian cities
Indicator | As an enabler | As a barrier |
Governance and planning | National policy directives to adapt: for example, strong national climate commitments in China, India and Thailand (Dulal, 2019); and dedicated public–private councils on climate change in Seoul, Republic of Korea (Lee and Painter, 2015) Participatory planning, co-producing solutions and engaging multiple stakeholders: for example, Surat (Anguelovski et al., 2014; Karanth and Archer, 2014; Chu et al., 2017) and Guwahati (Archer et al., 2014) in India; Bandar Lampung and Semarang in Indonesia (Archer et al., 2014); and Seoul, Republic of Korea (Lee and Painter, 2015) Devolving decision making to city governments (ADB, 2013) and strong political leadership helps to institutionalise adaptation programmes (Anguelovski et al., 2014; Friend et al., 2014; Lee and Painter, 2015): for example, in Moscow where the city mayor has spearheaded climate action (van der Heijden et al., 2019). Mainstreaming climate adaptation in city plans (UN-HABITAT and UNESCAP, 2018) | Low accountability and transparency in planning processes with inadequate spaces for public dialogue (Friend et al., 2014) and limited accountability to the most economically and politically marginalised people within cities (Garschagen and Marks, 2019) Of 180 urban adaptation interventions across Asia, 65% are reactive in nature (Dulal, 2019), thus missing opportunities for risk prevention and preparedness (Francisco and Zakaria, 2019). Lack of forward-looking, learning-oriented processes constrain adaptation with short-term development priorities often overshadowing long-term climate-action needs (Friend et al., 2014; de Leon and Pittock, 2017; Gajjar et al., 2018; Khaling et al., 2018; Garschagen and Marks, 2019; Jain et al., 2021). Fragmented governance, lack of mainstreaming between CCA and DRR (Fuhr et al., 2018; Khaling et al., 2018): for example, in Vietnam, Thailand, Indonesia (Friend et al., 2014) and greater Manila (Meerow, 2017) |
Information | Knowledge sharing through transnational municipal networks such as C40, ACCRN and A-PLAT (Fünfgeld, 2015) City-level knowledge creation and knowledge-transfer institutions (Lee and Painter, 2015) | Data gaps on projected climate risks and impacts in certain sub-regions and small settlements (Revi et al., 2014) Numerous tools for assessing vulnerability and adaptation planning (Nordgren et al., 2016) |
Technology and infrastructure | Early warning systems, climate information and modelling studies inform adaptation decision making (Reed et al., 2015; Singh et al., 2018a) | Inadequate regional downscaled data at the city scale (ADB, 2013; Khaling et al., 2018); inadequate cost–benefit analyses of different adaptation strategies (Khaling et al. 2018) |
Capacity and awareness | A focus on learning, experimentation, awareness and capacity building leads to more sustained, legitimate and inclusive adaptation (ADB, 2013; Anguelovski et al., 2014; Reed et al. (2015) . | Limited access to, and capacity to use, risk assessment tools (ADB, 2013; Shaw et al., 2016b) |
Finance | Dedicated adaptation financing (e.g., in Beijing, adaptation spending is 0.33% of the city’s GDP) (Georgeson et al., 2016); steering international and local funding to leverage adaptation benefits in urban development programmes such as in Surat (India) (Cook and Chu, 2019); mainstreaming climate adaptation into development programming to leverage developmental finance for adaptation action (Cuevas et al., 2016; Narender and Sethi, 2018) | Inadequate adaptation funding and lack of financial devolution to city governments (Fuhr et al., 2018; Garschagen and Marks, 2019) |
Climate change is increasing risks to human health in Asia by increasing exposure and vulnerability to extreme weather events such as heatwaves, flooding and drought, and air pollutants, increasing vector- and water-borne diseases, undernutrition, mental disorders and allergic diseases (high confidence). Sub-regional diversity in socioeconomic and demographic contexts (e.g., ageing, urban compared with agrarian society, increasing population compared with reduced birth rate, high income compared with low to middle income), and geographic characteristics, largely define the differential vulnerabilities and impacts in Asia (high confidence).
High temperatures affect mortality and morbidity in Asia (high confidence). In addition to all-cause mortality (Dang et al., 2016; Chen et al., 2018e), deaths related to circulatory, respiratory, diabetic (Li et al., 2014b) and infectious diseases (Ingole et al., 2015), as well as infant mortality (Son et al., 2017), are increased with high temperature (high confidence). Increased hospital admissions (Giang et al., 2014; Lin et al., 2019) and ambulance transport (Onozuka and Hagihara, 2015) coincide with increased ambient temperature (high confidence). Heatwaves are particularly detrimental to all-cause and cause-specific mortality (Chen et al., 2015a; Lee et al., 2016; Guo et al., 2017b; Yin et al., 2018). Both rural and urban populations are vulnerable to heat-related mortality (Ma et al., 2015; Chen et al., 2016a; Wang et al., 2018a). Individuals with lower degrees of education and socioeconomic status, older individuals and individuals living in communities with less green space are more susceptible to heat-related mortality (high confidence) (Yang et al., 2012a; Huang et al., 2015b; Seposo et al., 2015; Son et al., 2016; Kim and Kim, 2017 ). These heat effects have been attenuating over recent decades in East Asian countries, although the driving force behind this remains unknown (high confidence) (Chung et al., 2017c; Chung et al., 2018).
Rising ambient temperature accelerates pollutant formation reactions and may modify air-pollution-related health effects (medium confidence). Higher temperatures are associated with the increased effects of ozone on mortality (Shi et al., 2020). Climate change causes intensified droughts and greater wind erosion resulting in increased intensity and frequency of sand and dust storms (Akhtar et al., 2018). Mortality and hospital admissions for circulatory and respiratory diseases are increased after exposures to Asian dust events (high confidence) (Hashizume et al., 2020). El Niño has a major influence on weather patterns in various regions. For example, it causes dry conditions that sometimes result in forest fires and transboundary haze that increased all-cause mortality in children by 41% in Malaysia (Sahani et al., 2014).
Ambient temperature is associated with the risk of an outbreak of mosquito-borne disease in South and Southeast Asia (high confidence) (Servadio et al., 2018). Warmer climates are associated with a higher incidence of malaria (Xiang et al., 2018). Moderate rainfall also promotes malaria infection, while excessive rainfall decreases the risk of malaria (Wu et al., 2017b). El Niño intensity is positively associated with malaria incidence in a single year in India (Dhiman and Sarkar, 2017). The duration and survival rate of dengue mosquito development, mosquito density, mosquito biting activity, mosquito spatio-temporal range and distribution, and mosquito flying distance are all affected by temperature (high confidence) (Li et al., 2018b). Temperature, precipitation, humidity and air pressure are major weather factors associated with dengue fever transmission (high confidence) (Sang et al., 2014; Choi et al., 2016; Xu et al., 2017).
Climate change alters the hydrological cycle by increasing the frequency of extreme weather events such as excess precipitation, storm surges, floods and droughts (high confidence). Water-borne diseases, such as diarrhoea, leptospirosis and typhoid fever, can increase in incidence following heavy rainfall, tropical cyclones and flooding events (high confidence) (Deng et al., 2015; Levy et al., 2016; Li et al., 2018b; Matsushita et al., 2018; Zhang et al., 2019b). Droughts can cause increased concentrations of pathogens, which overwhelm water-treatment plants and contaminate surface water. A positive association between ambient temperature and bacterial diarrhoea has been reported, compared with a negative association with viral diarrhoea (Carlton et al., 2016; Wang et al., 2018c).
Asia has the highest prevalence of undernourishment in the world, which was 11.4% in 2017, representing more than 515 million people. Southeast Asia has been affected by adverse climate conditions such as floods and cyclones, with impacts on food availability and prices (FAO, 2018d). Crop destruction due to tropical cyclones can include salt damage from tides blowing inland (medium confidence) (Iizumi and Ramankutty, 2015). Sea level rises result in intrusion of saline water into the coastal area of Bangladesh and people living in this area face an increased risk of hypertension resulting from high salt consumption (Scheelbeek et al., 2016).
Weather conditions have been linked to mental health. High temperatures increase the risk of mental problems including mental disorders, depression, distress and anxiety in Vietnam (Trang et al., 2016), Hong Kong SAR of China (Chan et al., 2018) and the Republic of Korea (Lee et al., 2018d). In addition, high temperatures are reported to increase the risk of mortality from suicide in Japan, the Republic of Korea, Taiwan, Province of China (Kim et al., 2016c), India (Carleton, 2017) and China (Luan et al., 2019). Extreme weather events, such as storms, floods, hurricanes and cyclones, increase injuries and mental disorders (post-traumatic stress disorder and depressive disorders) (Rataj et al., 2016), thereby negatively affecting well-being (high confidence).
Higher temperatures and increased CO2 elevate the level of allergens such as pollen, which can result in increased allergic diseases, such as asthma and allergic rhinosinusitis. The association between variations in ambient temperature and the occurrence of asthma has been reported in several Asian countries/regions such as Japan (Yamazaki et al., 2015), the Republic of Korea (Kwon et al., 2016), China (Li et al., 2016a) and Hong Kong SAR of China (medium confidence) (Lam et al., 2016).
Climate change is associated with significantly increased mortality (high confidence). Figure 10.11 shows projected health impacts due to climate change in Asia. The global estimates of excess deaths due to malnutrition, malaria, diarrhoea and heat stress will be approximately 250,000 deaths per year in 2030–2050 under the medium-to-high emissions scenario, assuming no adaptation (World Health Organization, 2014). The impacts are expected to be greatest in South, East and Southeast Asia. Another projection showed that the change in heat-related deaths is largest in Southeast Asia, which was a 12.7% increase at the end of the century under a high-emissions scenario (Gasparrini et al., 2017). As the proportion of older individuals in the population rises, the number of years lost due to disability increases more steeply (Chung et al., 2017b). In the 2080s, the number of annual temperature-related deaths is estimated to reach twice that in the 1980s in China (Li et al., 2018c). Over a 20-year period in the mid-21st century (2041–2060), the incidence of excess heat-related mortality in 51 cities in China is estimated to reach 37,800 (95% CI: 31,300–43,500) deaths per year under RCP8.5 (Bazaz et al., 2018).
Figure 10.11 | Projected health impacts due to climate change in Asia.
Increased concentrations of fine particulate matter and ozone influenced by extreme events such as atmospheric stagnations and heatwaves are projected to result in an additional 12,100 and 8,900 deaths per year due to fine particulate matter and ozone exposure, respectively, in China in the mid-century under RCP4.5 (Hong et al., 2019a). Excess ozone-related future premature deaths is noticeable in 2030 in East Asia and India for RCP8.5 (over 95% of global excess mortality) (Silva et al., 2016).
The global estimates for increases in malaria and dengue deaths (annual estimates) are approximately 32,700 and 280 additional deaths, respectively, in 2050 under the medium-to-high emissions scenario (World Health Organization, 2014). Among these additional deaths, 9,300 and 200 deaths, respectively, are projected to occur in South Asia. The population at risk of malaria infection is estimated to increase by 134 million by 2030 in South Asia under the medium-to-high emissions scenario, considering socioeconomic development. If no actions are taken, malaria incidence in northern China is projected to increase by 69–182% by 2050 (Song et al., 2016). Another study suggested a decrease in climate suitability for malaria in northern and eastern India, southern Myanmar, southern Thailand, the Malaysia border region, Cambodia, eastern Borneo and Indonesia by 2050 (Khormi and Kumar, 2016). By contrast, climate suitability for malaria is projected to increase in the southern and southeast mainland of China and Taiwan, Province of China (Khormi and Kumar, 2016).
Dengue incidence is projected to increase to 16,000 cases per year by 2100 in Dhaka, Bangladesh, if ambient temperatures increase by 3.3°C without any adaptation measures or changes in socioeconomic conditions (Banu et al., 2014). This would represent an increase in incidence of over fortyfold compared with 2010. Higher numbers of dengue fever cases are projected to occur under RCP8.5 than RCP2.6 in China (Song et al., 2017). Compared with the average numbers in 1997–2012, the annual number of days suitable for dengue fever transmission in the 2020s, 2050s and 2080s will increase by 15, 25 and 40 d, respectively, in southern China under RCP8.5. In addition, areas in which year-round dengue fever epidemics occur will likely increase by 4500, 8800 and 20,700 km 2 in the 2020s, 2050s and 2080s, respectively, under RCP8.5 (Nahiduzzaman et al., 2015).
The global estimates for increases in deaths due to diarrhoeal disease (annual estimates) in children under 15 years in 2030 and 2050 are approximately 48,000 and 33,000 additional deaths, respectively, under the medium-to-high emissions scenario (World Health Organization, 2014). Among these additional deaths, 14,900 and 7,700 deaths, respectively, are projected to occur in South Asia. An updated projection with a pathogen-specific approach estimated 25,000 additional annual diarrhoeal deaths in Asia in 2080–2095 under the high-emissions scenario (Chua et al., 2021), while in some countries, such as Japan, net reductions in temperature-induced infectious diarrhoeal cases were estimated, because viral infections are dominant in these countries during the cold season (Onozuka et al., 2019).
South and Southeast Asia are projected to be among the highest-risk regions for reduced dietary iron intake among women of childbearing age and children under five years due to elevated CO2 concentrations (medium confidence) (Smith and Myers, 2018). The estimated number of additional deaths due to climate change in children aged under five years attributable to moderate and severe stunting in 2030 and 2050 are approximately 20,700 and 16,500, respectively, in South Asia, under the medium-to-high emissions scenario (World Health Organization, 2014). In Bangladesh, due to climate change, river salinity is projected to be increased in coastal and freshwater fishery communities leading to significant shortages of drinking water in the coastal urban areas (Dasgupta et al., 2014c).
The health co-benefits of GHG mitigation measures in energy generation have been reported to reduce disease burden. In China, the implementation of GHG policies would reduce the air-pollution-associated disease burden by 44% in 2020 under the Integrate Carbon Reduction scenario compared with the business-as-usual scenario (Liu et al., 2017b). Transition to a half-decarbonised power supply for the residential and transport sectors would prevent 55,000–69,000 deaths in 2030 compared with the business-as-usual scenario (Peng et al., 2018). A shift in travel modes from private motor vehicles to the use of mass rapid-transit lines is estimated to reduce CO2-equivalent emissions by 6% in greater Kuala Lumpur and bring important health co-benefits to the population (Kwan et al., 2017). The 25 measures developed for reducing air pollution levels in Asia and the Asia–Pacific in general would reduce CO2 emissions in 2030 by almost 20% relative to baseline projections and decrease warming by 0.3°C by 2050, which could eventually reduce heat-related excess deaths in the region (UNEP, 2019). The 25 measures include conventional emissions controls focusing on emissions that lead to the formation of fine particulate matter (PM2.5), next-stage air-quality measures for reducing emissions that lead to the formation of PM2.5 and are not yet major components of clean-air policies in many parts of the region, and measures contributing to development-priority goals with benefits for air quality. Health co-benefits outweigh mitigation costs in the Republic of Korea up to 2050 (Kim et al., 2020). Low-carbon pathways consistent with the 2°C and 1.5°C long-term climate targets defined in the Paris Agreement are associated with the largest health co-benefits when coordinated with stringent air pollution controls in Asia followed by Africa and Middle East (Rafaj et al., 2021).
Strategies to increase energy efficiency in urban environments by compact urban design and circular-economy policies can reduce GHG emissions and reap ancillary health benefits; for example, compared with conventional single-sector strategies, national CO2 emissions can be reduced by 15–36%, and the annual deaths from 25,500 to 57,500 are avoidable from air pollution reduction in 637 Chinese cities (Ramaswami et al., 2017). In a city in China, the existing mitigation policies (e.g., promotion of tertiary and high-tech industry) and the one-adaptation policy (increasing resilience) increased the co-benefits for well-being (Liu et al., 2016a).
Changing dietary patterns, particularly reducing red meat consumption and increasing fruit and vegetable consumption, contributes to reduced GHG emissions as well as reduced premature deaths. The adoption of global dietary guidelines was estimated to prevent 5.1 million deaths per year relative to the reference scenario in which the largest number of avoidable deaths occurred in East Asia and South Asia, and GHG emissions would be reduced most in East Asia (Springmann et al., 2016). In China, dietary shifts to meet national dietary reference intakes reduced the daily carbon footprint by 5–28% depending on the scenario (Song et al., 2017). In India, the optimised healthy diets (e.g., lower amounts of wheat and increased amounts of legumes) could help reduce up to 30% water use per person for irrigation and reduce diet-related GHG emissions. This would result in 6800 life-years gained per 100,000 population in 2050 (Milner et al., 2017).
Climate-change governance is characterised by a scalar/stakeholder turn which includes: (a) acknowledgement of the importance of both subnational and transnational–regional scales along with the global scale; (b) involvement of diverse stakeholders in decision-making systems; (c) reliance on bottom-up architectures of governance that are supported by the framework given by the SDGs; (d) emphasis on developmental and environmental co-benefits; (e) recognition of diverse experiences of marginalisation and social stratification, and their impacts on participation in governance-related activities; and (f) greater decentralisation and strengthening of local institutions.
In order to facilitate local adaptation, especially in a context characterised by regional diversity and spatio-temporal variation, climate-adaptive governance invites greater policy attention to institution building (formal and informal) at multiple scales and across sectors (Mubaya and Mafongoya, 2017). An incremental EbA approach underlines the advantage of drawing upon ecosystem services for reducing vulnerabilities, increasing resilience of communities to adapt to climate change, and minimising threats to social systems and human security, provided climate change remains below 2°C or, better yet, below the 1.5°C of global warming (Barkdull and Harris, 2018).
