Editing IPCC:AR6/WGII/Chapter-6 (section)

==== 6.3.3.3 Emergency and Disaster Risk Management ====

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There is growing evidence of the benefits of early warning systems for urban preparedness decision making and action for climate and weather-related hazards such as cyclones, hurricanes and floods ( ''medium evidence'' ; ''high agreement'' ) (Lumbroso, Brown and Ranger, 2016; [[#Zia--2015|Zia and Wagner, 2015]] ; Marchezini et al., 2017). Climate forecasting is constantly evolving and becoming increasingly accurate. Global organisations such as the World Meteorological Organizations are increasingly focusing on new and emerging technologies such as crowdsourced data collection to support integrated city services and early warning systems (Baklanov et al., 2018). However, while climate forecasting is an increasingly central tool for risk management agencies, a focus on urban areas or key infrastructure is still considerably rare (Lourenço et al., 2015; Nissan et al., 2019; Harvey et al., 2019). The significant rise in urban risks poses significant challenges to humanitarian agencies. Humanitarian responses and local emergency management are vital for disaster risk reduction yet are compromised in urban contexts where it is difficult to confirm property ownership and where renters and informal dwellers are often excluded from decision-making and planning ( [[#Parker--2015|Parker and Maynard, 2015]] ; Maynard et al., 2017). Disaster survivors and growing urban refugee populations are often displaced across the city thereby complicating efforts to track and provide support (Maynard et al., 2017).

Existing early warning systems remain insufficient and the complexity of urban landforms makes accurate and detailed early warning difficult ( ''medium evidence'' ; ''high agreement'' ) (Jones et al., 2015). This is particularly the case in low- and middle-income countries (LMICs) where urban centres are often characterised by rapid expansion of interlinked formal and informal human settlements and land use zones. In such contexts, early warning services vary in effectiveness within the same urban centre (Allen et al., 2020c; Rangwala et al., 2018). Often, forecast-based action follows linear structures where forecast information is applied mainly for responding to negative impacts rather than anticipatory decision-making and preparation to avoid such impacts (Marchezini et al., 2017). Early warning systems are effective for warning of threshold breaching events including cyclonic activity and riverine flooding but less able to provide localised warning, though capability is rapidly increasing. Probabilistic risk forecasting and forecast based early action are only beginning to be applied to urban contexts and often those that are most vulnerable do not receive warnings regarding hazardous events (Nissan et al., 2019). There is less capacity for early warning systems in LMICs with key challenges linked to a lack of well-established risk baseline information; accessibility, communication and understanding of forecast information, as well as political and institutional barriers and limited resources and capacities to act on such information (Jones et al., 2015; Mustafa et al., 2015; [[#Zia--2015|Zia and Wagner, 2015]] ; Marchezini et al., 2017; Gotgelf, Roggero and Eisenack, 2020). Political and institutional barriers to the incorporation of climate information to decision-making are not limited to LMICs (Harvey et al., 2019). For example, comprehensive studies on sectoral use of climate information in Europe revealed that, despite climate services becoming increasingly accessible and well resourced, there is limited organisational uptake of seasonal climate forecasts across key sectors (e.g., energy, transport, water and infrastructure) in informing their decision making processes ( [[#Soares--2016|Soares and Dessai, 2016]] ; Soares, Alexander and Dessai, 2018). This is due both to technical and non-technical barriers such as lack of awareness and knowledge of climate information and forecasting ( [[#Soares--2016|Soares and Dessai, 2016]] ; Soares, Alexander and Dessai, 2018).

