Editing IPCC:AR6/WGII/Chapter-10 (section)

== 10.6 Climate Resilient Development Pathways ==

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=== 10.6.1 Climate Resilient Development Pathways in Asia ===

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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--2018|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--2018|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 ( [[#10.3|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--2019|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--2014|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--2020|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--2019|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

{| class="wikitable"
|-
! rowspan="2"| Adaptation option

! rowspan="2"| Mitigation impacts (H/M/L/NA) a

! colspan="2"| Implications on SDGs

! rowspan="2"| References

|-
! Positive

! Negative

|-
| Wetland protection, restoration

| ''Medium synergy''

Carbon sequestration through mangroves

| SDGs 8, 14, 15

|
| Southeast Asia: [[#Griscom--2020|Griscom et al. (2020)]]

|-
| Solar drip irrigation

| ''High synergy''

Shift to cleaner energy

| SDGs 2, 7, 12

| SDG 10

| South Asia: [[#Alam--2020|Alam et al. (2020)]]

|-
| rowspan="2"| Climate-smart agriculture

| rowspan="2"| ''High synergy'' b

No till practices and improved residue management can reduce soil carbon emissions.

| rowspan="2"| SDGs 2, 12

| rowspan="2"|
| South Asia: [[#Aggarwal--2019|Aggarwal et al. (2019)]] ; [[#Aryal--2020b|Aryal et al. (2020b)]] ; [[#Aryal--2020a|Aryal et al. (2020a)]] ; Tankha et al. (2020)

|-
| Southeast Asia: [[#Chandra--2018|Chandra and McNamara (2018)]]

|-
| Integrated smart water grids

| ''High synergy''

Reduced energy needs for supplying water

| SDGs 6, 9, 11, 13

|
| Asia: [[#Kim--2017|Kim (2017)]]

|-
| rowspan="4"| Disaster risk management (including early warning systems) c

| rowspan="4"| Not applicable

| rowspan="4"| SDGs 9, 11

| rowspan="4"| SDGs 5, 10

| South and Southeast Asia: Ajibade et al. (2019); [[#Herbeck--2019|Herbeck and Flitner (2019)]] ; [[#Aryal--2020b|Aryal et al. (2020b)]] ; [[#Mishra--2020|Mishra (2020)]]

|-
| Asia: [[#Iturrizaga--2019|Iturrizaga (2019)]]

|-
| Bhutan: [[#Sovacool--2012|Sovacool et al. (2012)]]

|-
| The Philippines: [[#Grefalda--2020|Grefalda et al. (2020)]]

|-
| rowspan="4"| Carefully planned resettlement and migration (including decongestion of urban areas)

| rowspan="4"| Inadequate evidence to make an assessment

| rowspan="4"| SDGs 8, 10, 11

| rowspan="4"| SDGs 6, 10, 11

| Asia: [[#Arnall--2019|Arnall (2019)]]

|-
| South Asia: [[#Maharjan--2020|Maharjan et al. (2020)]]

|-
| The Philippines: [[#Estoque--2020|Estoque et al. (2020)]]

|-
| Nepal: [[#Banerjee--2019|Banerjee et al. (2019)]]

|-
| rowspan="2"| Aquifer storage and recovery

| rowspan="2"| ''Low synergy''

| rowspan="2"| SDGs 6, 12

| rowspan="2"|
| Saudi Arabia: Lopez et al. (2014)

|-
| South and Southeast Asia: [[#Hoque--2016|Hoque et al. (2016)]]

|-
| rowspan="5"| Nature-based solutions in urban areas: green infrastructure (including urban green space, blue–green infrastructure)

| rowspan="5"| ''High synergy''