Focus on multi-level governance, both below and beyond the state level, is steadily growing (Jogesh and Dubash, 2015; Jörgensen et al., 2015; Beermann et al., 2016). Discernible diversity across political systems and sectors in Asia notwithstanding, issues relevant to multi-level climate governance includes interplay between top-down national initiatives, which stem from supranational, regional and sub-regional levels. In the case of India, national climate governance has proliferated beyond the National Action Plan on Climate Change to include State Action Plans on Climate Change of over 28 states and union territories, demonstrating graphically the shared ‘co-benefit’ in terms of creating greater space for innovation and experimentation (Jörgensen et al., 2015).
In Japan’s Climate Change Adaptation Act, enacted by the Japanese Diet in June 2018, the national government shall formulate a national action plan to promote adaptation in all sectors. This Act recommends that prefectures and municipalities designate a ‘local climate change adaptation centre’ as a local climate-change data collection and provision centre to provide more locally specific information and support for adaptation planning at the level of local municipalities. The Japanese government, in partnership with the private sector, has formulated a new comprehensive strategy, named Society 5.0, which aims at devising a number of technologically innovative solutions (Mavrodieva and Shaw, 2020).
Significantly, the co-benefit concept for international city partnerships along with comparative analysis of the challenges, capabilities and limitations of urban areas in Asia with regard to CCA governance remains under-researched (Beermann et al., 2016).
In the case of Vietnam, especially at district and community levels, where the policy capacities in hierarchical governance systems to deal with climate-change impacts are generally constrained, the value of clear legal institutions, provision of financing for implementing policies and the training opportunities for governmental staff has been well demonstrated (Phuong et al., 2018b). A key finding is that any effort to support local actors (i.e., smallholder farmers) should ensure augmentation of policy capacity through necessary investments.
In the case of China, a combination of market-based policies, emissions trading systems, a growing number of environmental non-governmental organisations (NGOs) and international networks appear to be serving as an important tool for climate governance (Ramaswami et al., 2017; Wang et al., 2017b). Public private partnership (PPP) too is receiving increasing focus, especially with regard to climate-related cost-effective and innovative infrastructure projects. In the absence of major investments in resilience, climate change may force up to 77 million people into a poverty trap by 2030 (World Bank, 2016). As seen in the case of Japan, most of the countries in Asia face the challenge of contractual allocation of risks associated with natural hazards and climate change between the public and private sectors and its long-term management in the face of uncertainty. Risk sharing, therefore, could be addressed by clear definition and allocation (World Bank, 2017). Given that in Asia, especially Singapore, China, Japan and Republic of Korea, where the water sector is a target of industrial and technology policy, PPPs could prove to be mutually beneficial. As a middle ground, key findings of a study on Indonesia (Yoseph-Paulus and Hindmarsh, 2016) underline the importance of building, sustaining and augmenting local capacity by addressing inadequacies with regard to resource endowment and capacity building, public awareness about climate change, government–community partnerships, vulnerability assessment and providing inclusive decision-making spaces to Indigenous knowledge systems and communities.
In the agriculture sector, farmers in Asia are adapting to climate change at the grassroots level (Tripathi and Mishra, 2017). A recent, comprehensive and systematic review (Shaffril et al., 2018) shows how farmers in diverse sub-regions of Asia have adopted diverse adaptation strategies through management of crops, irrigation and water, farms, finances, physical infrastructure and social activities. Much more qualitative research on farmers’ perceptions and decision-making processes about adaptation practices is needed in order to capture their location-specific priorities and get a diverse understanding of the risks and threats. A study of Vietnamese smallholder farmers’ perceptions of their current and future capacity to adapt to climate change (Phuong et al., 2018a) found considerable differences between farmers in crop production and livestock production in terms of their motives behind adopting particular planned adaptation options.
A study on farmers’ awareness of, and adaptation to, climate change in the dry zones of Myanmar, critically dependent on agriculture, indicates how those at the front line of the adverse effects of climate change are steadily abandoning the common sesame/groundnut cropping pattern, and trying to adapt to risks and uncertainties with the aid of conventional agricultural practices such as rainwater collection, water-harvesting techniques and even traditional weather forecasting techniques for weather prediction. Similarly, a case study of the Gandak basin in Nepal showed that incorporation of local knowledge into agricultural practices and weather warning systems works best when coupled with multiple sources of information based on a method of triangulation. This also intersects with gender outcomes, where women frequently receive information from the men of their households rather than directly from state institutional sources (Acharya and Prakash, 2019). Climate-change adaptive governance is facilitated by improved cross-scalar and cross-sectoral cooperation, exchange of information and experiences, and best practices (Smith et al., 2014; Watts et al., 2015; Gamble et al., 2016; Gilfillan et al., 2017).
An integrated approach informed by science, which examines multiple stressors along with Indigenous knowledge, appears to be of immense value (Elum et al., 2017). A study on Pakistan concluded that poor agricultural communities are among the worst victims of climate change (Ali and Erenstein, 2017) and that farmers who are younger, better educated, belong to joint families and possess more landholdings are likely to adapt sooner and better. Correspondingly, this category achieved higher levels of income and food security. The climate-development nexus suggests that CCA practices at the farm level can have significant development outcomes, besides reducing risk posed by changing weather patterns. Central to the CCA process is the growing recognition of the role that institutions play in both the hierarchical setting and across different scales to influence implementation of CCA in diverse areas of governance across social and political domains. Cuevas (2018) highlights the usefulness of mainstreaming CCA into local land-use planning in Albay, the Philippines, by involving networks of interacting institutions and institutional arrangements for overcoming obstacles that are potentially counterproductive and conflictual.
As noted by AR5 (IPCC, 2014a), research on issues related to both climate-change impacts on livestock production–demand for which is expected to double by 2050 in a world of 10 billion people–and policy choices with regard to adaptation, especially at the local scale, is still limited but progressing (Rojas-Downing et al., 2017). The promise of diversification of livestock animals (within species), crop diversification and transition to mixed crop–livestock systems needs to be further explored. A study of livestock farmers in Pakistan showed that risk-coping mechanisms, such as purchasing livestock insurance and increasing land areas for fodder, are far more rewarding policy options in comparison with selling livestock and migrating to another place. Relatedly, the association of migration with adaptation measures is context specific and involves a number of factors pertaining to the socioeconomic circumstances of vulnerable agricultural groups in countries like India and Bangladesh (Ojha et al., 2014). In the 2010 United Nations Framework Convention on Climate Change’s Cancun Adaptation Framework, migration was recognised as a form of adaptation that should be included in a country’s long-term adaptation planning where appropriate (Paragraph 14 f).
Furthermore, agricultural climate-adaptation policy targeting livestock farmers in rural areas is very likely to benefit from better education and awareness as well as increased access to extension services among livestock farmers on climate risk-coping choices and strategies (Rahut and Ali, 2018). In Myanmar, the lack of adequate agricultural extension strategies has had a negative impact on adaptation outcomes in what is labelled the ‘central dry zone’. Farmers’ perceptions of climate change contribute to a comprehensive understanding of the context where they identify deforestation and related activities as the main culprits. Their adaptive methods include agricultural land preparation and crop rotation practices in addition to rainwater-harvesting techniques (Swe et al., 2015). A study of vulnerable areas in Bangladesh (Alam et al., 2017) has shown that with policy support, livestock rearing can prove to be a viable substitute for crop production in areas prone to riverbank erosion. Carefully developed partnerships between government organisations and NGOs can come to the rescue of poor farmers and their precarious households by providing information about best practices for local adaptation strategies, including credit options with various institutions and creating an enabling environment for the promotion of agro-based industries. A study in community forestry in the Indian Himalayan region (Gupta and Koontz, 2019) has shown how the synergies and successful partnerships could evolve between government and NGOs in local forest governance, with the former providing technical and financial support, and the latter directing the communities to those resources, and in the making up for each other’s limitations thereby enabling and augmenting community efforts in forest governance.
A study of Pakistan (Ali and Erenstein, 2017) shows that factors such as enhanced awareness about various climate risk-coping strategies, better education and agricultural extension services, augmenting farm-household assets, lowering the cost of adaptation, improving access to services and alternative livelihoods, and providing support to poorer households appear to have paid rich dividends. Countries such as Bhutan and Sri Lanka have included provisions for ‘climate-smart agriculture’ in their nationally determined contributions (NDCs) (Amjath-Babu et al., 2019).
In the domain of forest adaptive governance, ever since the introduction of Reducing Emissions from Deforestation and forest Degradation plus (REDD+) at COP 13 in 2007 in Bali, the Indonesian experience suggests that some of the major challenges include curbing emissions, changes in cross-sectoral land-use as well as practice within forestry and lack of effective, efficient and equitable implementation of diverse forest governance practices. The issue of how forest governance institutions are conceived and managed, both at national and subnational levels, involving state, private sector and civil society, also needs serious attention (Agung et al., 2014).
In an example from Nepal, Clement (2018) showed that deliberative governance mechanisms can create the space for alternative framings of climate change to take a hold in ways that are cognisant of both the local and global contexts; this moves beyond a dependence on techno-managerialism in the construction of solutions, where local governance solutions can support institutional changes. The possibilities more incorporating deliberative methods into wider governance architecture are also expanded through an acknowledgment of the role of social learning; this is observable in the multi-stakeholder involvement that this approach fosters in regions of South Asia such as the Brahmaputra River basin (Varma and Hazarika, 2018). Additionally, recent studies have reconfirmed the importance of linking Indigenous knowledge with the scientific knowledge of climate change in diverse regions of the globe, including Asia and Africa (Hiwasaki et al., 2014; Etchart, 2017; Taremwa et al., 2017; Vadigi, 2017; Apraku et al., 2018; Inaotombi and Mahanta, 2018; Makondo and Thomas, 2018) for building farmers’ resilience, enhancing CCA, ensuring cross-cultural communication, promoting local skills, drawing upon Indigenous Peoples’ intuitive thinking processes and geographic knowledge of remote areas.
A study of the Sylhet Division in Bangladesh, deploying a knowledge quality assessment tool, found significant correlation between a narrow technocratic problem framing, divorced from traditional knowledge strongly rooted in local sociocultural histories and relatively low project success due to skewed risk-based calculations disconnected from the ground realities (Haque et al., 2017; Wani and Ariana, 2018). Highlighting the vulnerability of the Bajo tribal communities, who inhabit the coastal areas of Indonesia, to climate change, the study showed how they share several examples of their Indigenous knowledge and traditions of marine resource conservation, and how this wisdom, a valuable asset for climate adaptation governance, has been passed from generation to generation through oral tradition.
One of the major knowledge gaps in the domain of climate adaptation governance relates to implementation by various stakeholders at multiple scales, and sharing of information and experiences in this regard. There is a need to assuage the perceptions of distrust in global information, through governance methods that engage multiple stakeholders in open and lucid channels of communication (Stott and Huq, 2014). This is observable in the structure of the New Urban Agenda which formed part of the SDGs pertaining to cities and has been shaped by a bottom-up process marked by diverse participation including communities, experts and activists, rather than the top-down variant that is observable in the Millenium Development Goals (Barnett and Parnell, 2016). This approach could also be evidenced in the Paris Agreement, which placed the onus of a successful global governance regime on the development of efficient systems of regional governance. However, these emerging systems of regional governance could equally pose a challenge to the global governance in a way that can be witnessed through the development of financial groups such as the BRICS (associated economies of Brazil, Russia, India, China and South Africa) and Asian Infrastructure Investment Bank, which resulted from a perception of inadequate institutional transformation at the global level. From another perspective, a comprehensive approach would require simultaneous implementation of both bottom-up and top-down models of governance, retaining flexibility of scale.
Given the concerns surrounding food security, especially in light of the principles of common but differentiated responsibilities, under the NDCs submitted by South Asian nations under the Paris Agreement, emission reduction commitments are less likely to include the agriculture sector. Prospects for enhancing both adaptive capacity and food security could be improved by strengthening resilience and profitability through the introduction of a basket of policy choices and actions including structural reforms, agriculture value-chain interventions and landscape-level efforts for climate resilience. Correspondingly, the substantial adaptation finance gap could be closed with the help of both private finance (autonomous adaptation) and international financial transfers (Amjath-Babu et al., 2019).
For nearly five decades, integrated coastal management (ICM), advocated by several international organisations (e.g., IMO, UNEP, WHO, FAO) and adopted by over 100 countries, has been acknowledged as a holistic coastal governance approach aimed at achieving coastal sustainability and reducing the vulnerability of coastal communities in the face of multiple environmental impacts (high confidence). In view of threats posed to coastal ecological integrity by climate-change-induced tropical storm activity, accelerated SLR and littoral erosion and social–ecological impacts on the livelihood security of vulnerable coastal communities, the pressing need for approaches that innovatively combine coastal zone management and CCA measures is widely acknowledged (Rosendo et al., 2018) yet under researched. A study focusing on the three coastal cities of Xiamen, Quanzhou and Dongying, in China, a country with nearly 12% of its national coastline already covered under the ICM governance framework, suggests that whereas the ICM approach has been found to be effective in promoting the overall sustainability of China’s coastal cities (Ye et al., 2015) using accurate and reliable data, in addition, the developing unified standards could usefully reveal changing conditions and parameters related to ICM performance.
Steadily the regional scale of climate adaptive governance is acquiring salience in diverse sub-regions of Asia, and more policy-oriented empirical research is needed on how various regional forums, agencies and multilateral organisations could further contribute by way of in-house expertise and other resources, including financial. A study of climate adaptation in the health sector in Southeast Asia (Gilfillan, 2018) highlights the growing role of the Asian Development Bank (ADB) and the Asia-Pacific Regional Forum on Health and Environment, and shows that their mandates and goals could mutually benefit from the institutionalisation of coordination mechanism. An example from the Maldives shows that the 2014 Tsunami, climate change and the risk of extreme weather events have led to the legitimisation of state-led population resettlement programmes. In China, this has occurred through the renaming of previously existing resettlement initiatives as climate adaptation initiatives; however, the efficacy of resettlement as a CCA measure requires further scrutiny (Arnall, 2019). In India, the National Adaptation Fund on Climate Change has been instituted in order to enable states to implement adaptation programmes; however, this does not address the question of mainstreaming CCA into designs for development (Prasad and Sud, 2019). This is closely related to the development of National Adaptation Programmes of Action (NAPAs) where the mainstreaming of adaptation within countries has been an important concern. Insights from developing countries indicate that there is still much ground to cover. The NAPA of the Maldives prioritises food security, coastal resources and public health, while Nepal has prioritised ecosystem management and public health, and food security, among other concerns (Saito, 2013). Importantly, Bangladesh’s NAPA has shown that there is potential for ‘reflexivity’ in the integration of adaptation objectives with sectoral objectives (Vij et al., 2018). Conspicuous by their absence are the transboundary-scale adaptation policies in South Asia (Vij et al., 2017).
A distinguishing feature of the case of Japanese apple growers is the co-existence of both top-down and bottom-up adaptation practices. The former pertains to farmers who rely on the support of the cooperative for agricultural support and follow institutional mechanisms. The latter pertains to non-co-op farmers who have been responsible for innovative practices of cultivation such as the shift to peaches and the sale in the market of apples without leaf-picking. Importantly, the non-co-op group also have access to sales channels that may not be accessible to the former owing to their direct interactions with customers, among other factors (Fujisawa and Kobayashi, 2011; Fujisawa et al., 2015). The significance of this combination of top-down and bottom-up approaches to agricultural adaptation practices may be further sharpened by formulating approaches for Asia and the Pacific region in ways that contribute to the fortification of food security objectives and the idea of co-benefits. This may be carried out by enhancing the ability of farmers to better manage cultivation practices in the context of climatic variability (FAO, 2018d).
There exist numerous barriers to the mainstreaming of CCA measures across Asia. The integration of CCA into the dissemination of localised climatic information and its uptake and implementation through institutional policy arrangements remain areas of concern (Cuevas, 2018). Institutional incentives to agricultural production, for instance, are frequently compounded by the negative impacts they have on existing bases of natural resources. The disconnected operations of local governmental agencies coupled with inadequacies of cross-sectoral coordination further highlights the prevalent food–water–energy nexus (Rasul, 2016). One possible way of addressing these intersecting sources’ complexity is by locating emerging CCA measures in educational development. The introduction of CCA thinking into land-use planning in the Philippines is an example of the successful role of enhancing public education and awareness through the dissemination of information by institutional channels. The linkages between the strength of local leadership and the inclusion of CCA in localised planning activities are also well illustrated by the case study of Cuevas (2018).
As shown in the case of Pakistan, level of education shares a positive relationship with the implementation of adaptation measures (Ali and Erenstein, 2017). However, a closer examination of the educational imperatives that drive CCA in ways that improve the representational architecture of adaptation actions through a focus on gender is needed. Mainstreaming of gender into CCA would involve addressing a host of barriers to education and involvement that are often rooted in the differential structures of households, social norms and roles, and the domestic division of labour (Rao et al., 2019). A study from the Indian state of Bihar shows that gender plays a major role in determining intra-household decision making and also inhibits the ability of female-headed households to establish access to agricultural extension services (Mehar et al., 2016). Even within wider female farmer-operated federations, such as the Bangladesh Kishani Sabha (BKS), the barriers to participation stem from social factors that include the limitation of female mobility through the gendered division of labour and a lack of recognition of female agency (Routledge, 2015). Gendered inequalities in educational attainment and outcomes viewed through the lens of social vulnerability thus intersect with environmental vulnerabilities in ways that affect the ability of women to participate in CCA, owing also to a lack of access to health and sanitation facilities. These factors have a direct impact on the ability of adaptation to be effective in the global South, and are especially important in the context of the commitments of the UN Convention on the Elimination of All Forms of Discrimination Against Women countries to the objective of gender equality (Roy, 2018).