Globally, a considerable diversity of tools and frameworks for urban resilience assessments are being developed at multiple scales ( [[#Arup%20and%20Rockefeller--2015|Arup and Rockefeller, 2015]] ; Elias-Trostmann et al., 2018). These include hybrids such as ecosystem-based disaster risk reduction (Eco-DRR) (Begum et al., 2014).While important advances have been made in assessing urban resilience, much debate remains around such tools and assessment approaches regarding issues such as validation, dynamics in exposure and vulnerability, and appropriateness of generic methods in high-density urban settlements (Leitner et al., 2018; Cardoso et al., 2020; Rufat et al., 2019). Disaster impact and recovery time are strongly influenced by the behaviour and actions of individuals, communities, businesses, and government organisations ( [[#Meriläinen--2020|Meriläinen, 2020]] ; Räsänen et al., 2020). For example, the review by Aaerts et al. (2018) shows how the limitations of existing flood risk assessment methods (which tend to account for human behaviour in limited terms) can be addressed through innovative flood-risk assessments that integrate behavioural adaptation dynamics. The study by [[#Moghadas--2019|Moghadas et al. (2019)]] highlights the importance of hybrid multi-criteria approaches for assessing urban flood resilience in Tehran, Iran. A growing literature shows how multidisciplinary and inclusive approaches that include Local knowledge can achieve greater accuracy in risk characterisation and support lasting impact of investments into more robust climate services (Aerts et al., 2018; Lourenço et al., 2015; Sword-Daniels et al., 2018; Singh et al., 2018; Nissan et al., 2019; Harvey et al., 2019; [[#Simon--2020|Simon and Palmer, 2020]] ). This literature highlights the need for innovative approaches in urban contexts that transcend traditional approaches of local knowledge inclusion widely applied in rural contexts, such as participatory rural appraisal.

The inclusion of Local knowledge and Indigenous knowledge in urban vulnerability and risk assessments can strongly enhance local resilience, but its effectiveness is constrained by wider decision making and policy contexts dominated by top-down approaches ( ''medium evidence'' ; ''high agreement'' ) (Jones et al., 2015; Sword-Daniels et al., 2018; Nissan et al., 2019). Established non-state actors such as Shack and Slum Dwellers International are particularly effective at implementing inclusive approaches for local knowledge incorporation into urban decision-making. Climate change and disaster risk exacerbate existing problems of economic development, yet macro-economic planning seldom incorporates adaptation. Recent evidence also confirms the role of Indigenous knowledge and local knowledge in management practices to reduce climate risks through early warning preparedness and response (see also [[#6.3.2|Section 6.3.2.3]] ). These practices are particularly important where alternative early warning methods are absent. For instance, Abudu Kasei et al. (2019) show that Indigenous knowledge gathered through observations on changes in natural indicators (such as links between rainfall patterns, certain flora and fauna, and temperature changes) could be applied to develop early warning of climate hazards (floods and droughts) in informal urban settlements in African countries such as Ghana. Similarly, Hiwaski et al. (2015) show that observations of changes in the environment and celestial bodies are used to predict climate-related hazards in Indonesia, the Philippines and Timor-Leste where communities in turn use local materials and methods, and customary practices to respond to the impacts of climate change.

Insurance is a risk transfer mechanism for middle- and high-income countries, yet is less widely available in LMICs ( [[#Surminski--2017|Surminski and Thieken, 2017]] ). Additionally, where insurance options do exist in LMICs, these are not usually available to large populations living or operating in the informal sector. Flood insurance is widely available in many Organisation for Economic Co-operation and Development (OECD) countries but the demand and uptake differ significantly across countries (Hanger et al., 2018). This financial tool is subject to increasing pressure under the changing climate, with growing concerns around affordability and availability. More integrative approaches are required, such as where changes in the insurance industry are closely linked to adaptation strategies, building standards and land use planning and their application (Cremades et al., 2018). This is particularly important in LMICs and of central concern for all insurance schemes is ensuring access, fairness and affordability for the most poor and vulnerable. However, there are some notable examples of low-income communities setting up their own disaster insurance mechanisms. For example, the Community Development Funds for the Baan Mankong upgrading programme in Thailand include disaster funds as insurance against housing damage ( [[#Archer--2012|Archer, 2012]] ). Such approaches also need to be more closely linked to existing urban risk management planning approaches where urban livelihoods are seldom integrated and informed by more dynamic risk reduction frameworks that consider adaptive cycles and how resilience changes over time ( [[#Beringer--2018|Beringer and Kaewsuk, 2018]] ; Cremades et al., 2018).

Disaster risk management systems face increasing challenges in adapting to evolving risk profiles, shaped by expanding urban areas and changing environmental conditions associated with climate change. In addition to flooding, risk monitoring and management systems have recently shown considerable shortfalls in planning for and responding to increased fire risk such as the devastating Californian wildfires in October 2019 ( [[#Morley--2020|Morley, 2020]] ) and Australia’s unprecedented and catastrophic 2019–2020 wildfire season. Risk management has also been challenged by new risk experiences including wild/bush fires encroaching on expanding urban areas and fire outbreaks in densely populated informal settlements pose increasing threats to livelihoods, human health and habitats globally (see also Sections 2.4.4.2 and 2.5.5.2).

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