Blue–green infrastructure acts as a carbon sink

| rowspan="5"| SDGs 3, 9, 11

| rowspan="5"|
| Japan: [[#Mabon--2019|Mabon et al. (2019)]]

|-
| The Philippines: [[#Estoque--2020|Estoque et al. (2020)]]

|-
| China: Byrne et al. (2015); Zhang et al. (2020a)

|-
| Taiwan, Province of China: [[#Mabon--2018|Mabon and Shih (2018)]]

|-
| Singapore: [[#Liao--2019|Liao (2019)]] ; [[#Radhakrishnan--2019|Radhakrishnan et al. (2019)]]

|-
| rowspan="3"| Coastal green infrastructure

| rowspan="3"| ''High synergy''

| rowspan="3"| SDGs 9, 11, 13, 14, 15

| rowspan="3"|
| Bangladesh: [[#Sovacool--2012|Sovacool et al. (2012)]] ; [[#Chow--2018|Chow (2018)]] ; Zinia and (McShane, 2018)

|-
| Southeast Asia: [[#Koh--2019|Koh and Teh (2019)]] ; [[#Herbeck--2019|Herbeck and Flitner (2019)]]

|-
| Asia: [[#Giffin--2020|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--2020b|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--2020a|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--2020b|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.

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=== 10.6.2 Disaster Risk Reduction and Climate-Change Adaptation Linkages ===

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==== 10.6.2.1 Point of Departure ====

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There is growing evidence on the interconnectedness of extreme weather, climate change and disaster impacts ( [[#Asia--2017|Asia, 2017]] ; Reyer, 2017). In Asia, climate-related disasters have become more recurrent and destructive in terms of both economic and social impacts ( [[#Bhatt--2015|Bhatt et al., 2015]] ; [[#Aich--2017|Aich et al., 2017]] ; [[#Vij--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|Sapountzaki, 2018]] ) in policy development to address risks efficiently ( [[#Rahman--2018|Rahman et al., 2018]] ) and to promote sustainable development pathways for reduced vulnerability and increased resilience ( [[#Seidler--2018|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|Cousins, 2014]] ) and structural barriers persist ( [[#Mall--2019|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--2019|Street et al., 2019]] ).

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==== 10.6.2.2 Findings ====

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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--2019|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--2019|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|Porio, 2014]] ); social–ecological vulnerability where a degraded environment influences hazard patterns and vulnerability of people ( [[#Depietri--2020|Depietri, 2020]] ); and livelihood vulnerability due to perceived climate risks and adaptation constraints ( [[#Fahad--2018|Fahad and Wang, 2018]] ; [[#Hossain--2020|Hossain et al., 2020]] ).

Risk assessments have been undertaken for different hazards such as flood ( [[#Al%20Saud--2015|Al Saud, 2015]] ; [[#Al-Amin--2019|Al-Amin et al., 2019]] ; [[#Jha--2019|Jha and Gundimeda, 2019]] ; Mahmood et al., 2019; [[#Zhang--2019e|Zhang et al., 2019e]] ), drought ( [[#Guo--2019|Guo et al., 2019]] ; Mainali et al., 2019), rainfall-induced landslide ( [[#Li--2019b|Li et al., 2019b]] ), SLR ( [[#Imaduddina--2014|Imaduddina and Subagyo, 2014]] ; [[#Suroso--2018|Suroso and Firman, 2018]] ) and heat stress ( [[#Onosuka--2019|Onosuka et al., 2019]] ), among others, as well as environmental assessment, for example, in coastal zones ( [[#Islam--2019|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--2017|Jamero et al., 2017]] ); (b) managed retreat or relocation ( [[#Buchori--2018|Buchori et al., 2018]] ; [[#Doberstein--2020|Doberstein et al., 2020]] ); (c) planned sheltering in flood zones ( [[#Wu--2019c|Wu et al., 2019c]] ); (d) sustainable livelihoods that consider long-term CCA measures of farmers and fishermen ( [[#Nizami--2019|Nizami et al., 2019]] ; [[#Shaffril--2019|Shaffril et al., 2019]] ); (e) coastal afforestation through mangrove plantation ( [[#Rahman--2018|Rahman et al., 2018]] ); (f) management of ecosystem services to mitigate the effects of droughts ( [[#Tran--2019|Tran and Brown, 2019]] ); (g) pre-investments, including holistic assessment of the basin ( [[#Inaoka--2019|Inaoka et al., 2019]] ); (h) institutionalisation, where entry points are identified in efforts to build resilience ( [[#Lassa--2019|Lassa, 2019]] ) and adaptive governance ( [[#Walch--2019|Walch, 2019]] ); and (i) linking science and local knowledge ( [[#Mehta--2019|Mehta et al., 2019]] ; [[#van%20Gevelt--2019|van Gevelt et al., 2019]] ).