Box 10.5 | Bangladesh Delta Plan 2100
The Bangladesh Delta Plan (BDP)2100 is the plan moving Bangladesh forward for the next 100 years. We have formulated BDP 2100 in the way we want to build Bangladesh. (Commission, 2018).
The vision of BDP is revealed by the foregoing statement from Sheikh Hasina, the prime minister of Bangladesh. The government approved BDP 2100 in 2018. Achievement of a safe, climate-resilient and prosperous delta is the aspiration of the delta plan. Ensuring water and food security with economic growth, environmental sustainability, climate resilience, vulnerability reduction to natural hazards and minimising different challenges of the delta through robust, adaptive and integrated strategies, and equitable water governance, are the mission of this mega plan. Under this mission, three higher-level goals and six specific goals have been determined. Three higher-level goals include elimination of extreme poverty by 2030, achievement of upper middle-income status by 2030 and becoming a prosperous country beyond 2041. Six specific goals of BDP 2100 are fully linked with SDG Goals 2, 6, 13 and 14 and partially linked with Goals 1, 5, 8, 9, 11 and 15. These specific goals comprise a wide range of issues, including land and water resources, climate change, disaster, wetlands and ecosystems, river systems and estuaries. The vision, mission and goals of BDP 2100 reveal that this mega plan is a holistic and integrated approach considering diversified themes and sectors for the whole country. The implementation of the BDP 2100 requires total spending of an amount of about 2.5% of the GDP per annum. A series of strategies have been formulated for better implementation of the mega plan.
Water is the key and complicated resource of Bangladesh, and therefore BDP 2100 has kept water at the centre of the plan. It aims to promote wise and integrated use of water and other resources through development of effective institutions and equitable governance for in-country and transboundary water resource management.
Along with water, for the first time in any development planning, BDP 2100 has taken the climate-change issue as an exogenous variable in developing the macroeconomic framework of the plan. In a brief, it is stated that the principle of BDP 2100 is ‘Living with Nature’.
Much like any other field, CCA is greatly facilitated by science, technology and continuous innovation. These range from the application of existing science, to the development of new scientific tools and methods, to the utilisation of Indigenous knowledge and citizen science. Many of the pressing problems in Asia, including water scarcity, rapid urbanisation, loss of natural habitats, biodiversity, rising coastal and river basin hazards, and agricultural loss can be effectively minimised through the adoption of suitable scientific and technological methods. Despite the current challenges in the region, many significant advances in science and technology have been made, and the future prospects look bright. The following sections outline the present status and future prospects of science and technology in scaling up adaptation actions in four key sectors, namely (a) DRR, (b) urbanisation, (c) water and agriculture, and (d) forests and biodiversity.
Technological advances have enhanced the capabilities of Asian countries to monitor and prepare for climate-related hazards. Remote sensing technologies and GIS are widely used for DRR (Kato et al., 2017), for example, to assess and mitigate risks of an area to potential climate-related disasters (Wu et al., 2018b). The potential impacts of different types of hazards can be visualised using interactive maps (Lee, 2017), which help local communities to understand risks and find appropriate evacuation areas (Cadiz, 2018). These maps provide a situational overview and instant risk assessment (Yang et al., 2012b). As an emerging technology, artificial intelligence (AI) can identify conditioning factors of a landslide disaster (Hong et al., 2019b). Mobile virtual reality is used for disaster mitigation training through a three-dimensional visualisation of a past disaster (Ghosh et al., 2018).
A community-based DRR system provides risk investigation, training and information analysis (Liu et al., 2016b). Sharing information enhances establishment of such a system and contributes to disaster prevention (Nakamura et al., 2017). One example is an online mapping tool, which has been developed by volunteers (Sakurai and Thapa, 2017). Social media enables the population to access real-time information on a disaster (Ghosh et al., 2018), raises situation awareness (Yin et al., 2012) and empowers communities towards appropriate emergency actions (Leong et al., 2015). Among the various forms of social media, Twitter is widely used as a social sensor to detect what is happening in a disaster event (Sakaki et al., 2013). Accuracy of information on Twitter has been proved in collecting local details about floods (Shi et al., 2019b); however, it has been noticed that Twitter generates rumours as well (Ogasahara et al., 2019). Artificial intelligence is expected to reduce human error when they operate a decision-making system (Lin et al., 2018). Since technologies supporting DRR completely depend on electricity, the loss of power supply and communication constrains the recovery work in disaster-affected areas (Sakurai et al., 2014).
In the urban sector, a wide variety of sensor technologies are being used to monitor urban land-use and climate changes over time, and to better understand the potential impacts of future changes. These sensors range from large optical–thermal–radar satellite instruments with (near) global coverage–for example, Landsat (US Geological Service), Sentinel (European Space Agency), ALOS (Japan Aerospace Exploration Agency) and MethaneSAT–to portable sensors embedded in mobile phones (e.g., phone cameras or temperature sensors) whose data are collected into centralised databases through crowdsourcing (Fenner et al., 2017; Meier et al., 2017). To combine and extract useful information from these heterogeneous sensor data–for example, for conducting climate risk assessments (Perera and Emmanuel, 2018; Bechtel et al., 2019) and/or simulations of future land-use or climate changes in urban areas (Bateman et al., 2016; Iizuka et al., 2017; Liu et al., 2017c)–AI technologies (e.g., machine-learning algorithms) are now being widely adopted (Johnson and Iizuka, 2016; Joshi et al., 2016; Mao et al., 2017). Thanks to advances in cloud-computing technology, which allows for online processing of massive volumes of remote sensing data, high-resolution (~30 m) global urban-area maps from the late 1990s to 2018 are now available from several different sources (Gong et al., 2020). Using these historical maps, researchers have been able to generate maps of future urban land-use changes at the global level to 2100 (Chen et al., 2020a), which can help to elucidate the potential impacts of this future urban expansion and identify adaptation needs. Technology also plays a major role in urban planning and design in the context of adaptation. To mitigate rising urban temperatures and reduce the impacts of climate-related hazards, many new ‘grey’ infrastructure and ‘green’ infrastructure technologies are being adopted in urban areas in Asia, for example, cool (i.e., high solar reflectance) rooftops and pavements as well as green (i.e., vegetated) rooftops to mitigate high temperatures; and porous pavements to mitigate flooding (Akbari and Kolokotsa, 2016).
The majority of the Asian region is experiencing water stress in terms of both quantity and quality, due to poor management systems and governance. This has dire consequences for the national GDP as the majority of the population belongs to agrarian communities and their water-dependent agriculture system. Despite a substantial investment and progress in research and development, and capacity building in the recent past, the majority of developing countries in Asia are struggling to manage both water resources and agriculture sectors heavily dependent on water resources, in response to rapid global changes. Considering the frequent extreme weather conditions, progress in management tasks is even more consequential; hence, critically important for these countries, to achieve better CCA, are advanced science and technology viz. smart agriculture, robust EWS using downscaled meteorological information, a participatory approach, IWRM and so forth.
Having scientific knowledge relevant at the local scale through placed knowledge is important to identify climate-change risk and vulnerability. Moreover, once integrated with socioeconomic attributes, it can be useful for natural resource management, agriculture and so forth (Leith and Vanclay, 2017). Role of big data and data mining is undeniably very huge to get reliable climatic information and hence for designing appropriate adaptation measures for natural resource measurement. For example, use of big data in terms of EWS and real-time observation data provides more accurate information on hydro-meteorological extreme weather conditions or hazards like drought and flood, and will help farmers and local governments to improve their perception and hence preparedness for better adaptation (Hou et al., 2017; Ong and G.L.B.L., 2017). Using big data, different adaptation measures, such as new cultivar breeding, cropping-region adjustment, irrigation-pattern change, crop rotation and cropping-practice optimisation, are being designed in the agriculture sector, and these practices have greatly increased crop yield, leading to higher resource-use efficiency as well as greatly increased soil organic carbon content with reduced GHG emissions. It results in a win–win situation in terms of enhancing food security and mitigating climate warming (Deng et al., 2017). However, usability and application of this technology are still not common, especially in data-scarce regions. Integrated numerical simulations are efficient tools for estimating the current status and predicting the risk and efficiency of the adaptive capabilities of different countermeasures for sustainable natural resource management such as with water (Kumar, 2019). Similarly, the agent-based model is commonly used to estimate risk of food-borne diseases due to climate change, using tunable parameters such as hygiene level, the microorganism’s growth rate and the number of consumers, and hence it has the potential to be a useful tool for optimising decision making and urban planning strategies related to health and climate change (Gay Garcia et al., 2017). The integrated assessment model under the shared-socioeconomic pathway (SSP) framework is effectively used to estimate future energy development and possible mitigation strategies to reduce GHG emissions related to the energy sector (Bauer et al., 2017). Sound understanding of different drivers, pressures and stress factors, such as abnormal temperature, rainfall, insect pests or pathogens and their interaction pattern with the genetic makeup of crops, is the key to produce high-yielding varieties of wheat with better nutritional quality and resistance to major diseases (Goel et al., 2017). Another critical point to address this water security is inclusive, polycentric and adaptive governance. Polycentric governance is a means by which water management plans and policies should be framed and agreed by all relevant stakeholders. For adaptive governance, more emphasis will be on finding the best pathways to make robust water management plans amid rapid global changes. The benefit of such plans should reach the end users in terms of providing clean water, protection from hydrological hazards and maintaining the health of the ecosystem. In addition, there is urgent need for co-management, which includes the cycle of co-design, co-implementation and co-delivery throughout the whole water cycle. The best suitable example is using the circulating and ecological sphere (CES) approach. The CES is a concept that complements and supports regional resources by building broader networks, which are composed of natural connections (connections among forests; city and countryside; groundwater, rivers and the sea) and economic connections (human resources, funds and others), thus complementing each other and generating synergy (Mavrodieva and Shaw, 2020). Another suitable example for managing water resources is the participatory watershed land-use management (PWLM) approach. The PWLM is another very innovative and successful approach for more robust water resource management as explained by Kumar et al. (2020). It helps to make land-use and CCA policies more effective at the local scale. This is an integrative method using both participating tactics and computer-simulation modelling for water resource management at the regional scale.
Technologies and their applications to identify habitat degradation, ecosystem functions and biodiversity conservation are increasing in Asia, with many countries looking to new and improved means for forest and biodiversity monitoring and conservation. In particular, there has been an impressive use of temporal satellite data, particularly from the Landsat and the Moderate Resolution Imaging Spectroradiometer (MODIS) series for widespread monitoring of forests and ecological resources. These series have provided reliable information on forests and ecosystem services at the country level, in difficult terrains, such as the mountains, cross-boundaries and otherwise inaccessible areas. For instance, Yin et al. (2017) estimated cross-boundary forest resources in Central Asia, a region which traditionally suffered from lack of reliable forest data, using remote sensing techniques. In a separate study, Reddy et al. (2020) used long-term MODIS forest fire data from 2003 to 2017 to characterise fire frequency, density and hotspots in South Asia. Archives of scientific data, backed by state-of-the art modelling techniques, advanced-computing methods and innovations in big-data analysis, particularly helped the provisioning of scientific research. A number of studies simulated forest futures from the local to the continent scale under different socioeconomic and climate scenarios. For instance, at the local scale, Dasgupta et al. (2018) projected the future extent of mangroves in the Sundarban Delta under four local scenarios, while Estoque et al. (2019) modelled and developed spatial maps of regional forest futures in Southeast Asia using the five SSP scenarios. Science and technology also helped the monitoring of species diversity and abundance, pivotal for sustaining an ecosystem and ecosystem-based adaptation. Digital camera traps and radio-collaring methods have largely replaced old film cameras and labour-intensive methods of photo screening to count target species (Pimm et al., 2015). This enhanced scientific capacities to monitor biodiversity and facilitate better conservation in difficult terrains, control poachers and maintain steady ecological balance. Umapathy et al. (2016), for example, used VHF radio collars and satellite-based tracking tools to monitor the movement of Bengal tigers over hostile island terrain. Photo recognition and other non-invasive techniques for individual identification have been rising in Asia. For example, a study by Gray et al. (2014) used faecal-DNA samples to estimate the population density of the Asian elephant in Cambodia. Furthermore, the advancement of citizen science programmes has greatly facilitated better monitoring of forest resources, including invasive floral and faunal species (Chandler et al., 2017; Johnson et al., 2020). In Asia, citizen science has been used effectively in India (Chandler et al., 2017), and also in Malaysia for the monitoring urban bird abundance (Puan et al., 2019).
With rapid advances of technologies, the use of appropriate technologies generates some degree of management problems. To resolve such problems, the enhancement of information science is essential to understand design, implementation and adoption of digital tools under crisis (Xie et al., 2020). For example, social media research reveals a way of controlling malicious information (Tanaka et al., 2014), and its characteristics under COVID-19–showing a plain text message–can be more powerful in the context of citizen engagement than media-rich communications (Chen et al., 2020b). Information behaviour needs more investigation to understand how people survive and connect in the era of information overload (Pan et al., 2020). Moreover, a new set of data (e.g., travel history record, personal health data, etc.) becomes an important base of DRR (Xie et al., 2020). Analysis of these personal data requires careful consideration, as it generates ethical issues (Sakurai and Chughtai, 2020). Indicators or measurements of technology-enabled crisis response needs to be developed for further risk reduction (Akbari and Kolokotsa, 2016; Wong et al., 2020). On the other hand, adopting infrastructure technologies requires investment, and due to the inherent uncertainties of climate projections, the future payoffs of these investments are also somewhat uncertain (Ginbo et al., 2020). In the water and infrastructure sectors, for example, various options exist for conducting cost–benefit analysis considering future uncertainty (i.e., so-called robust approaches, which are able to identify adaptation projects and infrastructure that can achieve their intended purpose(s) across a wide range of climate scenarios) (Dittrich et al., 2016). Despite substantial investment and progress in research, development and capacity building in the recent past, the majority of the developing countries in Asia are struggling to manage both water resources and the agriculture sector. Considering the frequent extreme weather conditions, progress in management tasks has become even more mammoth and, hence, we need a holistic solution, which is currently missing in field implementation. This solution should be based on advanced science and technology in association with other attributes like social, economic and political dynamics, which play a pivotal role in sustainable management of water resources and agriculture, as a way forward.
Understanding the motivations and processes underpinning decisions to adapt or not is key to enabling adaptation (see Section 17.2.2.1; Clayton et al., 2015; de Coninck et al., 2018; Taylor, 2019; van Valkengoed and Steg, 2019a; van Valkengoed and Steg, 2019b), because how and why certain people adapt is shaped by sociocultural factors, ways of making sense of risks and uncertainty, and personal motivations to undertake action (Nguyen et al., 2016; Mortreux and Barnett, 2017; Singh et al., 2018b; van Valkengoed and Steg, 2019b). The IPCC’s Assessment Report 5 was critiqued for silences on how perceptions shape climate action and the behavioural drivers of adaptation responses (Lorenzoni and Whitmarsh, 2014). Addressing this gap and assessing the growing literature from social sciences, notably psychology, behavioural economics and risk perception studies, the IPCC Special Report on 1.5°C (de Coninck et al., 2018) comprehensively assessed behavioural dimensions of CCA for the first time; however, compared with studies on mitigation behaviour, the literature on what motivates adaptation remains incomplete (Lorenzoni and Whitmarsh, 2014; Clayton et al., 2015).
There are three key aspects of adaptation to which psychology and behavioural science contribute: understanding perceptions of climate risk, identifying the behavioural drivers of adaptation actions and analysing the impacts of climate change on human well-being (Clayton et al., 2015). Overall, there is growing acknowledgement that individual adaptation is significantly shaped by perceptions of risk, perceived self-efficacy (i.e., beliefs about which options are effective and one’s ability to implement specific adaptation interventions), sociocultural norms and beliefs within which adaptation decisions are taken, past experiences of risk management and the nature of the intervention itself (Grothmann and Patt, 2005; Werg et al., 2013; Clayton et al., 2015; Truelove et al., 2015; Pyhälä et al., 2016; Deng et al., 2017; Sullivan-Wiley and Short Gianotti, 2017; Taylor, 2019; van Valkengoed and Steg, 2019a). This is in addition to more commonly understood factors shaping adaptation behaviour such as technical know-how and the cost and benefits associated with an option.
Across Asia, behavioural aspects of adaptation have been studied to a lesser extent: a global meta-analysis of 106 studies found that most research focused on North America and Europe with only 12% of papers from Asia (van Valkengoed and Steg, 2019a). Within Asia, behavioural drivers of adaptation decision making have been studied primarily in agriculture (in South, East and Southeast Asia) and disaster risk management (from Southeast and East Asia) (Table 10.4) and tend to focus on technical adaptation interventions rather than how and why people adapt (Sun and Han, 2018).
