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

===== 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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