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

==== 10.4.6.4 Adaptation in Cities Across Asia ====
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A review of urban adaptation in South, East and Central Asia found examples of 180 adaptation activities across 74 cities ( [[#Dulal--2019|Dulal, 2019]] ). Most adaptation actions in Asia are in the initial stages ( [[#Araos--2016|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|Dulal, 2019]] ), although the proportion of climate finance spent on disaster preparedness is not very high (as [[#Georgeson--2016|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--2015|Blok and Tschötschel, 2015]] ). Figure 10.8 shows risks and key adaptation options in select cities across Asia.

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[[File:d1da2e524a9884942611e779d1a12b91 IPCC_AR6_WGII_Figure_10_008.png]]

'''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|Dulal, 2019]] ; [[#Singh--2021b|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--2014|Friend et al., 2014]] ; [[#Gajjar--2018|Gajjar et al., 2018]] ; [[#Salim--2019|Salim et al., 2019]] ; [[#Chi--2020|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--2015|Lee and Painter, 2015]] ; [[#Dulal--2019|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|Shaw, 2019]] ) and transnational municipal networks ( [[#Fünfgeld--2015|Fünfgeld, 2015]] ) are emerging as important for knowledge brokering, capacity building and financing urban adaptation ( [[#Karanth--2014|Karanth and Archer, 2014]] ; [[#Chu--2017|Chu et al., 2017]] ; [[#Bazaz--2018|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--2016b|Shaw et al., 2016b]] ; [[#Ho--2017|Ho et al., 2017]] ); (b) sustainable land-use planning through zoning, developing building codes ( [[#Knowlton--2014|Knowlton et al., 2014]] ; [[#Nahiduzzaman--2015|Nahiduzzaman et al., 2015]] ; [[#Rahman--2016|Rahman et al., 2016]] ; [[#Ahmed--2019b|Ahmed et al., 2019b]] ); (c) ecosystem-based adaptation measures such as protecting urban green spaces, improving permeability, mangrove restoration in coastal cities, etc. ( [[#Brink--2016|Brink et al., 2016]] ; [[#Fink--2016|Fink, 2016]] ; [[#Yu--2018d|Yu et al., 2018d]] ); (d) relocation and migration out of risk-prone areas ( [[#McLeman--2019|McLeman, 2019]] ; [[#Hauer--2020|Hauer et al., 2020]] ; [[#Maharjan--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--2016a|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--2014|Anguelovski et al., 2014]] ; [[#Friend--2014|Friend et al., 2014]] ; [[#Knowlton--2014|Knowlton et al., 2014]] ), improving awareness ( [[#Knowlton--2014|Knowlton et al., 2014]] ), and putting local research and monitoring mechanisms in place ( [[#Lee--2015|Lee and Painter, 2015]] ) to enable adaptation. Figure 10.9 shows the effectiveness of select adaptation options in cities across Asia.

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[[File:31408e3b142daa24a2a2ceaffe41ad00 IPCC_AR6_WGII_Figure_10_009.png]]

'''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.

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===== 10.4.6.4.1 Infrastructural adaptation options =====

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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--2019|Hallegatte et al., 2019]] ; [[#Lu--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|Meerow, 2017]] ) through interventions such as improved highways and power plants, climate-resilient housing, improved water infrastructure and so forth ( [[#ADB--2014|ADB, 2014]] ).