Table 10.4 | Sectors and sub-regions where behavioural aspects of adaptation have been assessed
Sub-region | Sector | Adaptation interventions | Behavioural aspects affecting adaptation | Supporting references |
West Asia | Agriculture | Soil and water conservation activities to mitigate drought impacts | Response efficacy and perceived severity shape water conservation. | Iran (Keshavarz and Karami, 2016) |
Central Asia | NEa | NEa | NEa | NEa |
South Asia | Agriculture | Conservation agriculture, adjusting agricultural practices | Risk perceptions shape adoption of adaptation strategy (e.g., perceptions of decreasing rainfall motivate building water storage tanks). | Nepal (Piya et al., 2013; Halbrendt et al., 2014) |
Sustainable water management practices, adjusting agricultural practices | Risk perception is shaped by sociocultural context, memories, experiences and expectations (of future change). | India (Singh et al., 2016) | ||
Alternate wetting and drying irrigation, alternative crop selection, using drought-resistant seeds | A combination of attitudes, self-efficacy, outcome efficacy, and community efficacy predict intent to adapt strongly. | Sri Lanka (Truelove et al., 2015) | ||
Adjustment in farm management including growing short duration or drought-tolerant varieties, pest-resistant varieties, changing planting distance, increasing weeding, soil conservation techniques, cultivation of direct-seeded rice, switching to non-rice crops | Farmers’ education, access to credit and extension services, experience with climate-change impacts such as drought and flood, information on climate-change issues, belief in climate change and the need to adapt all variously determine their decision making. | Nepal (Khanal et al., 2018) | ||
Disaster management | Flood and cyclone preparedness measures such as using durable building materials, raising plinth levels, storing food and water | Disaster management behaviour is intuitive: low evidence to suggest outcome expectancy, self-efficacy, and preparedness intention follow linear patterns. | India (Samaddar et al., 2014); Bangladesh (Dasgupta et al., 2014b) | |
Use of emergency toolkits and evacuation plans | Risk perception and knowledge of adaptation options shape uptake and perceived benefits. | Pakistan, Bangladesh (Alvi and Khayyam, 2020) | ||
Insurance to deal mitigate financial losses from floods and droughts | Frequency, the severity of previous extreme events, socioeconomic settings and ability to pay shape decisions to take crop insurance. Acceptability of flood insurance depends on the perceived efficacy of the insurance (among other factors such as age of household head, land ownership and off-farm income sources). | Pakistan (Arshad et al., 2016; Abbas et al., 2015) | ||
Embankments and dikes for flood risk mitigation | Willingness to contribute manual labour to flood protection measures is positively influenced by the number of adult family members, livestock damage, compensation received and expected effectiveness of the intervention, but is negatively influenced by age and education of the household head, farm income and the distance of the farm from the river. | Pakistan (Abbas et al., 2019) | ||
Southeast Asia | Agriculture | Changing agricultural practices, diversifying livelihoods | Values along with personal and social beliefs of risk shape adaptation. | Vietnam (Le Dang et al., 2014; Cullen and Anderson, 2016; Nguyen et al., 2016; Arunrat et al., 2017) |
Disaster management | Raising floor height to avoid flooding, retrofitting houses | Perceived probabilities and perceived consequences of flood shape preparedness. | Vietnam (Reynaud et al., 2013; Ling et al., 2015) | |
Flood insurance | Likelihood of purchasing flood insurance increased with higher physical exposure and subjective perceptions of vulnerability. | Malaysia (Aliagha, 2013; Aliagha et al., 2014) | ||
Evacuation | Individual risk perceptions lead to learning, but only where previous disaster experiences are traumatic. | Philippines, India (Walch, 2018) | ||
Disaster preparedness measures such as having kits, undertaking precautionary measures | Perceived self-efficacy was the most significant measure affecting reactive adaptation; education had the highest effect size on anticipatory adaptation. | Cambodia (Ung et al., 2015) | ||
East Asia | Agriculture | Changing agricultural practices, diversifying incomes, adopting water-saving technology, purchasing weather insurance | Perceived self-efficacy strongly predicts adaptive intent. | China (Jianjun et al., 2015; Zhang et al., 2016a; Burnham and Ma, 2017; Feng et al., 2017) |
Disaster management | General | Higher education and being in environments where climate is discussed leads to stronger risk perceptions. | Taiwan, Province of China (Sun and Han, 2018) | |
Drought management through early warnings, prevention information | Policies can positively shape adaptation decision making depending on how information is given and what support is provided. | China (Wang et al., 2015) |
(a) No evidence
In agriculture, studies demonstrate how perceptions of risk (e.g., climate variability) (Singh et al., 2016; Zheng and Dallimer, 2016; Burnham and Ma, 2017; Feng et al., 2017), sociocultural norms and personal experiences (Masud, 2016; Nguyen et al., 2016; Singh et al., 2016), and perceived efficacy of adaptation interventions in having a positive and desirable impact (Halbrendt et al., 2014; Truelove et al., 2015; Feng et al., 2017), affect adaptation decisions. Policies on providing early warnings of drought or information on prevention techniques shape farmer decisions to undertake adaptation interventions (Wang et al., 2015).
In disaster risk management, risk appraisal (Samaddar et al., 2014; Rauf et al., 2017; Hung et al., 2018), previous experience and losses (Said et al., 2015; Hung et al., 2018; Walch, 2018)12, 11 perceived probabilities and consequences (Reynaud et al., 2013), perceived self-efficacy (Ung et al., 2015; Hung et al., 2018) and awareness (Hung et al., 2018; Wu et al., 2018a; Alvi and Khayyam, 2020) shape preparedness. Individual risk management is nested within public policies, such as those on flood management, which shape individual flood risk perception and protective behaviours (Reynaud et al., 2013) as well as personal factors such as religious beliefs (Alshehri et al., 2013). For example, communities often perceive disasters as ‘acts of God’ (Birkmann et al., 2019) or punishment for wrongdoings (Alshehri et al., 2013; Iqbal et al., 2018), which might constrain adaptive action. However, religious faith can also motivate people to prepare for extreme events, as Alshehri et al. (2013) showed in Saudi Arabia demonstrating how ‘Islam urges that it is most important to prepare the people to escape from disaster’ (p.1825).
Trust in public action as a mediator of risk management has had conflicting evidence: some studies have discussed trust as being critical to effective preparedness (Kittipongvises and Mino, 2015; Walch, 2018), while others have found that trust in public actions, such as structural interventions to mitigate flood impacts, can lower individual motivations to act since they feel protected (Hung et al., 2018).
Belief in climate variability and change significantly shapes adaptation decision making (Le Dang et al., 2014; Singh et al., 2016; Khanal et al., 2018; Liu et al., 2018a) with those believing in climate change and associated impacts tending to engage in adaptation. Crucially, those who do not believe in climate change can be influenced by social norms (Arunrat et al., 2017) thereby incentivising adaptation behaviour. While risk perception is a critical step in adaptation decision making, higher risk perception does not necessarily signal better capacity to cope: in Taiwan, Province of China, Sun and Han (2018) highlight how perceptions of climate risk as a global problem tends reduce its urgency as an individual issue. Providing information on climate risks, impacts and possible adaptation options enables adaptation behaviour (Piya et al., 2013; Zheng and Dallimer, 2016; Rauf et al., 2017), but information alone is not sufficient to motivate adaptive behaviour. Specifically, awareness building on concrete measures and outcomes, such as the amount of water saved or number of deaths averted, rather than abstract notions of climate change, motivate adaptation (Deng et al., 2017; Rauf et al., 2017).
Changes in current lifestyles and consumption patterns are acknowledged as critical to climate action (de Coninck et al., 2018; IGES, 2019). With rapidly changing diets and increasing purchasing power, lifestyle changes in countries across Asia, especially those with large populations such as China and India, will be critical to contributing to global climate solutions (IGES, 2019). Lifestyle shifts that can contribute towards adaptation include:
Overall, understanding behavioural factors shaping adaptation implementation and uptake is important (medium evidence, high agreement ). While there is a growing literature on behavioural drivers of adaptation at the individual and household levels, gaps remain in understanding how socio-cognitive factors affect adaptation behaviour at higher scales (e.g., at local or subnational government, in the private sector, etc.)13. 12 More empirical evidence is needed in sectors beyond agriculture and disaster risk management (e.g., factors motivating urban adaptation) and better coverage across Asia’s sub-regions. Importantly, there are no studies on the behavioural aspects of adaptation from Central Asia.
Estimates of adaptation costs and financial needs have evolved significantly since the previous IPCC assessments. These developments are based on improvements in the understanding of how the hazard interacts with the physical and socioeconomic elements, and how to capture these interactions in systematic modelling frameworks. The developments are also clearly reported especially in the area of addressing the underestimates in adaptation costs that the previous studies suffered from as the previous studies tended to rely on data from wealthy economies (Hochrainer-Stigler et al., 2014; Carleton et al., 2020). The adaptation cost estimates have also improved since the previous IPCC reports due to constant improvements in capturing the loss and damages of disaster events (Hochrainer-Stigler et al., 2014). The reliance of earlier studies on correlations to derive adaptation costs was addressed to some extent by addressing the endogeneity of disaster measures (Kousky, 2014), especially by relying upon the physical measures of disasters such as wind speed, although more work is needed in this area.
Climate change can cause significant impacts and as a result can impose considerable adaptation costs on countries and people. Despite the importance, the research on adaptation costs is limited in Asia, especially on the economy-wide costs, while fragmented literature is available on sector-level adaptation costs. Most of the available literature on adaptation costs at the regional level originate from the work carried out by development finance institutions such as ADB.
Estimates suggest that climate-change impacts could result in a loss of 2% of the GDP of South Asian countries by 2050 and 9% by 2100 (Ahmed and Suphachalasai, 2014). These impacts will be felt in major vulnerable sectors, including agriculture, water, coastal, marine, health and energy, and will have significant impact on the economic growth and poverty reduction in the region. Countries could differ widely in terms of the economic costs they face. In South Asia, the economic costs were projected to be 12.6% of the GDP for the Maldives, which is the highest among the South Asian countries, and 6.6% for Sri Lanka, the least among the South Asian countries. The resultant adaptation costs for countries were projected to range from 0.36% (Copenhagen Cancun Scenario for 2050) to 1.32% (business-as-usual scenario) of the GDP in various scenarios during 2010–2050 (Medium agreement , limited evidence) (Ahmed and Suphachalasai, 2014).
Arto et al. (2019) have reported the adaptation costs of the Mahanadi Delta in India for agriculture, fisheries and infrastructure sectors (Arto et al., 2019). The cumulative adaptation costs for 2015–2016 were reported to be 276 million USD for agriculture and 0.163 million USD for fisheries. In comparison, the modelled cumulative agricultural GDP loss due to climate-change impacts was reported to be 5% up to 2050, and 8% for infrastructure. Adaptation interventions, such as embankments, were found to provide an avoided losses (adaptation benefits) to the tune of 2.2% of the delta’s GDP by 2050. Similarly, input subsidies in seeds, fertilisers and biofertilisers were found to buffer the shocks in agriculture by 10%, and buffer the GDP per capita by 3% (Arto et al., 2019).
Markandya and González-Eguino (2019) have estimated the adaptation costs and residual adaptation costs accrued due to insufficient adaptation using integrated assessment models. Using the residual damages as a measure of loss and damage, the authors have estimated adaptation costs and residual costs under scenarios of high damages–low discount rate and low damages–high discount rate. The estimates suggested adaptation costs of 182 and 193 billion USD by 2050, and 737 and 783 billion USD by 2100 for South Asia and East Asia, respectively, under the scenario of high damages–low discount rate. The residual costs for the same scenario were 289 and 76% for 2050 and 238 and 62% for 2100 for South Asia and East Asia, respectively. Estimates for low damages–high discount rate were significantly lower adaptation costs and residual costs for both of these sub-regions of Asia.
The CCA efforts can be characterised as fragmented, incoherent and lacking perspective (Ahmed et al., 2019a), and the picture on adaptation financing can be stated as similarly fragmented with very limited literature published in peer-reviewed journals. Adaptation financing is crucial for supporting vulnerable countries and enhances adaptation, as it is evident that the enhanced adaptation finance support has positively affected the pace of adaptation in low-income countries (Ford et al., 2015). At the organisational level, adaptation financing has provided multiple functions that include risk assessment functions, valuation functions and risk disclosure functions (Linnenluecke et al., 2016).
Of the total global public adaptation finance of 28 billion USD, East Asia and the Asia–Pacific attracted 46% of the total funding, while South Asian countries attracted only 9% of the total funding (UNEP, 2016). These differences reflect the capacity of countries to attract adaptation finance. Some of the important adaptation-targeted climate funds are Pilot Programmes for Climate Resilience, Green Climate Fund, and Least-Developed Countries Fund, and South Asian countries have significantly benefited from these dedicated climate funds. Due to the disaster implications of climate change, there is a need to allocate adaptation finances for DRR. Estimates suggest that East Asia and the Asia–Pacific in general allocated 27% of the total adaptation funds to DRR, while South Asia allocated 25% (Caravani, 2016). Low-income economies tend to allocate more adaptation funds to DRR (46%), while lower-middle-income economies allocated 22%.
The least developed countries lack the capacity to adapt to climate change and the Least Developed Country Fund (LDCF) has made significant contributions to adaptation in these countries (High agreement, limited evidence). Based on the interview-based field research in four least developed countries, Sovacool et al. (2017) opined that the LDCF projects are contributing to the adaptive capacity of these countries (Sovacool et al., 2017). They also found that these projects are taking a marginal approach, rather than a radical or transformational one, to adaptation.
Kissinger et al. (2019) have estimated the climate financing needs in the land sector under the Paris Agreement. The estimates suggested adaptation needs of 2.5 billion USD for Bangladesh, 40.5 million USD for Lao PDR and 31 million USD for Mongolia, for the forest sector alone (Low agreement, limited evidence).
Financing green growth and low-carbon development can provide resilience benefits (high agreement , limited evidence). Kameyama et al. (2016) have estimated the cost of low-carbon investments that can provide resilience benefits in Asia and reported that such low-carbon development will cost in the range of 125–149 billion USD annually. A combination of public, private, bilateral and multilateral funding sources, and carbon-market offsets, were suggested to achieve this level of funding. In terms of the total resources available, a combination of public, private and bi- and multi-lateral funding could help the region to raise as much as 222.3–412.5 billion USD annually, with a possibility to reach higher amounts depending on the future economic growth of countries in the region. Soil carbon sequestration in agricultural soils was found to be a win–win solution for both mitigation and adaptation as it can help improve soils while increasing farm yields and incomes of smallholders (Aryal et al., 2020a).
New adaptation financing sources have been emerging which could provide country-specific adaptation financing suiting local-level adaptation needs in Asia. The newly established Asia Infrastructure Investment Bank (AIDB), and newly emerging developing-country finance institutions, are known to provide an additional adaptation finance (Neufeldt et al., 2018); however, despite these emerging financial sources, the region will fall short of the adaptation target in the Paris Agreement (Neufeldt et al., 2018).
Adaptation cost estimates can vary between various studies due to the differences in methodologies they adopt. Some studies have conducted cost assessments using a combination of stakeholder consultations and quantitative modelling of climate-change impacts and adaptation (Ahmed and Suphachalasai, 2014), while others depended solely on the quantitative modelling. Studies also differ in the coverage of sectors too: they either have focused on the multiple vulnerable sectors (Ahmed and Suphachalasai, 2014) or on a single sector (Hossain et al., 2019). Studies have differed in their estimates depending on their ability to take into consideration the transition costs of sudden adaptation (Hossain et al., 2019), the nature of social cost and/or damage functions employed (Arto et al., 2019), the discount rates applied (Markandya and González-Eguino, 2019) and consideration for the effects of GHG mitigation on adaptation needs (Duan et al., 2019a). In addition, the assumptions made on the pace of adaptation in estimating adaptation costs can make a difference in adaptation cost estimates. Adaptation at a slow or normal pace could require more adaptation finance, as large amounts of damage are not eliminated, than when adaptation is implemented at a faster rate (Markandya and González-Eguino, 2019). Although there have been improvements in adaptation cost estimates, there is a need to address the issue of endogeneity (Kousky, 2014; Samuel et al., 2019). The vast majority of studies that rely on databases, such as EM-DAT, tend to suffer from such endogeneity problems due to their inability to control the causality between GDP and damages (Kousky, 2014). Costs attributable to non-economic losses and damages are the least reported and least quantified in the adaptation costs literature due to lack of sufficient, robust and accessible methodologies (Chiba et al., 2017; Chiba et al., 2019; Serdeczny, 2019). This is a major limitation in assessing adaptation costs and financial needs, and it can lead to gross underestimation of adaptation costs. A detailed description of issues related to non-economic losses and damages, and its importance in strengthening adaptation, is provided in Box 10.6 and Table 10.5.
Box 10.6 | Loss and Damage Across Asia: Mapping the Evidence and Knowledge Gaps
Losses and damages are climate impacts after implementing adaptation and mitigation actions, signifying the presence of residual risks (Chapter 1; Kugler and Sariego, 2016; Mechler et al., 2019). These residual risks indicate that despite adaptation, there are soft and hard adaptation limits (Mechler et al., 2019). This box reviews the adaptation literature across 51 countries in Asia on loss and damage (L&D), and adaptation barriers and limits, and identifies knowledge and regional gaps. The key messages are that (a) climate-induced L&D is already occurring across Asia (medium evidence, high agreement ), (b) these L&D are very likely to increase at higher warming levels (medium evidence, high agreement ) and (c) measuring and attributing non-economic and intangible L&D remains a challenge (low evidence, high agreement ).