The sectors to which CCA and DRR have been linked are varied. For example, [[#Filho--2019|Filho et al. (2019)]] assessed adaptive capacity and resilience to climate change based on urban poverty, infrastructure and community facilities; [[#Mabon--2019|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--2019|Lama and Becker (2019)]] focused on adaptation to reduce risk in conflicts; [[#Banwell--2018|Banwell et al. (2018)]] studied the link between health, CCA and DRR; and [[#Izumi--2019|Izumi et al. (2019)]] surveyed science, technology and innovation for DRR. Vulnerable groups have been given much attention, such as farmers ( [[#Afroz--2017|Afroz, 2017]] ; [[#Gupta--2019|Gupta et al., 2019]] ; [[#Jawid--2019|Jawid and Khadjavi, 2019]] ; Khanal et al., 2019; [[#Shi--2019a|Shi et al., 2019a]] ), women ( [[#Goodrich--2019|Goodrich et al., 2019]] ; [[#Hossain--2019|Hossain et al., 2019]] ; [[#Udas--2019|Udas et al., 2019]] ), and children, elderly and refugees ( [[#Asia--2017|Asia, 2017]] ). Finally, issues identified include water resource management ( [[#Bhatta--2019|Bhatta et al., 2019]] ; Sen et al., 2019; [[#Zhang--2019a|Zhang et al., 2019a]] ); food security ( [[#Aleksandrova--2016|Aleksandrova et al., 2016]] ; [[#Le--2016|Le, 2016]] ); disaster governance ( [[#Blanco--2015|Blanco, 2015]] ); climate boundary shifting wherein impacts of climate change are significant for crop production, soil management and DRR ( [[#Talchabhadel--2019|Talchabhadel and Karki, 2019]] ); and institutional dimensions of CCA ( [[#Cuevas--2018|Cuevas, 2018]] ; [[#Islam--2020|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--2019|Filho et al., 2019]] ); adoption of an adaptive flood risk management framework incorporating both risk observation and public perceptions ( [[#Al-Amin--2019|Al-Amin et al., 2019]] ); a holistic approach and non-structural and technological measures in flood control management ( [[#Chan--2014|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--2019|Faridatul et al., 2019]] ); removing ‘gender blindness’ in agrobiodiversity conservation and adaptation policies ( [[#Ravera--2019|Ravera et al., 2019]] ); understanding uncertainties in CCA and DRR at the local level ( [[#van%20der%20Keur--2016|van der Keur et al., 2016]] ; [[#Djalante--2019|Djalante and]] [[#Lassa--2019|Lassa, 2019]] ); promoting the use of IKLK alongside scientific knowledge ( [[#Hiwasaki--2014|Hiwasaki et al., 2014]] ); and increasing information, education and communication activities, and capacity development on DRR at the local level ( [[#Tuladhar--2015a|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--2017|Lassa and Sembiring, 2017]] ; [[#Agency--2018|Agency, 2018]] ). According to [[#Cutter--2015|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--2019|Dilshad et al., 2019]] ; [[#Yari--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--2018|Dujardin et al., 2018]] ; [[#Dwirahmadi--2019|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--2019|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--2020|Ishiwatari and Surjan, 2020]] ; [[#Rahayu--2020|Rahayu et al., 2020]] ; [[#Rani--2020|Rani et al., 2020]] b).