* '''Power infrastructure:''' Adaptations in electricity systems include climate-resilient power infrastructure, particularly essential for coastal megacities such as Manila, Mumbai, Bangkok and Ho Chi Minh City ( [[#Meerow--2017|Meerow, 2017]] ; [[#Duy--2019|Duy et al., 2019]] ), which double as regional economic hubs and are home to tens of millions of people. In the Philippines, solar panels at water pumping stations are installed to operate and maintain a minimal capacity to pump water if the electricity grid were to break down ( [[#Stip--2019|Stip et al., 2019]] ).
* '''Water infrastructure:''' Sustainable water supply and resource management are key to urban adaptation through improved water service delivery, wastewater recycling and storm-water diversion ( [[#Deng--2015|Deng and Zhao, 2015]] ; [[#Xie--2017|Xie et al., 2017]] ; [[#Yu--2018d|Yu et al., 2018d]] ). Infrastructure-based adaptation options in urban water management include building water storage facilities, storm-water management and enhancing water quality improving permeability, managing runoff and enabling groundwater recharge. One example is of Shanghai (China), where infrastructural and policy incentives come together to enable adaptation: the city has been divided into 14 water conservancy zones, including 348 polder areas with 2517 km of dykes, 1499 pump stations and 2203 sluices ( [[#Yu--2018d|Yu et al., 2018d]] ). It also depends on a regional inundation control system, flood Early warning system and an emergency plan to deal with flood risk and mitigate waterlogging ( [[#Chen--2018e|Chen et al., 2018e]] ; [[#Yu--2018d|Yu et al., 2018d]] ). Another example is Ho Chi Minh City (Vietnam), where, given significant increases in area at risk of flooding under climate change, the city has invested in storm sewer upgradation, dike works, improving drainage and increasing the height of road embankments and minor bridges ( [[#Storch--2011|Storch and Downes, 2011]] ; [[#ADB--2014|ADB, 2014]] ; [[#Ho--2017|Ho et al., 2017]] ). These infrastructural interventions were complemented by designing an Early warning system to initiate flood mitigation procedures, such as isolating critical electrical and mechanical operating systems from water.
* '''Built infrastructure:''' Current built-infrastructure adaptation interventions are mostly reactive (e.g., strengthening housing units, using sandbags during flooding, storing of food, evacuation) rather than preventive (e.g., relocation, building multi-storey and stronger housing units), mainly due to limited resources within most vulnerable households for investing in proactive measures ( [[#Francisco--2019|Francisco and Zakaria, 2019]] ). For cities in North Asia seeing permafrost thawing, adequate land-use practices, permafrost monitoring, maintenance of infrastructure and engineering solutions (e.g., using thermosiphons) may temporarily offset the negative effects of permafrost degradation in small, economically vital areas, but are unlikely to have an effect beyond the immediate areas ( [[#Shiklomanov--2017b|Shiklomanov et al., 2017b]] ; Streletskiy, 2019). Importantly, thawing permafrost and GHG emissions create feedbacks where emissions amplify warming and drive additional thaw. Reducing these impacts through mitigation will reduce the need for adaptation significantly ( [[#Schaefer--2014|Schaefer et al., 2014]] ).
* '''Infrastructure and technology:''' Several infrastructural options employ technology, such as smart meters, to monitor water usage and service delivery, but these are differentially adopted across Asian sub-regions with higher adoption across East Asia. Examples include: the Yokohama smart city project in Japan, which has been smart eco-urbanism interventions since 2011 (e.g., energy saving and storage infrastructure, wastewater management, behavioural change towards renewable energy and low-carbon transportation) (IUC, 2019); the Tianjin Eco-city mega-project in China, which is testing a range of measures to meet urban sustainability goals in partnership with Singapore ( [[#ICLEI--2014b|ICLEI, 2014b]] ; [[#Blok--2015|Blok and Tschötschel, 2015]] ); development in New Songdo (Republic of Korea), which is experimenting with interventions, such as embedded smart waste management ( [[#Anthopoulos--2017|Anthopoulos, 2017]] ), and national policy initiatives such as the Smart Cities Mission covering 100 cities in India (e.g. technology-enabled water, energy and land management for urban agriculture in Nashik city) ( [[#ICLEI--2014a|ICLEI, 2014a]] ). However, the efficacy of such measures, especially for larger sustainability and climate-change goals, remains to be seen ( [[#ICLEI--2014a|ICLEI, 2014a]] ; [[#ICLEI--2014b|ICLEI, 2014b]] ; [[#Caprotti--2015|Caprotti et al., 2015]] ; [[#Anthopoulos--2017|Anthopoulos, 2017]] ).

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--2019|Duy et al., 2019]] ), or projected estimates by [[#Pervin--2020|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--2020|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--2021|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--2017|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--2019|Salim et al., 2019]] ).

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<span id="sustainable-land-use-planning-and-regulation"></span>
===== 10.4.6.4.2 Sustainable land-use planning and regulation =====

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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%20Coninck--2018|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--2015|Mitchell et al., 2015]] ; [[#Dhar--2016|Dhar and Khirfan, 2016]] ): for example, strict building regulations can protect urban wetlands and associated ecosystem services ( [[#Jiang--2015|Jiang et al., 2015]] ); appropriate land zoning can safeguard green spaces, ensure improvements in permeability and obviate new development in risk-prone locations ( [[#Duy--2019|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--2015|Mitchell et al., 2015]] ).

Land tenure arrangements strongly shape urban dwellers’ vulnerability and their adaptive capacities ( [[#Roy--2013|Roy et al., 2013]] ; [[#Michael--2018|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--2018|Deshpande et al., 2018]] ) and Phnom Penh (Cambodia) ( [[#Mitchell--2015|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--2015|Nahiduzzaman et al., 2015]] ; [[#Rahman--2016|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--2021|Cao et al., 2021]] ; [[#Nicholls--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--2019|Xu et al. (2019)]] have shown in Xiamen.