Findings on losses and damages in Asia: Evidence on climate-related L&D highlights tangible or material losses and damages such as loss to life, property, infrastructure and livelihoods (medium evidence, high agreement ); and intangible or non-material losses and damages such as increasing conflict and civil unrest, erosion of sociocultural practices and decreased well-being (low evidence, high agreement ). The main constraint in assessing past and future L&D is that this terminology is not used prominently or consistently in the disaster management and climate risk literature in Asia, which potentially leads to under-reporting. In contrast, there is robust evidence (high agreement ) on adaptation constraints, notably on governance, informational and physical constraints, to adapting, but regional evidence is very uneven with gaps in Central, North and West Asia. Table 10.5 presents a summary of L&D but draws on national and subnational studies.
The knowledge gaps are as follows:
Way forward: Developing robust metrics and institutions for measuring and reporting L&D at national and regional scales, especially non-economic damages and L&D due to slow-onset events, is critical. In addition to vulnerability assessments, assessing L&D and limits to adaptation can inform adaptation prioritisation and enhance adaptation effectiveness (e.g., Craft and Fisher, 2016; Leiter et al., 2019). Lessons are available from biodiversity and ecosystem services monitoring frameworks that have well-developed metrics and processes (e.g., Díaz et al., 2020).
Table 10.5 | Tangible and intangible losses and damages across Asia a
Sub-region (no. of papers) | Key risks reported in L&D papers | Losses and damages | Adaptation constraints (bold ticks denote strong barrier) | Adaptation limits | ||||||||||||
Tangible | Intangible | E | S | H | G | F | I | P | B | Soft | Hard | |||||
Past | RCP2.5 | RCP4.5 | RCP8.5 | |||||||||||||
East Asia (32) | Coastal flooding, heatwaves, SLR | *** | * | ** | ** | * | ✓ | ✓ | ✓ | ✓ | ✓ | NE | NE | |||
Southeast Asia (4) | Coastal flooding, SLR | * | * | ✓ | ✓ | ✓ | NE | NE | ||||||||
South Asia (18) | Coastal flooding, drought, SLR, heatwaves | *** | * | ** | ** | ** | ✓ | ✓ | ✓ | ✓ | * | ** | ||||
Central Asia (3) | Snowmelt, heatwaves, drought | * | * | * | ✓ | ✓ | NE | NE | ||||||||
North Asia (2) | Permafrost thaw | * | * | * | ✓ | NE | NE | |||||||||
West Asia (9) | Heatwaves, drought | ** | * | * | * | ✓ | * | ** | ||||||||
Magnitude of losses and damages | Evidence | Adaptation constraints | ||||||||||||||
High (>50% sector/population affected relative to reported baseline) | *** | High (≥10 papers) | E | Economic | ||||||||||||
S | Sociocultural | |||||||||||||||
Medium (25–50% sector/population affected) | ** | Medium (5–9 papers) | H | Human capacity | ||||||||||||
G | Governance | |||||||||||||||
Low (<25% sector/population affected) | * | Low (≤4 papers) | F | Financial | ||||||||||||
I | Informational/technological | |||||||||||||||
Not assessed due to inadequate evidence | NE | No evidence | P | Physical | ||||||||||||
B | Biological |
Notes:
East Asia: Tezuka et al. (2014); Elliott et al. (2015); Lei et al. (2015); Li et al. (2015a); Li et al. (2015b); Kim et al. (2016a); Lee and Kim (2016); Yu (2016); Zhao et al. (2016b); Abadie et al. (2017); Chen et al. (2017a); Chen et al. (2017b); Chung et al. (2017b); Lee et al. (2017); Feng et al. (2018a); Lee et al. (2018b); Lee et al. (2018c); Udo and Takeda (2018); Yu et al. (2018a); Yu et al. (2018c); Lee et al. (2019); Liu et al. (2019c); Liu et al. (2019d); Wang et al. (2019b); Wu et al. (2019d); Kim and Lee (2020); Liu (2020); Liu and Chen (2020); Yu et al. (2020). Southeast Asia: Giuliani et al. (2016); Dau et al. (2017); Vu and Ranzi (2017); Mehvar et al. (2018). South Asia: Wijetunge (2014); Ahmed et al. (2016b); Jevrejeva et al. (2016); Patankar and Patwardhan (2016); Abadie et al. (2017); Aslam et al. (2017); Chiba et al. (2017); Mishra et al. (2017); van der Geest (2017); Chhogyel and Kumar (2018); Jevrejeva et al. (2018); Leng and Hall (2019); Bahinipati (2020); Bahinipati and Patnaik (2020); Khan et al. (2020); Bhowmik et al. (2021). Central Asia: Groll et al. (2015); Babagaliyeva et al. (2017); Otto et al. (2017). North Asia: Gleick (2014); Hjort et al. (2018); Tschakert et al. (2019). West Asia: Mantyka-Pringle et al. (2015); Pal and Eltahir (2016); Ghomian and Yousefian (2017); Gohari et al. (2017); Ashrafzadeh et al. (2019b); Bierkens and Wada (2019); Houmsi et al. (2019); Mosavi et al. (2020).
(a) For definitions on losses and damages and limits, see Cross-Chapter Box LOSS in Chapter 1.
Risk insurance approaches and tools have significantly evolved during recent years. The emphasis has been mainly on mitigating the adverse selection and moral hazard that have been the limitations of traditional area-based crop insurance approaches (He et al., 2019). This has been achieved by shifting the indemnity calculations on to the specific weather parameters and developing a weather index (Greatrex et al., 2015; Fischer, 2019). Technological applications in the development of insurance products have seen significant progress, including that of the blockchain and smart contracts (Gatteschi et al., 2018). There are technological developments in loss estimation, which has been a major limitation in the traditional insurance approaches in the past that either delayed the indemnity payment or misjudged the losses. Application of multi-model and multi-stage decision support systems has begun to make crop loss assessments for insurance more efficient (Aggarwal et al., 2020). Technological applications also include remote sensing (Di et al., 2017) and mobile phone app technologies (Meena et al., 2018) to provide accurate and quick damage assessments, and application of Internet-based indemnity approvals have enabled quick payment of indemnities (OECD, 2017b).
As against financing post-disaster relief and reconstruction, which has been the norm of disaster management for decades in Asia, the evolution of ex-ante risk financing in the form of risk insurance has seen a steady rise globally and in Asia. The rise in popularity for risk financing in general and insurance in specific stem from the observation that governments have recognised the burden of mainly financing the post-disaster relief and reconstruction only (Juswanto and Nugroho, 2017; UNESCAP, 2018c; ADB, 2019), and from the realisation of cost savings and efficiency that risk financing for risk mitigation brings overall risk reduction (high agreement , medium evidence). As a result, a gamut of risk-financing instruments have been introduced to finance DRR and CCA initiatives in Asia among which risk insurance has gained prominence for it provides a low-cost and easy option for individuals, provides an opportunity for the governments to effectively engage the private sector in implementation and has the ability to inculcate risk-aware decision making at various levels (high agreement , medium evidence) (Hazell and Hess, 2017; UNESCAP, 2018c).
Several Asian countries, including India, the Philippines and China, have a significant experience of offering agricultural insurance against typhoons, droughts and floods (Yang, 2018). For the most part, these insurance systems have followed a traditional indemnity-based insurance which faces several challenges in implementation including moral hazard and adverse selection, disagreements and delays in crop-damage assessments that relied upon crop-cutting experiments, often leading to a delay in processing indemnity payments, costly insurance premiums and poor insurance expansion (high agreement , robust evidence) (Patnaik and Swain, 2017; Ghosh et al., 2019). Other factors contributing to poor penetration of insurance include limited awareness on the importance of insurance, and poor access.
To tackle the problem of costly insurance premiums, governments have subsidised the premiums (Ghosh et al., 2019). Premium subsidies have been reported to undermine the ability to convey the real cost of risks by the insured (price distortion), and have encouraged adverse selection and moral hazard (Nguyen and Jolly, 2019). On the contrary, subsidies have been suggested to address the issue of adverse selection associated with the insurance (Zhao et al., 2017c).
Despite the fact that the insurance programmes are able to obtain high participation rates due to subsidised premiums, their impact on farmers’ income seems to be insignificant especially under the conditions of low indemnities, low guarantee and wide coverage (Zhao et al., 2016a). The subsidy burden of insurance on national governments is found to be significant with an estimated equivalent of 6 billion USD spent by China alone on insurance (Hazell et al., 2017). In addition, the insurance programmes in Asian countries are reporting higher producer claim ratios, and often governments have to spend more than the money being transferred to the insured through the insurance programmes (Hazell et al., 2017).
To address the issues associated with traditional indemnity insurance, efforts have been made to develop weather-index insurance in Asia that bases the payouts on the rainfall or temperature index, rather than on the direct damage measurements. The parametric insurance products help avoid the delays in insurance payouts as they are based on modelled risks, rather than actual damage measurements, and control the adverse selection and moral hazard, although basis risks could be increased due to improper matching of payouts with the index (De Leeuw et al., 2014). Index insurance is known to promote public–private partnerships that in turn will enhance the efficiency of overall programme delivery (Hazell and Hess, 2017). Several countries, including India, Bangladesh, Thailand, Indonesia, Myanmar and the Philippines, either are currently piloting or expanding the weather-index insurance (Surminski and Oramas-Dorta, 2014; Tyagi and Joshi, 2019). Index insurance is constantly expanding with an estimated 194 million farmers already enrolled in China and India, which is much lower than the potential number of farmers it can reach (Hazell et al., 2017).
Few significant bottlenecks that are limiting the scaling up of weather-index insurance include lack of reliable weather data, low density of weather stations leading to high basis risk, and limited data on damage and hazard for parametric modelling of the insurance (Shirsath et al., 2019). Several innovations are being tried and tested to overcome the limitations associated with the index insurance which include developing multiscale index insurance, application of remote sensing, smartphone-based near-surface remote sensing and building insurance based on vegetation indices instead of relying on weather data alone (Hufkens et al., 2019). Alternative indices, such as the NDVI, are being tested for their applications in designing index-based insurance in India (IFAD, 2017). Agro-meteorology-based statistical analysis and crop growth modelling have been suggested to calibrate and rectify faulty weather indices (Shirsath et al., 2019; Zhu et al., 2019). Establishing automatic weather stations can improve data accuracy while preventing the delay in acquiring the weather data (Sinha and Tripathi, 2016). These technological applications have already started finding space within insurance programmes designed by national governments in Asia. For example, the government of India has released new operational guidelines for the application of new technologies such as drones, remote sensing and mobile phone apps in implementation of the national agricultural insurance, which is the third largest insurance in the world (Department of Agriculture, 2019).
Despite these developments, several issues still seem to hinder the penetration of insurance in Asia. Issues such as lack of sufficient choices, lack of clear model, lack of legal support, limited or absence of proper monitoring and evaluation, and limited data for underwriters to properly evaluate claims have been suggested (Nguyen and Jolly, 2019). Low interest among the potential buyers due to unaffordable insurance premiums, lack of provision for partial-loss claim settlement, big hassles in the claim settlement process and lack of timely settlement of claims are reported (Parappurathu et al., 2017). In addition, insurance has been reported to have expanded the coverage of cash crops at the expense of drought-resistant subsistence crops with effects on natural capital and a potential increase in farmer’s vulnerability to market price fluctuations (Müller et al., 2017).
Regional catastrophic insurance pools have also received attention in Asia. With the formation of Southeast Asia Disaster Risk Insurance Facility (Haraguchi and Lall, 2019), the regional insurance pool has been introduced in Southeast Asia, initially being piloted in Lao PDR and Myanmar and to be expanded to the rest of the ASEAN region. Regional catastrophic insurance allows vulnerable countries to buffer climatic shocks by diversifying the risks beyond country boundaries.
Social protection (SP) encompasses initiatives that involve transfer income or assets to the poor, protect the vulnerable against risks to their livelihood, and enhance the social status and rights of the marginalised (Béné et al., 2014; Kothari, 2014). Social protection offers a wide range of instruments (e.g., cash transfers, insurance products, pension schemes and employment guarantee schemes) that can be used to support households that are exposed to climate changes (Bank, 2015). It also presents an opportunity to develop inclusive comprehensive risk management strategies to address L&D from climate change as well as a means to CCA (Aleksandrova, 2019).
Social protection programmes assist individuals and families, especially the poor and vulnerable, cope with crises and shocks, finds jobs, improve productivity, invest in the health and education of their children, and protect the ageing population (Bank, 2018b). Social protection that is well designed and implemented in a more long-term approach can enhance human capital and productivity, reduce inequalities, build resilience and empowerment, and end the inter-generational cycle of poverty (medium evidence, medium agreement ) as indicated from various experiences in the region such as (a) cash transfer programmes in Indonesia (Kwon and Kim, 2015), (b) the Benazir Income Support Programme in Pakistan (Watson et al., 2017), (c) the Chars Livelihoods Programme in Bangladesh (Pritchard et al., 2015) and (d) Minsei-in designated volunteer social workers in Japan (Boeckmann, 2016). A key consideration in strengthening resilience through SP programmes is to design with climate and disaster risk considerations in mind and implement in close synergy with existing programmes, such as on sustainable livelihoods, EWS and financial inclusion (Coirolo et al., 2013; Bank, 2018a).
Asia is already the most disaster-prone region in the world, with over 200,000 lives lost and almost 1 billion people affected by storms and floods alone between 2005 and 2014, while a heatwave in North and Central Asia in 2010 killed 56,000 people (United Nations, 2015). Climate change is increasing the frequency and intensity of these sudden and slow-onset disasters, among them, hydrological changes in major river basins where 1.5 billion people live (such as the Indus, Ganges, Brahmaputra, Mekong, Yellow, Yangtze, Tarim, Amu and Syr Darya rivers) (Bank, 2017a). According to the latest estimates of the International Labour Organisation (ILO), 55% of the global population (around 4 billion people) remain without any SP benefits, and the SP coverage gap is highest in Africa (82.2%) and the Asia–Pacific (61%) (ILO, 2017b).
Risks are generally amplified for people without SP or essential infrastructure and services, and for people with limited access to land and quality housing, especially those in exposed areas and informal settlements without secure tenure (ESCAP, 2017). Stateless people are disproportionately affected by climate change and disasters as they tend to reside in hazard-prone areas and their statues as non-citizens often limits access to assistance (Connell, 2015). The three main types of SP are: (a) social safety nets (also known as social assistance), which include conditional and unconditional cash transfers, public work programmes, subsidies and food stamps; (b) social insurance, which consists of contributory pensions and contributory health insurance; and (c) labour market measures, which include instruments such as unemployment compensation (Bank, 2018b). The potential for an integrated adaptive SP is not yet harnessed by policymakers in tackling the structural causes of vulnerability to climate change (Tenzing, 2019). Public works programmes (i.e., India’s Mahatma Gandhi National Rural Employment Guarantee Act, MGNREGA) should take into account climate risk in planning and support development of community assets to increase collective resilience.
Aligning SP with climate-change interventions is an attempt to develop more durable pathways out of poverty and climate vulnerability; examples from MGNREGA depicting the attempt to align through a mainstreaming approach has helped women and their households (Adam, 2015; Steinbach et al., 2016). On another note, the Catastrophe Insurance Framework, the first model introduced in Shenzen, China, provides timely relief for citizens and operates as a safety net, particularly for the poorest residents who do not have disposable income to cover the costs associated with bodily injuries arising from disasters (Telesetsky and He, 2016). The Department of Labour and Employment’s Integrated Livelihood and Emergency Employment Programme in the Philippines is part of the recovery efforts after Typhoon Haiyan, providing short-term wage employment, and facilitates entrepreneurship for people affected by natural calamities and economic shocks (Bank, 2018b).
In each of these instances, governments are using SP to protect populations suffering from climate change or are adversely affected by structural, pro-climate economic reforms (Hallegatte et al., 2015). However, additional research is still needed and new tools need to be developed to inform policy design and support the implementation of ‘green’ SP, as well as to measure the net-welfare impacts of such policies (Canonge, 2016). In order to enhance SP programmes, one of the cross-cutting issues is to discuss the linkages between gender roles and responsibilities, food security, agricultural productivity and the mediating role that SP programmes can have (Jones et al., 2017). Social protection has a potentially important role to play in contributing to food security and agricultural productivity in a gender-responsive way (Holmes and Jones, 2013). As such, experience from Challenging the Frontiers of Poverty Reduction: Targeting the Ultra Poor programme in Bangladesh has promoted social innovation by creating social and economic values, fostering microenterprises, increasing food security and fostering inclusive growth, all while empowering ultra-poor women (Emran et al., 2014; Mahmuda et al., 2014). Although there is increasing evidence that SP programmes are having a positive impact in terms of reducing vulnerability in women’s everyday lives (Jones et al., 2017), the transformative impact of these programmes is rare due to limitations in recognising women’s access to productive inputs and resources (Tanjeela and Rutherford, 2018; Cameron, 2019).
On the other hand, poor governance practices affect delivery of SP programmes and the ability of beneficiary households to reap the benefits from such support (Sijapati, 2017). In Nepal, a closer look at public expenditure shows that about 60% of the SP budget is used by social insurance programmes that predominantly consist of public-sector pensions (Babken Babajanian, 2014; Koehler, 2014). Towards this end, more effort is needed to improve its existing programmes so that there is an equality of opportunities, along with secured human rights. The example from Nepal’s Child Grant is an indicative of an incremental approach to social policy (Garde et al., 2017). Meanwhile, in the Philippines, despite the existence of flagship national interventions that cover a significant number of people in need and have clear and robust implementation rules, there are still many programmes with overlapping mandates and target population, and several gaps in their monitoring systems (Bank, 2018b).