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==== 10.6.2.3 Knowledge Gaps ====

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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%20der%20Keur--2016|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--2019|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--2019|Akhtar et al., 2019]] ; Khanal et al., 2019; [[#Ullah--2019|Ullah et al., 2019]] ). Better understanding of effective water management is crucial due to conflicts for shared water in ARA ( [[#Shaban--2017|Shaban and Hamze, 2017]] ; [[#UNDP--2018|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|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--2019|Filho et al., 2019]] ).

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=== 10.6.3 Food–Water–Energy Nexus ===

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==== 10.6.3.1 Point of Departure ====

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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--2013|Bizikova et al., 2013]] ; [[#Ringler--2013|Ringler et al., 2013]] ; [[#Rasul--2014|Rasul, 2014]] ; [[#Chang--2016|Chang et al., 2016]] ; [[#Ringler--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--2010|Barnett and O’Neill, 2010]] ; [[#Howells--2013|Howells et al., 2013]] ; [[#Lele--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--2015|Bhaduri et al., 2015]] ; [[#Zaman--2017|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--2011|Bazilian et al., 2011]] ; [[#Lawford--2013|Lawford et al., 2013]] ; [[#UNESCAP--2013|UNESCAP, 2013]] ; [[#FAO--2014|FAO, 2014]] ; [[#Rasul--2014|Rasul and Sharma, 2014]] ; [[#Taniguchi--2017a|Taniguchi et al., 2017a]] ; [[#Sukhwani--2019|Sukhwani et al., 2019]] ; [[#Sukhwani--2020|Sukhwani et al., 2020]] ).

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<span id="findings-8"></span>
==== 10.6.3.2 Findings ====

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The food–water–energy nexus can be evaluated in the two-way interactions between water–food, water–energy and food–energy ( [[#Taniguchi--2017a|Taniguchi et al., 2017a]] ). The water–energy nexus includes water for energy and energy for water ( [[#Rothausen--2011|Rothausen and Conway, 2011]] ; [[#Hussey--2012|Hussey and Pittock, 2012]] ; [[#Byers--2014|Byers et al., 2014]] ), the water–food nexus includes water for food and the impact of food production on water ( [[#Hoekstra--2012|Hoekstra and Mekonnen, 2012]] ) and the energy–food nexus includes energy consumption for food production and food crops for biofuel production ( [[#Tilman--2009|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--2021|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--2012|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--2009|Baran and Myschowoda, 2009]] ; [[#Dugan--2010|Dugan et al., 2010]] ; [[#Arias--2014|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--2012|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--2017a|Lim et al., 2017a]] ; [[#Lim--2019b|Lim et al., 2019b]] ).

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==== 10.6.3.3 Knowledge gaps ====

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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--2017a|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--2019|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|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--2018|Bao et al., 2018]] ; [[#Scheyvens--2019|Scheyvens and Shivakoti, 2019]] ).

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=== 10.6.4 Social Justice and Equity ===

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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--2017|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|Tol, 2018]] ), in particular, focusing on how vulnerability to various impacts is created, maintained and distributed across geographic, social, demographic and economic dimensions ( [[#Bulkeley--2014|Bulkeley et al., 2014]] ; [[#Schlosberg--2014|Schlosberg and Collins, 2014]] ; [[#Van%20de%20Vliert--2014|Van de Vliert, 2014]] ; [[#Burke--2016|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--2015|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--2016|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|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--2014|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|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--2015|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--2016|Sadia et al., 2016]] ; [[#Sohrabizadeh--2016|Sohrabizadeh et al., 2016]] ; [[#Hadiyanto--2018|Hadiyanto et al., 2018]] ; [[#Yumarni--2018|Yumarni and Amaratunga, 2018]] ; [[#Alam--2019|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--2014|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--2017|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|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|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|Joshi, 2014]] ; [[#Chaudhuri--2020|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|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|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|Sekine, 2021]] ).

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