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<span id="ecosystem-based-adaptation"></span>
===== 10.4.6.4.3 Ecosystem-based adaptation =====

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The literature on urban ecosystem-based adaptation (EbA) [[#footnote-004|9]] , especially across Asia, has grown significantly since AR5 (Demuzere and al., 2014; [[#Yao--2015|Yao et al., 2015]] ; [[#Brink--2016|Brink et al., 2016]] ; [[#Bazaz--2018|Bazaz et al., 2018]] ; [[#de%20Coninck--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--2015|Palmer et al., 2015]] ) and need to be complemented by ecosystem-based actions to manage risk more effectively ( [[#Du--2020|Du et al., 2020]] ), build adaptive capacity, and in some cases, meet mitigation and SDGs ( [[#Huang--2020|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--2018|Jiang et al., 2018]] ; [[#Yu--2018d|Yu et al., 2018d]] ; [[#Wang--2019a|Wang et al., 2019a]] ; [[#Zhanqiang--2019|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--2018|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|Saraswat, 2016]] ; [[#Mishra--2019|]] [[#Mishra--2019|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--2016b|Li et al., 2016b]] ; [[#Stip--2019|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--2019|Zhu et al., 2019]] ); inadequate consideration of low-income, vulnerable populations ( [[#Blok--2015|Blok and Tschötschel, 2015]] ; [[#Meerow--2017|Meerow, 2017]] ; [[#Mabon--2021|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--2018|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--2021|Mabon and Shih, 2021]] ; [[#Singh--2021b|Singh et al., 2021b]] ).

The EbA interventions are not uniform across Asian cities: in a global study on urban EbA, [[#Brink--2016|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.

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[[File:68388bfd6f5d105824b1a71661789e47 IPCC_AR6_WGII_Figure_10_010.png]]

'''Figure 10.10 |''' '''Evidence of the effectiveness of ecosystem-based adaptation (EbA) using examples of four commonly used EbA options''' '''[[#footnote-000|10]]''' '''.''' 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).

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[[#footnote-000-backlink|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|Owen, 2020]] ; [[#Singh--2021a|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--2015|Padgham and Dietrich, 2015]] ; [[#Patil--2019|Patil et al., 2019]] ). However, it can potentially undermine ecosystem services through land-use changes, water overextraction or applying chemical fertilisers ( [[#Ackerman--2014|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.

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===== 10.4.6.4.4 Migration and planned relocation =====

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There is ''medium evidence'' with ''high agreement'' that climatic risks are exacerbating internal and international migration across Asia (see Box 10.2; [[#IDMC--2019|IDMC, 2019]] ; [[#Maharjan--2020|Maharjan et al., 2020]] ). In coastal cities, formal ‘retreat’ measures, such as forced displacement and planned relocation ( [[#Oppenheimer--2019|Oppenheimer et al., 2019]] ), are commonly considered ‘last resort’ adaptation strategies once other infrastructural and ecosystem-based protect-and-accommodate strategies are exhausted ( [https://www.ipcc.ch/chapter/10#CCP2.3 CCP2.3] ) ( [[#Haasnoot--2019|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--2020|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--2018|Davis et al., 2018]] ; [[#Ajibade--2019|Ajibade, 2019]] ; [[#Lincke--2021|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|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|Blondin, 2019]] ; [[#Zickgraf--2019|Zickgraf, 2019]] ; [[#Singh--2020|Singh and Basu, 2020]] ; [[#Cundill--2021|Cundill et al., 2021]] ; [[#Gavonel--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--2020|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--2018|Michael et al., 2018]] ; [[#Singh--2020|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|Meerow, 2017]] ; [[#Ajibade--2019|Ajibade, 2019]] ; [[#Jain--2021|Jain et al., 2021]] ).

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===== 10.4.6.4.5 Disaster management and contingency planning =====

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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--2019|Ray and]] [[#Shaw--2019|Shaw, 2019]] ; [[#UNESCAP--2019|UNESCAP, 2019]] ; [[#Singh--2021a|Singh et al., 2021a]] ). Overall, there has been a growing emphasis on ‘build back better’ interventions ( [[#Mannakkara--2013|Mannakkara and Wilkinson, 2013]] ; [[#Hallegatte--2018|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 EWS 11 , [[#footnote-003|10]] increasing awareness about disaster risks and impacts, and building local capacities to deal with them ( [[#Bhowmik--2021|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--2021|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--2018|Schaer and Pantakar, 2018]] ), and Kratie, Cambodia ( [[#Ngin--2020|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--2019|Izumi et al., 2019]] ). Furthermore, technology-based innovations, such as using big data ( [[#Yu--2018b|Yu et al., 2018b]] ), improved warnings through mobile phones or mobilising relief through social media ( [[#Carley--2016|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|UN-Water, 2018]] ; [[#Zevenbergen--2018|Zevenbergen et al., 2018]] ; [[#Rozenberg--2019|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%20Municipal--2018|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|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--2013|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--2018|Seidler et al., 2018]] ; [[#Islam--2020|Islam et al., 2020]] ).

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