Having an integrated SP information system would allow policymakers to better monitor inputs, outputs and outcomes (e.g., who the beneficiaries are, what they are receiving, at what frequency, what the existing gaps are) (OECD, 2017a; Samad and Shahid, 2018). Based on evidence from the assessments of three countries (Mongolia, Nepal and Vietnam), the political and institutional arrangements (i.e., the software) is as important as the technical fixes (i.e., the hardware) in the success of using information and communication technology for delivering SP programmes (ADB, 2016). By 2050, climate-induced migration will likely be a major policy aspect of the rural–urban nexus as slow-onset impacts of climate change in sub-Saharan Africa, South Asia and Latin America will likely force over 143 million people to migrate within their national borders (Kumari Rigaud, 2018). This will have major implications for SP systems, and therefore national SP strategies should be designed to anticipate and address climate-induced internal mobility (Schwan and Yu, 2017). For instance, it does not offer a solution for maintaining Indigenous cultures which are often strongly affected by, or even disrupted by, climate change (Olsson, 2014). Hence, an effective approach needs to combine different policy instruments to support protection, adaptation and migration (O’Brien et al., 2018).
Evidently, SP has been financed typically through the combination of government tax revenues and official development assistance, and the challenges of the increasing frequency and intensity of natural and economic crises are straining these traditional financial sources (Durán-Valverde, 2020). In this context, innovative financing schemes are seen as critical to achieve the sustainable financing of SP (Asher, 2015; UNICEF, 2019) via social and solidarity economy, as seen in women’s autonomous adaptation measures in precautionary savings and flood preparedness in Nepal (Banerjee et al., 2019), and self-help groups as development intermediaries (Anderson, 2019). Still, there are constraints of SP to reach those who are most vulnerable to climate change and other hazards due to their legal status, such as the fact that attention to forcibly displaced populations within the SP field has been limited (Sabates-Wheeler, 2019).
Government SP can attenuate the negative impacts in facing disasters, depending on the differences in political systems and the focus put on sociopolitical measures (medium evidence, medium agreement ), not only in restoring livelihoods but also in easing mental burdens faced by rural households in developing countries (Dalton et al., 2016; Kosec and Mo, 2017; Liebenehm, 2018). However, limited government capacities and fiscal feasibility may impede the expansion and effective implementation of SP as developing countries need further support to design, adjust and implement SP schemes effectively (Klonner, 2014; Schwan and Yu, 2017). Most countries have comprehensive strategies for both SP and climate change, but few have attempted to align them, as in practice they remain in separate institutional homes, governed by their own intra-sector coordination groups and funding channels (Steinbach et al., 2016; Bank, 2018b). Thus, significant knowledge gaps remain in terms of understanding the potential of SP to build long-term resilience to climate change (Ulrichs et al., 2019). Future efforts should be geared to develop climate-responsive SP policies that consider a broad range of issues including urbanisation and migration, the impact of green policies on the poor, access to essential health care and risks to socially marginalised groups (Aleksandrova, 2019). Along with strengthening links to climate information and EWS, finance for enabling SP systems to address climate-related shocks and stresses dynamically needs to be scaled up (Kuriakose et al., 2013; Ulrichs et al., 2019).
Asian areas with the least capacity to respond, such as the Himalayan region and densely populated deltas, are hit first and hardest by climate impacts (De Souza et al., 2015; Khan, 2017). Acknowledging the limitations in terms of capacity and coping mechanisms towards climate change, education, training and awareness building is central to sustaining long-term capacity building (Clemens et al., 2016). Education has a lot more to offer in terms of improvements in addressing climate change, particularly in the climate hotspots of Asia where mostly poor, disadvantaged communities vulnerable to climate change reside (Mani et al., 2018). In particular, when disseminated, climate-change awareness and information need more explanation (Steg et al., 2014; Wi and Chang, 2018; Cho, 2020). In addition, international and national support through institutions and financing is critical for successful capacity building (Hemachandra, 2019), which must be designed for the long term and be self-sustaining (Gustafson et al., 2018). National ownership by recipient countries and members of communities of capacity-building efforts is key to ensuring their success (Roberts and Pelling, 2016; Mikulewicz, 2017).
The need to develop tailored climate communication and education strategies for individual nations as public awareness and risk perceptions towards climate change vary greatly (medium evidence, high agreement ) (Lee et al., 2015a). Improving on, and investing in, basic education, climate literacy and location-based strategies of climate change are vital to enhance public engagement, societies’ adaptive capacity and support for climate action (Lutz et al., 2014c; Hu and Chen, 2016). As stated in the IPCC Special Report 1.5°C, sustainable development has the potential to significantly reduce systemic vulnerability, enhance adaptive capacity and promote livelihood security for poor and disadvantaged populations (Roy et al., 2018). Hence, various concepts are introduced to foster awareness, understanding, knowledge, participation as well as commitment towards managing climate change in a sustainable manner. One such concept is education for sustainable development (ESD), which is aimed at integrating the principles and practices of sustainable development in all aspects of education, and training individuals who will contribute to the realisation of a more sustainable society (Kitamura, 2017).
Climate-change education (CCE) is also now addressed in the context of ESD and allows for learners to understand the causes and consequences of climate change, and teaches them how to take action (Mochizuki and Bryan, 2015). Both ESD and CCE are gaining broader attention, for instance, in China (Han, 2015) and the Republic of Korea (Sung, 2015); however, development of policies and implementation of initiatives regarding ESD and CCE still face a handful of challenges which require a strong political will and consensus of key stakeholders (Læssøe and Mochizuki, 2015). Effective communication on CCE particularly for younger-generation engagement is also essential, as they are our future leaders as climate change is an inter-generational equity issue (Corner et al., 2015). Action for Climate Empowerment of Article 6 of the UNFCCC target youth as a major group for effective engagement in the formulation and implementation of decisions on climate change (UNFCCC, 2015). Increasing attention from countries in Asia, such as Thailand and India, will encourage innovative ways to provide adequately in educating and engaging youth in climate-change issues (Narksompong and Limjirakan, 2015; Dür and Keller, 2018).
An integrated approach to knowledge about climate change embraces both the importance in bridging knowledge of climate science and respecting IKLK, and should be at the heart of any effort to educate citizens to have a deeper understanding of the causes and consequence of climate change in a holistic manner (Aswani et al., 2018). Indigenous Peoples, comprising about 6% of the global population, play a crucial role in the fight against climate change for two interlinked reasons. First, they have a particular physical and spiritual relationship with land, water and associated ecosystems, and tend to be among the most vulnerable group to climate change (Magni, 2017). Second, they have a specialised ecological and traditional knowledge relevant to finding the best solutions to climate change (Rautela and Karki, 2015). Indigenous knowledge systems and resource management practices are important tools for both mitigating and adapting to climate change (Fernandez-Llamazares et al., 2015). Indigenous knowledge is increasingly recognised as a powerful tool for compiling evidence of climate change over time (Ahmed et al., 2016a). Knowledge of CCA and DRR provide a range of complementary approaches in building resilience and reducing the vulnerability of natural and human systems to the impacts of climate change and environmental hazards (Mall et al., 2019). The adaptation dimension involves developing knowledge and utilising existing IKLK, skills and dispositions to better cope with already evident and looming climate impacts (Aghaei et al., 2018). It is also important to ensure inclusive efforts in DRR across different nations and communities as well as increasing skills and capacities of women towards DRR efforts (Alam and Rahman, 2014; Drolet et al., 2015; Islam et al., 2016b; Reyes and Lu, 2016; Hemachandra et al., 2018). More effective and efficient teaching and learning strategies, as well as collaborative networks, are needed to increase preparedness and DRR activities across various levels of community (Oktari et al., 2015; Takahashi et al., 2015; Tuladhar et al., 2015b; Shiwaku et al., 2016; Gampell et al., 2017).
Table 10.6 shows education and capacity-building aspects affecting adaptation by sub-region examples.
Table 10.6 | Education and capacity-building aspects affecting adaptation by sub-regions examples
Sub-region | Sectors | Adaptation interventions | Education and capacity-building factors affecting adaptation | Supporting references |
North Asia | Human well-being | PEEX (Pan Eurasian Experiment) originating from a bottom-up approach by the science communities aiming at resolving major uncertainties in Earth system science and global sustainability issues concerning the Arctic and boreal pan-Eurasian regions, as well as China | Educating the next generation of multidisciplinary experts and scientists capable of finding tools in solving future environmental, socioeconomic and demographic development problems of the Arctic and boreal regions, as well as China | Pan Eurasian regions, as well as China (Kulmala et al., 2015) |
West Asia | Agriculture | Smallholder farmers’ vulnerability assessment | High level of education, more human capacity and adaptive capacity, less vulnerability | Iran (Jamshidi et al., 2019) |
Central Asia | Agriculture, water resources and energy | Carrying out the selection and cultivation of drought-tolerant, salt-tolerant crops, preservation of the upper watershed of the rivers, improving climate resilience of hydro-facilities | Placing the focal point for the preparation and implementation of programmes for climate change at the regional level, increasing capacity of professionals in targeted areas and networking between them, and strengthening institutional, technical and human resources to promote adaptation and research in fields of climate and hydrological investigations, geographic information systems, environmental impact assessment, and protection and re-cultivation of lands | Kazakhstan, Tajikistan and Kyrgyzstan mountain societies in Central Asia (Schmidt-Vogt et al., 2016; Xenarios et al., 2019) |
South Asia | Agriculture | Productivity, net crop income, improvement in livelihoods and food security | Farmers’ education, easy access to farm advisory services, weather forecasting and marketing information | Pakistan (Abid et al., 2016) |
Passive adaptation in agricultural and farming practices implicitly to cope with climate change | Increasing knowledge on climate change so that concrete steps can be taken in dealing with perceived climate changes | India (Tripathi and Mishra, 2017) | ||
Having farmers’ perceptions shape knowledge, and vice versa on climate change | Age, education, occupation, farming experience, knowledge about coping strategies (all significantly related to farmers’ perceptions about climate change) | India (Aslam Ansari, 2018) | ||
Disaster risk reduction | Local institutions’ preparedness and capacity for managing disaster at the local scale | Capacity building, technical support and financial capacity, as well as adopting a proactive approach, to achieve a higher level of disaster preparedness | Pakistan (Shah et al., 2019) | |
Southeast Asia | Agriculture | Farming cultural practices adopted to minimise production losses due to extreme weather | Small-scale farmers’ attendance at climate-change training to enhance adaptive capacity | Vietnam (Trinh et al., 2018) |
Removing farmers’ barriers to adopting adaptation measures, and provide funds and timely information | Knowledge of crop variety, increasing educational outreach and communicating climate-change-related information to increase the likelihood of employing adaptive strategies | China (Zhai et al., 2018) | ||
Making farmers in rural, under-resourced communities in the Lower Mekong basin aware of how climate change will affect them | Scientific findings which can be merged with local knowledge at a community level to help raise awareness, and knowledge gaps on both which can be filled for better understanding and adaptation planning | Cambodia, Lao PDR, Vietnam and Thailand (USAID, 2015; Gustafson et al., 2018) | ||
Coastal areas | Reducing households’ vulnerability due to variation in socioeconomic and livelihoods assets | Increasing resilience by establishing effective an communication system, improving knowledge on climate change | Vietnam and Indonesia (Nanlohy et al., 2015; Huynh and Stringer, 2018) | |
Disaster risk reduction | Capacity building through learning labs on disaster risk management for sustainable development (DRM-SD) | Transfer of learning initiatives to provide approach guidelines and innovative mechanisms for DRM practitioners who will have the know-how and potential for leadership in DRM-SD | Four ASEAN countries: Malaysia, Vietnam, Lao PDR and Cambodia (Ahmad Shabudin et al., 2017) | |
East Asia | Disaster risk reduction | Conducting community participation and disaster education so that people can take action in disaster management | Educational-resilience system tested and revised through experiences from past disasters; recognising and integrating gender perspectives into mainstream disaster management; ‘school-based recovery concept’ facilitating short-term recovery and the longer-term community building needs, which can also help communities in building new networks and solving chronic social problems | Japan (Matsuura and Shaw, 2014; Saito, 2014; Shiwaku et al., 2016) |
Bridging Indigenous knowledge and scientific knowledge | In efforts to solve real-world problems, engaging first with those local communities that are most affected, beginning with the perspective of Indigenous knowledge and then seeking relevant scientific knowledge | Paying attention to the Indigenous perception of a hazard and risk with the aim of increasing the effectiveness of projects implemented by practitioners who might need to communicate risks in the future; empowering the younger generation to ensure continuity of Indigenous cultures and their linked ecosystems |
Capacity building at national and local levels still needs to address gaps in research and practice, such as impacts and results of different preparedness measures (Alcayna et al., 2016). Ad-hoc and localised documentations and monitoring of efforts to build adaptive capacities has rendered it difficult to assess success (Cinner et al., 2018). Recommendations for strengthened capacity building are sometimes made or understood in isolation from the underlying structural issues shaping vulnerability, or without adequately recognising the political relationships that mediate the ways in which particular technical interventions result in differentiated outcomes for different groups (Archer and Dodman, 2015). Thus, design- and decision-based tools, such as rapid assessment for community resilience to climate change as well as rapid approach to monitor the effectiveness of aid projects, support the community-based adaptation to climate change to analyse using a multi-dimensional approach, procedural, distributional, rights and responsibilities (Nkoana et al., 2018; Jacobson et al., 2019).
As a model of communication and engagement, citizen science has the potential to promote individual and collective climate-change action (Groulx et al., 2017). More than information provision is needed to mobilise public action on climate change (Kyburz-Graber, 2013). Citizen science links communication and engagement in a manner that holds important lessons on ways to promote collective responses to climate (Wals et al., 2014; Bonney et al., 2016). The power of science-based citizen engagement lies in citizen group contribution in drawing upon their local knowledge to enrich the knowledge base required for management decisions (Sayer et al., 2015). Scientific evidence may be less attuned to the complexity of local realities in managing climate change; thus, citizen science has the potential in bridging this gap and has many advantages for climate mitigation and adaptation practice and policy (Ford et al., 2016). While citizen science uses citizens as policy-passive objects for research in conducting measurements for big datasets, citizen social science is gaining momentum where it repositions citizens as central co-learners who can widen the climate-science evidence base to achieve a more holistic understanding for the benefit of all (Kythreotis et al., 2019).
Climate resilient development pathways (CRDPs) are ‘trajectories that strengthen sustainable development and efforts to eradicate poverty and reduce inequalities while promoting fair and cross-scalar adaptation to and resilience in a changing climate’ (Roy et al., 2018). Moving beyond a business-as-usual scenario, CRDPs involve not only adaptation and mitigation choices but also sustainable development implications and societal transformation (Roy et al., 2018). This basic understanding of CRDPs explicitly reflects that climate action (mitigation and adaptation) and sustainable development are fundamentally integrated and interdependent.
There is high confidence that currently implemented climate action in Asia (such as climate-smart agriculture, ecosystem-based DRR and investing in urban blue–green infrastructure) can meet adaptation, mitigation and SDGs simultaneously, presenting opportunities for climate resilient development (CRD). However, there also exist significant barriers to CRD such as fragmented, reactive governance; inadequate evidence on which actions to prioritise and how to sequence them; and finance deficits. Some Asian countries and regions offer solutions to overcome these barriers: through use of advanced technologies (in situ observation and remote sensing, a variety of new sensor technologies, citizen science, AI and machine learning tools); regional partnerships and learning; improved forecasting capabilities; and better risk awareness (high confidence).
Asian countries are repeatedly identified as the most vulnerable to climatic risks with key sectors such as agriculture, cities and infrastructure, and terrestrial ecosystems expected to see high exposure to multiple hazards (Section 10.3). Owing to rapid development and large populations, Asian countries have large and growing GHG emissions: in 2018, five of the top ten emitters in the world were Asian–China (1), India (3), Japan (5), the Republic of Korea (8) and Indonesia (10) (Friedlingstein et al., 2019)–although it is critical to note that per-capita emissions and cumulative emissions are relatively lower than in developed economies (Raupach et al., 2014). However, in the 2020 Sustainability Index and Dashboard, only two Asian countries made it into the top 30 countries in the world: Japan (17) and the Republic of Korea (20) (Sachs et al., 2020). Finally, Asia has varied capacities to adapt with high heterogeneity in adaptation progress across the region.
Given this context of high risks, growing emissions and varied adaptive capacities in Asia, CRDPs can enable (a) reducing existing vulnerability and inequality, (b) sustainable development and meeting the SDGs and (c) managing multiple and often concurrent risks, including climate-change and disaster risks. Potentially, combinations of adaptation and mitigation options will be required to lead to CRD (see Figure 18.1 on CRDPs ), and some of them are shown in Table 10.7. For example, climate-smart agriculture strengthens food security (SDG 2, Zero Hunger) (Aggarwal et al., 2019); urban disaster management, such as the Jakarta Disaster Risk Reduction Education Initiative, contributes to SDG 11 (Sustainable Cities) (Ajibade et al., 2019).
Table 10.7 | Adaptation options that can have mitigation and SDG synergies and trade-offs, providing opportunities for the triple wins necessary for climate resilient development pathways
Adaptation option | Mitigation impacts (H/M/L/NA)a | Implications on SDGs | References | |
Positive | Negative | |||
Wetland protection, restoration | Medium synergy Carbon sequestration through mangroves | SDGs 8, 14, 15 | Southeast Asia: Griscom et al. (2020) | |
Solar drip irrigation | High synergy Shift to cleaner energy | SDGs 2, 7, 12 | SDG 10 | South Asia: Alam et al. (2020) |
Climate-smart agriculture | High synergyb No till practices and improved residue management can reduce soil carbon emissions. | SDGs 2, 12 | South Asia: Aggarwal et al. (2019); Aryal et al. (2020b); Aryal et al. (2020a); Tankha et al. (2020) | |
Southeast Asia: Chandra and McNamara (2018) | ||||
Integrated smart water grids | High synergy Reduced energy needs for supplying water | SDGs 6, 9, 11, 13 | Asia: Kim (2017) | |
Disaster risk management (including early warning systems)c | Not applicable | SDGs 9, 11 | SDGs 5, 10 | South and Southeast Asia: Ajibade et al. (2019); Herbeck and Flitner (2019); Aryal et al. (2020b); Mishra (2020) |
Asia: Iturrizaga (2019) | ||||
Bhutan: Sovacool et al. (2012) | ||||
The Philippines: Grefalda et al. (2020) | ||||
Carefully planned resettlement and migration (including decongestion of urban areas) | Inadequate evidence to make an assessment | SDGs 8, 10, 11 | SDGs 6, 10, 11 | Asia: Arnall (2019) |
South Asia: Maharjan et al. (2020) | ||||
The Philippines: Estoque et al. (2020) | ||||
Nepal: Banerjee et al. (2019) | ||||
Aquifer storage and recovery | Low synergy | SDGs 6, 12 | Saudi Arabia: Lopez et al. (2014) | |
South and Southeast Asia: Hoque et al. (2016) | ||||
Nature-based solutions in urban areas: green infrastructure (including urban green space, blue–green infrastructure) | High synergy Blue–green infrastructure acts as a carbon sink | SDGs 3, 9, 11 | Japan: Mabon et al. (2019) | |
The Philippines: Estoque et al. (2020) | ||||
China: Byrne et al. (2015); Zhang et al. (2020a) | ||||
Taiwan, Province of China: Mabon and Shih (2018) | ||||
Singapore: Liao (2019); Radhakrishnan et al. (2019) | ||||
Coastal green infrastructure | High synergy | SDGs 9, 11, 13, 14, 15 | Bangladesh: Sovacool et al. (2012); Chow (2018); Zinia and (McShane, 2018) | |
Southeast Asia: Koh and Teh (2019); Herbeck and Flitner (2019) | ||||
Asia: Giffin et al. (2020) |
Notes:
(a) Expert judgment.
(b) The CCA options in the agriculture sector include soil management, crop diversification, cropping system optimisation and management, water management, sustainable land management, crop pest and disease management, and direct seeding of rice (Aryal et al., 2020b). Other specific agricultural practices that have adaptation and mitigation synergies include between-tillage and residue management, alternate wetting and drying, site-specific nutrient management, crop diversification for less-water-intensive crops, such as maize, and improved livestock management (Aryal et al., 2020a).
(c) Risk management strategies in agriculture include crop insurance, index insurance, social networking and community-based adaptation, collective international action and integrated agro-meteorological advisory services (Aryal et al., 2020b).
The following subsections examine CRDPs through three approaches that are particularly important in Asia and have a large body of evidence to assess implications for adaptation, mitigation and sustainable development. The three illustrative approaches are: (a) disaster risk management and adaptation synergies, (b) the food–water–energy nexus and (c) poverty alleviation and meeting equity goals.
There is growing evidence on the interconnectedness of extreme weather, climate change and disaster impacts (Asia, 2017; Reyer, 2017). In Asia, climate-related disasters have become more recurrent and destructive in terms of both economic and social impacts (Bhatt et al., 2015; Aich et al., 2017; Vij et al., 2017). Projections of increasing frequency, intensity and severity of climate-related disasters call for better integration of CCA and DRR (Sapountzaki, 2018) in policy development to address risks efficiently (Rahman et al., 2018) and to promote sustainable development pathways for reduced vulnerability and increased resilience (Seidler et al., 2018). Connecting CCA and DRR efforts in both policy and practice continue to be a challenge, however, because the convergence of national policy and planning processes on CCA and DRR within Asia is in its early stages (Cousins, 2014) and structural barriers persist (Mall et al., 2019). Both CCA and DRR have developed as separate policy domains because of the different temporal and spatial scales considered, the diversity of actors involved, the policies and institutional frameworks adopted and the differences in tools and methodological approaches used. This has resulted in the CCA and DRR communities, and the knowledge and research they produce to support planning and decision making, not always being well connected (Street et al., 2019).
Climate risk management in Asia is approached by focusing on hazards that are associated with extremes (i.e., extreme weather events with increased frequency and severity) as well as climate- and weather-related events. For example, farming has been affected by climatic variability and change in a wide variety of ways that include an increase in drought periods and intensity, a shortage of irrigation water availability, an increase in flooding and landslides, pest infestation of crops, a rising number of crop diseases, the introduction of invasive species and crop weeds, land degradation and an overall reduction in crop yields (Khanal et al., 2019). Estimation of the number of daily patients of heat-related illness based on the weather data and newly introduced metrics shows that the effects of age, successive days and heat adaptation are key variables (Kodera et al., 2019).
Because most developing countries in Asia are highly vulnerable to the impacts of climate change due to a number of factors, many studies have focused on understanding vulnerability, for instance, gendered vulnerability at the micro scale, which limits capacity to respond to both climatic and socioeconomic stressors (Ferdous and Mallick, 2019); vulnerability of urban poor communities due to the interaction of environmental and social factors (e.g., low incomes, gender, migrant status) and heightens the impacts of climate change on the poor (Porio, 2014); social–ecological vulnerability where a degraded environment influences hazard patterns and vulnerability of people (Depietri, 2020); and livelihood vulnerability due to perceived climate risks and adaptation constraints (Fahad and Wang, 2018; Hossain et al., 2020).
Risk assessments have been undertaken for different hazards such as flood (Al Saud, 2015; Al-Amin et al., 2019; Jha and Gundimeda, 2019; Mahmood et al., 2019; Zhang et al., 2019e), drought (Guo et al., 2019; Mainali et al., 2019), rainfall-induced landslide (Li et al., 2019b), SLR (Imaduddina and Subagyo, 2014; Suroso and Firman, 2018) and heat stress (Onosuka et al., 2019), among others, as well as environmental assessment, for example, in coastal zones (Islam and Zhang, 2019). Different types of strategies for climate risk management have also been studied including: (a)in situ adaptation through ecosystem- and community-based adaptation (Jamero et al., 2017); (b) managed retreat or relocation (Buchori et al., 2018; Doberstein et al., 2020); (c) planned sheltering in flood zones (Wu et al., 2019c); (d) sustainable livelihoods that consider long-term CCA measures of farmers and fishermen (Nizami et al., 2019; Shaffril et al., 2019); (e) coastal afforestation through mangrove plantation (Rahman et al., 2018); (f) management of ecosystem services to mitigate the effects of droughts (Tran and Brown, 2019); (g) pre-investments, including holistic assessment of the basin (Inaoka et al., 2019); (h) institutionalisation, where entry points are identified in efforts to build resilience (Lassa, 2019) and adaptive governance (Walch, 2019); and (i) linking science and local knowledge (Mehta et al., 2019; van Gevelt et al., 2019).
The sectors to which CCA and DRR have been linked are varied. For example, Filho et al. (2019) assessed adaptive capacity and resilience to climate change based on urban poverty, infrastructure and community facilities; Mabon et al. (2019) looked at adaptation via the built environment, green roofs, and citizen and private-sector involvement in smaller-scale greening actions; Lama and Becker (2019) focused on adaptation to reduce risk in conflicts; Banwell et al. (2018) studied the link between health, CCA and DRR; and Izumi et al. (2019) surveyed science, technology and innovation for DRR. Vulnerable groups have been given much attention, such as farmers (Afroz, 2017; Gupta et al., 2019; Jawid and Khadjavi, 2019; Khanal et al., 2019; Shi et al., 2019a), women (Goodrich et al., 2019; Hossain et al., 2019; Udas et al., 2019), and children, elderly and refugees (Asia, 2017). Finally, issues identified include water resource management (Bhatta et al., 2019; Sen et al., 2019; Zhang et al., 2019a); food security (Aleksandrova et al., 2016; Le, 2016); disaster governance (Blanco, 2015); climate boundary shifting wherein impacts of climate change are significant for crop production, soil management and DRR (Talchabhadel and Karki, 2019); and institutional dimensions of CCA (Cuevas, 2018; Islam et al., 2020).
Case studies on climate risk management and integrated CCA and DRR actions highlight some key lessons including: an integrated and transformative approach to CCA, which focuses on long-term changes in addressing climate impacts (Filho et al., 2019); adoption of an adaptive flood risk management framework incorporating both risk observation and public perceptions (Al-Amin et al., 2019); a holistic approach and non-structural and technological measures in flood control management (Chan, 2014); monitoring of changes in urban surface water in relation to changes in seasons, land covers, anthropogenic activities and topographic characteristics for managing watersheds and urban planning (Faridatul et al., 2019); removing ‘gender blindness’ in agrobiodiversity conservation and adaptation policies (Ravera et al., 2019); understanding uncertainties in CCA and DRR at the local level (van der Keur et al., 2016; Djalante and Lassa, 2019 ); promoting the use of IKLK alongside scientific knowledge (Hiwasaki et al., 2014); and increasing information, education and communication activities, and capacity development on DRR at the local level (Tuladhar et al., 2015a).
Several studies also have identified enabling conditions to effectively implement CCA and DRR actions. In the Arab region of Asia (ARA), the following are critical: capacity building to develop knowledge and awareness; mainstreaming CCA and DRR in the national strategies and policies (e.g., water and environmental strategies); empowering the role of CCA and DRR actors, notably women and rural societies; adopting lessons learned from regions with physical characteristics similar to those of ARA; establishing forecasting and prediction platforms that are supported by advanced monitoring technologies (e.g., remote sensing); and encouraging universities and research centres to develop studies on CCA and DRR. In Southeast Asia, laws and policies, institutional and financial arrangements, risk assessment, capacity building, and planning and implementation are entry points in integrating CCA and DRR (Lassa and Sembiring, 2017; Agency, 2018). According to Cutter et al. (2015), holistic solutions and integrated approaches, rigorous risk research that shows coherent science-based assessment and knowledge transfer from research to practice, and aligned targets on disaster risk management, climate change and sustainable development targets, are critical. Social capital and SP measures could promote pro-poor and gender-responsive adaptation as well as socially inclusive policies (Dilshad et al., 2019; Yari et al., 2019). Community-based approaches could allow local perceptions of climate change and experience of place to be included in planning (Dujardin et al., 2018; Dwirahmadi et al., 2019; Widiati and Irianto, 2019), and multi-stakeholder participation could engage various actors such as the private sector in CCA and DRR. Furthermore, multi-level climate governance could benefit from vertical and horizontal interactions at different levels and layers in the city (Zen et al., 2019). To mainstream and secure funding commitments, CCA and DRR could be integrated into national development plans and sectoral long-term plans (Ishiwatari and Surjan, 2020; Rahayu et al., 2020; Rani et al., 2020 b).
Adaptation follows knowledge on risks, and literature exists that systematically identifies and characterises exposure and vulnerability, but gaps still exist. Decision making under uncertainty is challenged by the lack of data for adapting to current and uncertain future climate, the different perceptions of risk, and the potential solutions across different cultures and languages (van der Keur et al., 2016). Lack of downscaled climatic data, diverse institutional structures, and missing links in policies, are among the challenges in South Asia (Mall et al., 2019). In agriculture, there are gaps in the use of advanced farming techniques such as drought-resistant crops, and information on climate change to support farming households in making adaptation decisions (Akhtar et al., 2019; Khanal et al., 2019; Ullah et al., 2019). Better understanding of effective water management is crucial due to conflicts for shared water in ARA (Shaban and Hamze, 2017; UNDP, 2018). For delta regions, gaps identified are methodologies and approaches appropriate for understanding social vulnerability at various scales, pathways required for adaptation policy and response in the deltas that transcend development, and the lessons from implemented policy and how practice can build on these lessons in the deltas, among others (Lwasa, 2015). Approaches in tackling the challenges of climate change and disasters in the cities of developing countries could be better understood, and shared between cities so they can learn from one another (Filho et al., 2019).
Food, energy, water and land are vital elements for sustainable development as well as enhancing resilience to both climatic and non-climatic shocks. All these resources are highly vulnerable to climate change (Sections 10.3.1, 10.3.4). Poor people are most affected due to changes in resources availability and accessibility. Food, water and energy security are interconnected (Bizikova et al., 2013; Ringler et al., 2013; Rasul, 2014; Chang et al., 2016; Ringler et al., 2016). Although adapting to climate change is one of the core components of the global, regional, national and subnational agendas, the focus of adaptation action has remained sectoral. Undermining the interlinkages of food, energy and water security may increase trade-offs between sectors or places, which may lead to maladaptation (Barnett and O’Neill, 2010; Howells et al., 2013; Lele et al., 2013). Therefore, focusing on the nature of trade-offs and synergies across the food–water–energy nexus for integrated management of resources is a potential strategy for adaptation to both climatic and non-climatic challenges (Bhaduri et al., 2015; Zaman et al., 2017). Due to its importance to the Paris Agreement and SDGs, the food–water–energy nexus approach has gotten increasing attention in terms of capturing synergies and minimising trade-offs in this interconnected system, which is also critical for enhancing adaptation together (Bazilian et al., 2011; Lawford et al., 2013; UNESCAP, 2013; FAO, 2014; Rasul and Sharma, 2014; Taniguchi et al., 2017a; Sukhwani et al., 2019; Sukhwani et al., 2020).
The food–water–energy nexus can be evaluated in the two-way interactions between water–food, water–energy and food–energy (Taniguchi et al., 2017a). The water–energy nexus includes water for energy and energy for water (Rothausen and Conway, 2011; Hussey and Pittock, 2012; Byers et al., 2014), the water–food nexus includes water for food and the impact of food production on water (Hoekstra and Mekonnen, 2012) and the energy–food nexus includes energy consumption for food production and food crops for biofuel production (Tilman et al., 2009). The food–water–energy–land nexus has diverse implications at the sub-regional level in Asia. The increase in the water-supply gap raises questions about the sustainability of the main mode of electricity generation in South Asia. Thermal power generation and hydropower generation are both threatened by water shortages in South Asia (Luo, 2018b; Mitra et al., 2021). Furthermore, policy-mismatch-driven anthropogenic causes lead to unsustainable water use for food production in India. For example, subsidised electricity supply for watering agriculture plays a key role in losing groundwater’s buffer capacity against the various changes including climate variabilities (Badiani et al., 2012; Mitra, 2017). In the Mekong River basin of Southeast Asia, massive and rapid export-oriented hydropower development will have direct implications on regional food security and livelihoods through a major negative effect on the aquatic ecosystem (Baran and Myschowoda, 2009; Dugan et al., 2010; Arias et al., 2014). Similarly, in Central Asia, the shifting of water storage for irrigation to power development has increased risks on reliable water supply and quality of water (Granit et al., 2012). Deforestation-driven agro-environmental changes have led to a decreased forest water supply, an increased irrigation water demand and a negative effect on cropland stability and productivity (Lim et al., 2017a; Lim et al., 2019b).
Many challenges remain in both scientific research and policy actions at the global, regional, national and subnational levels. The scientific challenges include data, information and knowledge gaps in understanding the food, energy, water and land interlinkages, and lack of systematic tools to address trade-offs (Liu et al., 2017a). Until very recently, implementation of the food–energy–water nexus focused primarily on technical solutions, whereas governance (i.e., the institutions and processes governing the food–energy–water nexus) has not received much consideration (Scheyvens and Shivakoti, 2019). At the policy end, the common challenges for implementation of the water–energy–food–land nexus are absence of sectoral coordination (Pahl-Wostl, 2019), the influence of political priorities on decisions and lack of processes for scientific knowledge to shape decisions, lack of capacity to understand interlinkages between sectors, lack of multi-stakeholder engagement in planning and decision-making processes, and lack of incentive mechanisms and adequate finance to support the approach (Bao et al., 2018; Scheyvens and Shivakoti, 2019).
Social justice focuses on the justice-related implications of social and economic institutions, examined in different ways such as distributional justice (distribution of benefits and burdens across different societal groups), procedural justice (the design of just institutions and processes for decision making), inter-generational justice (duties of justice to future generations) and recognitional justice (recognition of historical inequality) (Thaler et al., 2017). Climate change is affecting every aspect of our society and economy; thus, it is pertinent to understand the interactions between social justice and climate-change impacts (Tol, 2018), in particular, focusing on how vulnerability to various impacts is created, maintained and distributed across geographic, social, demographic and economic dimensions (Bulkeley et al., 2014; Schlosberg and Collins, 2014; Van de Vliert, 2014; Burke et al., 2016). For instance, environmental and health consequences of climate change, which disproportionately affect low-income countries and poor people in high-income countries, profoundly affect human rights and social justice (Levy and Patz, 2015). Furthermore, great concern is expressed about the plight of the poor, disadvantaged and vulnerable populations when it comes to climate, but not in other policy domains (Winters, 2014).
Evidence is increasing on the importance of focusing on environmental sustainability, and relieving poverty and social injustice are not conflicting aims; in fact, there is a further need for mainstreaming such approaches in order to respond to the climate-change challenge in a socially just manner (Mayrhofer and Gupta, 2016). These non-conflicting aims are described as co-benefits as reiterated in the IPCC reports as a central concept that refers to ‘the positive effects that a policy or measure aimed at one objective might have on other objectives, irrespective of the net effect on overall social welfare’ (IPCC, 2014b). Better understanding of how social justice affects, and is affected by, efforts to build adaptive capacity will be crucial to avoiding unintended, and even perverse, outcomes. For example, on the Andaman coast of Thailand, responses to climate-change trends and events tended to be reactive rather than proactive, making already vulnerable people even more vulnerable and undermining their capacity to adapt in the future (Bennett et al., 2014). Different forms of inequality, moreover, render some groups more vulnerable than others to damage from climate hazards. In Mumbai, India, for example, the houses of poorer families required repeated repairs to secure them against flood damage, and the cumulative cost of those repairs consumed a greater proportion of their income than for richer populations (UN, 2016). Building the resilience of vulnerable groups requires strong community and government institutions that can support efforts to cope with devastating events, offering SP and social development initiatives to support at-risk or vulnerable groups (Drolet et al., 2015). In addition, agencies need to consider how they can best work in ways which potentially support longer-term positive change to gender roles and relations. For example, post-disaster activities must build and resource women’s resilience and adaptive capacity in practice and challenge the constraints that impinge on their lives (Sadia et al., 2016; Sohrabizadeh et al., 2016; Hadiyanto et al., 2018; Yumarni and Amaratunga, 2018; Alam and Rahman, 2019).
Insights from the environmental justice literature show that an overemphasis on emission reductions at national levels obscures the negative impacts on disadvantaged communities, including low-income communities (Burch and Harris, 2014). The issue of social justice and adaptation is particularly relevant because of the politics that drive how adaptation and recovery efforts, as well as investments, are targeted towards specific populations, places and capacities (Klinsky et al., 2017). Hence, climate justice and equity need to be highlighted more explicitly in integrative approaches to mitigation and adaptation (medium evidence, high agreement ) (Moellendorf, 2015; Henrique KP, 2020).
The term ‘climate justice’ is used to problematise global warming in ethical and political contexts. It does so by employing the concepts of environmental justice and social justice to examine inequalities and violation of human collective rights in relation to climate-change impacts (Ghimire, 2016).
At the heart of climate-justice concerns lies the asymmetry that those who have contributed least to the problem of climate change (i.e., GHG emissions) are the ones who will be affected by its adverse impacts the most. It is about sharing the burden and benefits equitably (a) among developed and developing countries in the context of historical responsibility, and (b) within nations to uplift the marginalised and affected populations who have contributed the least to the problem in the contexts of per-capita equity and local vulnerability (Joshi, 2014; Chaudhuri, 2020; Shawoo, 2020).
An ethical analysis of the climate regime reveals an abidingly strong interconnection between economic circumstances, geopolitical power and the justice claims that nations can assert in negotiations (Okereke, 2016). Events within the climate regime highlight the importance of questioning the extent to which claims of justice can ever be truly realised in the context of international regimes of environmental governance, as well as how much concerns for justice are motivated by other concerns such as relative economic gains or geopolitical objectives (Sikor, 2014).
The global land rush and mainstream climate-change narratives have broadened the ranks of state and social actors concerned about land issues while strengthening those opposed to social-justice-oriented land policies (Borras, 2018). The five deep social reforms (redistribution, recognition, restitution, regeneration and resistance) of socially just land policy are necessarily intertwined. But the global land rush amid deepening climate change calls attention to the linkages, especially between the pursuit of agrarian justice, on the one hand, and climate justice, on the other. Here, the relationship is not without contradictions and warrants increased attention as both unit of analysis and object of political action. Understanding and deepening agrarian-justice imperatives in climate politics, and understanding and deepening climate-justice imperatives in agrarian politics, is needed more than ever in the ongoing pursuit of alternatives. For example, the intersection between land grabs and climate-change mitigation politics in Myanmar has created new political opportunities for scaling up, expanding and deepening the struggles towards ‘agrarian climate justice’(Sekine, 2021).
Climate-change-related risks are projected to increase progressively at 1.5°C, 2°C and 3°C of global warming in many parts of Asia. Heat stress and water deficit are affecting human health and food security. Risks due to extreme rainfall and sea level rise are exacerbated in vulnerable Asia.
Climatologically, the summer surface air temperature in South, Southeast and Southwest Asia is high, and its coastal area is very humid. In these regions, heat stress is already a medium risk for humans. Large cities are warmer by more than 2°C compared with the surroundings due to heat island effects, exacerbating heat stress conditions. Future warming will cause more frequent temperature extremes and heatwaves especially in densely populated South Asian cities, where working conditions will be exacerbated and daytime outdoor work will become dangerous. For example, incidence of excess heat-related mortality in 51 cities in China is estimated to reach 37,800 deaths per year over a 20-year period in the mid-21st century (2041–2060) under the RCP8.5 scenario.
Asian glaciers are the water resources for local and adjacent regions. Glaciers are decreasing in Central, Southwest, Southeast and North Asia, but are stable or increased in some parts of the Hindu Kush Himalaya region. The glacier melt water in the southern Tibetan Plateau increased during 1998–2007, and the total amount and area of glacier lakes has increased during recent decades. In the future, maximum glacial runoff is projected in High Mountain Asia. Glacier collapses and surges, together with glacier lake outburst flood due to the expansion of glacier lakes, will threaten the securities of the local and down streaming societies.
With much of the Asian population living in drought-prone areas, water scarcity is a prevailing risk across Asia through water and food shortage leading to malnutrition. Populations vulnerable to impacts related to water are going to increase progressively at 1.5°C, 2°C and 3°C of global warming. Aggravating drought condition is projected in Central Asia. Water quality degradation also has profound impact on human health.
Extreme rainfall causes floods in vulnerable rivers. Observed changes in extreme rainfall vary considerably by region in Asia. Extreme rainfall events (such as heavy rainfall >100 mm per day) have been increasing in South and East Asia. In the future, most of East and Southeast Asia are projected to experience more intense rainfall events as soon as by the middle of the 21st century. In those regions, the flood risk will become more frequent and severe. It is estimated that over one-third of Asian cities and about 932 million urban dwellers are living in areas with high risk of flooding.
Sea level rise is continuing. Higher than the global mean sea level rise is projected on Asian coasts. Storm surge and high wave by tropical cyclones of higher intensity are high risk for a large number of Asian megacities facing the ocean: China, India, Bangladesh, Indonesia and Vietnam have the highest numbers of coastal populations exposed and thus are most vulnerable to disaster-related mortality.
Changes in terrestrial biome have been observed that are consistent with warming, such as an upward move of treeline position in mountains. Climate change, human activity, lightning and quality of forest governance and management have increased wildfire severity and area burned in North Asia in recent decades. Changes in marine primary production also have been observed: a decrease up to 20% over the past six decades in the western Indian Ocean, due to ocean warming and stratification, has restricted nutrient mixing. The risk of irreversible loss of many ecosystems will increase with global warming.
The likelihood of adverse impacts to agricultural and food security in many parts of developing Asia will progressively escalate with the changing climate. The potential of total fisheries production in South and Southeast Asia is also projected to decrease.
Figure FAQ10.1.1 | Key risks related to climate change in Asia.
Mirroring the heterogeneity across Asia, different countries and communities are undertaking a range of reactive and proactive strategies to manage risk in various sectors. Several of these adaptation actions show promise, reducing vulnerability and improving societal well-being. However, challenges remain around scaling up adaptation actions in a manner that is effective and inclusive while simultaneously meeting national development goals.
Asia exhibits tremendous variation in terms of ecosystems, economic development, cultures and climate risk exposure. Mirroring this variation, households, communities and governments have a wide range of coping and adaptation strategies to deal with changing climatic conditions, with co-benefits for various non-climatic issues such as poverty, conflict and livelihood dynamics.
Currently, Asian countries have rich evidence on managing risk, drawing on long histories of dealing with change. For example, to deal with erratic rainfall and shifting monsoons, farmers make incremental shifts such as changing what and when they grow or adjusting their irrigation practices. Communities living in coastal settlements are using Early warning systems to prepare for cyclones or raising the height of their houses to minimise flood impacts. These types of strategies, seen across all Asian sub-regions, based on local social and ecological contexts, are termed autonomous adaptations that occur incrementally and help people manage current impacts.
Currently and in the future, Asia is identified as one of regions most vulnerable to climate change, especially on extreme heat, flooding, sea level rise and erratic rainfall. All these climatic risks, when overlaid on existing development deficits, show us that incremental adaptation will not be enough; transformational change is required. Recognising this, at subnational and national levels, government and non-governmental actors are also prioritising planned adaptation strategies which include interventions like ‘climate-smart agriculture’ as seen in South and Southeast Asian countries, or changing labour laws to reduce exposure to heat as seen in West Asia. These are often sectoral priorities governments lay out through national or subnational policies and projects, drawing on various sources of funding: domestic, bilateral and international. Apart from these planned adaptation strategies in social systems, Asian countries also report and invest in adaptation measures in natural systems such as expanding nature reserves to enable species conservation or setting up habitat corridors to facilitate landscape connectivity and species movements across climatic gradients.
Overall, the fundamental challenges that Asia will see exacerbated under climate change are around water and food insecurity, poverty and inequality, and increased frequency and severity of extreme events. In some places and for some people, climate change, even at 1.5°C and more so at 2°C, will significantly constrain the functioning and well-being of human and ecological systems. Asian cities, villages and countries are rising to this current and projected challenge, albeit somewhat unevenly.
Some examples of innovative adaptation actions are China’s ‘Sponge Cities’ which are trying to protect ecosystems while reducing risk for people, now and in the future. Another example is India’s Heat Action Plans that are using ‘cool roofs’ technologies and awareness-building campaigns to reduce the impacts of extreme heat. Across South and Southeast Asia, climate-smart agriculture programmes are reducing GHG emissions associated with farming while helping farmers adapt to changing risks. Each country is experimenting with infrastructural, nature-based, technological, institutional and behavioural strategies to adapt to current and future climate change with local contexts shaping both the possibility of undertaking such actions as well as the effectiveness of these actions to reduce risk. What works for ageing cities in Japan exposed to heatwaves and floods may not work for pastoral communities in the highlands of Central Asia, but there is progress on understanding what actions work and for whom. The challenge is to scale current adaptation action, especially in the most exposed areas and for the most vulnerable populations, as well as move beyond adapting to single risks alone (i.e., adapt to multiple coinciding risks such as flooding and water scarcity in coastal cities across South Asia or extreme heat and flash floods in West Asia). In this context, funding and implementing adaptation is essential, and while Asian countries are experimenting with a range of autonomous and planned adaptation actions to deal with these multiple and often concurrent challenges, making current development pathways climate resilient is necessary and, some might argue, unavoidable.
Table FAQ10.2.1 | System transitions, sectors and illustrative adaptation options
System transitions | Sectors | Illustrative adaptation options |
Energy and industrial systems | Energy and industries | Diversifying energy sources Improving energy access, especially in rural areas Improving resilience of power infrastructure Rehabilitation and upgrading of old buildings |
Land and ecosystems | Terrestrial and freshwater ecosystems | Expanding nature reserves Assisted species migration Introducing species to new regions to protect them from climate-induced extinction risk Sustainable forest management including afforestation, forest fuel management, fire management |
Ocean and coastal ecosystems | Marine protected areas Mangrove and coral reef restoration Integrated coastal zone management Sand banks and structural technologies | |
Freshwater | Integrated watershed management Transboundary water management Changing water access and use practices to reduce/manage water demand High-efficiency water-saving technology Aquifer storage and recovery | |
Agriculture, fisheries and food | Changing crop type and variety, improving seed quality Water storage, irrigation and water management Climate-smart agriculture Early warning systems and use of climate information services Fisheries management plans (e.g., seasonal closures, limited fishing licenses, livelihood diversification) | |
Urban systems | Cities and settlements | Flood protection measures and sea walls sustainable land-use planning and regulation Protecting urban green spaces, improving permeability, mangrove restoration in coastal cities Planned relocation and migration Disaster management and contingency planning |
Key infrastructures | Climate-resilient highways and power infrastructure Relocating key infrastructure | |
Health systems | Reducing air pollution Changing dietary patterns |
Indigenous People, comprising about 6% of the global population, play a crucial role in managing climate change for two important reasons. First, they have a physical and spiritual connection with land, water and associated ecosystems, thus making them most vulnerable to any environmental and climatic changes. Second, their ecological and local knowledge are relevant to finding solutions to climate change.
Indigenous knowledge and local knowledge (IKLK) play an important role in the formulation of adaptation governance and related strategies (IPCC 2007), and best quality, locality-specific knowledge can help address the serious lack of education on climate change and uncertainties surrounding quality, salience, credibility and the legitimacy of the available knowledge base.
Key findings across Asia underline the importance of building, sustaining and augmenting local capacity through addressing inadequacies in terms of resource base, climate-change awareness, government–community partnerships and vulnerability assessment. Furthermore, inclusion of as well as related practices will improve adaptation planning and decision-making processes concerning climate change.
In climate-sensitive livelihoods, an integrated approach informed by science that examines multiple stressors, along with IKLK, appears to be of immense value. For instance, in building farmers’ resilience, enhancing CCA, ensuring cross-cultural communication and promoting local skills, Indigenous People’s intuitive thinking processes and geographic knowledge of remote areas are very important.
There is also a widespread recognition that IKLK are important in ensuring successful ecosystem-based adaptation (EbA). However, this recognition requires more practical application and translation into IKLK-driven EbA projects. For instance, in the Coral Triangle region, creating historical timelines and mapping seasonal calendars can help to capture IKLK while also feeding this information into climate science and climate adaptation planning. Identifying indigenous crop species for agriculture by using IKLK is already identified as an important way to localise climate adaptation: an example is Bali’s vital contribution of moral economies to food systems which have long built resilience among groups of communities in terms of food security and sovereignty, even with the challenges faced due to modernising of local food systems.
Many of the pressing problems of Asia, including water scarcity, rapid urbanisation, deforestation, loss of species, rising coastal hazards and agricultural loss can be effectively negated, or at least minimised, through proper adoption of suitable science and technological methods. Climate-change adaptation is greatly facilitated by science, technology and innovation. This ranges from application of existing science, new development on scientific tools and methods, application of IKLK and citizen sciences. Deploying Knowledge Quality Assessment Tool found significant co-relation between science-based and IKLK framing would help to address, acknowledge and utilise by an integrated approach the wisdom of IKLK, a valuable asset for climate adaptation governance. The IKLK-based environmental indicators need to be seen as part of a separate system of knowledge that coexists with, but is not submerged into, another conventional knowledge system.
In the context of education and capacity development of climate change, an integrated approach of embracing both the importance of climate science and IKLK is acknowledged. The IKLK is increasingly recognised as a powerful tool for compiling evidence of climate change over time. Such as knowledge of CCA and DRR provide a range of complementary approaches in building resilience and reducing the vulnerability of natural and human systems. Developing knowledge and utilising existing IKLK, skills and dispositions to better cope with already evident and looming climate impacts. Engaging communities in the process of documenting and understanding long-term trends and practices will enable both IKLK as well as Western scientific assessments of climate change to contribute in designing appropriate climate adaptation measures.
Asian countries are testing ways to develop in a climate-resilient manner to meet the goals related to climate change and sustainable development simultaneously. Some promising examples exist, but the window of opportunity to put some of these plans in place is small and closing fast, highlighting the need for urgent action across and within countries.
In order to achieve the multiple goals of CCA, mitigation and sustainable development, critical are rapid, system transitions across (a) energy systems, (b) land and ecosystems and (c) urban and infrastructural systems. This is especially important across Asia, which has the largest population exposed to current climate risks and high sub-regional diversity, and where risks are expected to rise significantly and unevenly under higher levels of global warming. However, such transformational change is deeply challenging because of variable national development imperatives; differing capacities and requirements of large, highly unequal and vulnerable populations; and socioeconomic and ecological diversity that requires very contextual solutions. Furthermore, issues such as growing transboundary risks, inadequate data for long-term adaptation planning, finance barriers, uneven institutional capacity and non-climatic issues, such as increasing conflict, political instability and polarization, constrain rapid, transformational action across systems.
Despite these challenges, there are increasing examples of actions across Asia that are meeting climate adaptation goals and SDGs simultaneously, such as through climate-smart agriculture, disaster risk management and NbS. To enable these system transitions, vertical and horizontal policy linkages, active communication and cooperation between multiple stakeholders, and attention to the root causes of vulnerability are essential. Furthermore, rapid systemic transformation can be enabled by policies and finances to incentivise capacity building, new technological innovation and diffusion. The effectiveness of such technology-centred approaches can be maximised by combining them with attention to behavioural shifts such as by improving education and awareness, building local capacities and institutions, and leveraging IKLK.
Obviously, time is of the essence. If system transitions are delayed, there is high confidence that climatic risks will increase human and natural system vulnerability, as well as increase inequality and erode the achievements of multiple SDGs. Thus, urgent systemic change that is suited to national and subnational social–ecological contexts across Asia is imperative.
Figure FAQ10.4.1 | Adaptation options, mitigation impacts and implications on Sustainable Development Goals.
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