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Sea-levels will rise, even with stringent climate change mitigation. Mitigation will slow the rate of rise. There is limited knowledge on how the costs of coastal protection vary with alternative global warming levels of 1.5°C to 4.0°C. Analysing six sea-level rise scenarios (0.74m to 1.09m, 50th percentile) across these warming levels, and five Shared Socioeconomic Pathways, this paper quantifies the economic costs of flooding and protection due to sea-level rise using the Dynamic Interactive Vulnerability Assessment (DIVA) modelling framework. Results are presented for World Bank income groups and five selected countries from the present to 2100. Annual sea flood damage costs without additional adaptation are more influenced by socio-economic development than sea-level rise, indicating there are opportunities to control risk with development choices. In contrast, annual sea dike investment costs are more dependent on the magnitude of sea-level rise. In terms of total costs with adaptation, upper middle, low middle and low income groups are projected to have higher relative costs as a proportion of GDP compared with high income groups. If low income countries protected now, flood costs could be reduced after 2050 and beyond. However, without further adaptation, their coasts will experience growing risks and costs leaving them increasingly reliant on emergency response measures. adaptation. Without mitigation or adaptation, greater inequalities in damage costs between income groups could result. At country level, annual sea flood damage costs without additional adaptation are projected to rapidly increase with approximately 0.2m of sea-level rise, leaving limited time to plan and adapt. SB, PG, KJ, RJ and RW were funded by the Department for Business, Energy and Industrial Strategy (BEIS) under contract UK SBS CR18083. ASA, SB, SJ, DL, RN, RT and AV were funded by the European Union’s Seventh Programme for Research, Technological Development and Demonstration under grant agreement No. 603396 (RISES-AM project).

Floods are among the most frequent and costliest natural hazards. Fluvial flood losses are expected to increase in the future, driven by population and economic growth in flood-prone areas, and exacerbated in many regions by effects of climate change on the hydrological cycle. Yet, studies assessing direct and indirect economic impacts of fluvial flooding in combination with climate change and socio-economic projections at a country level are rare. This study presents an integrated flood risk analysis framework to calculate total (direct and indirect) economic damages, with and without socio-economic development, under a range of warming levels from < 1.5 to 4 °C in Brazil, China, India, Egypt, Ethiopia, and Ghana. Direct damages are estimated by linking spatially explicit daily flood hazard data from the Catchment-based Macro-scale Floodplain (CaMa-Flood) model with country- and sector-specific depth-damage functions. These values input into an economic Input-Output model for the estimation of indirect losses. The study highlights that total fluvial flood losses are largest in China and India when expressed in absolute terms. When expressed as a share of national GDP, Egypt faces the largest total losses under both the climate change and climate change plus socio-economic development experiments. The magnitude of indirect losses also increased significantly when socio-economic development was modelled. The study highlights the importance of including socio-economic development when estimating direct and indirect flood losses, as well as the role of recovery dynamics, essential to provide a more comprehensive picture of potential losses that will be important for decision makers.

The potential impact of climate change on agriculture has been one of the most discussed topics in the literature on climate change. Although the possible impacts of climate change on crop yields have been widely studied, there remains little quantitative understanding of the heterogeneous economic responses to climate-induced crop yield changes in different economies, particularly at higher levels of warming. This study assesses the economic impacts of eight scenarios of warming, from 1.5 to 4 °C, on rice and wheat yields in China, India, Brazil, Egypt, Ghana and Ethiopia. The role of both natural and social factors in crop production is considered by coupling a statistical crop model (ClimaCrop) and a global economic model (GTAP). Changes in economic outputs, consumer and producer prices and national economic welfare are presented. The study shows marginal benefits of crop yield changes on GDP and welfare in China up to 3.5 and 3.0 °C, respectively. This is due to projected increases in rice yields which lower domestic consumer rice prices. Although at higher warming levels these trends begin to reverse. The other countries are negatively impacted due to declining crop yields, with increasing consumer prices of domestic and imported rice and wheat. GDP and welfare declines, with more severe reductions associated with the higher warming levels, particularly in India and Ethiopia. The method is beneficial as the economic outputs reflect a more in-depth picture of the response of global markets and ultimately regional consequences of agricultural impacts that will be of importance to decision makers.

Flooding in urban areas during heavy rainfall, often characterized by short duration and high-intensity events, is known as "surface water flooding." Analyzing surface water flood risk is complex as it requires understanding of biophysical and human factors, such as the localized scale and nature of heavy precipitation events, characteristics of the urban area affected (including detailed topography and drainage networks), and the spatial distribution of economic and social vulnerability. Climate change is recognized as having the potential to enhance the intensity and frequency of heavy rainfall events. This study develops a methodology to link high spatial resolution probabilistic projections of hourly precipitation with detailed surface water flood depth maps and characterization of urban vulnerability to estimate surface water flood risk. It incorporates probabilistic information on the range of uncertainties in future precipitation in a changing climate. The method is applied to a case study of Greater London and highlights that both the frequency and spatial extent of surface water flood events are set to increase under future climate change. The expected annual damage from surface water flooding is estimated to be to be £171 million, £343 million, and £390 million/year under the baseline, 2030 high, and 2050 high climate change scenarios, respectively.

Climate change and increasing urbanization are projected to result in an increase in surface water flooding and consequential damages in the future. In this paper, we present insights from a novel Agent Based Model (ABM), applied to a London case study of surface water flood risk, designed to assess the interplay between different adaptation options; how risk reduction could be achieved by homeowners and government; and the role of flood insurance and the new flood insurance pool, Flood Re, in the context of climate change. The analysis highlights that while combined investment in property-level flood protection and sustainable urban drainage systems reduce surface water flood risk, the benefits can be outweighed by continued development in high risk areas and the effects of climate change. In our simulations, Flood Re is beneficial in its function to provide affordable insurance, even under climate change. However, the scheme does face increasing financial pressure due to rising surface water flood damages. If the intended transition to risk-based pricing is to take place then a determined and coordinated strategy will be needed to manage flood risk, which utilises insurance incentives, limits new development, and supports resilience measures. Our modelling approach and findings are highly relevant for the ongoing regulatory and political approval process for Flood Re as well as for wider discussions on the potential of insurance schemes to incentivise flood risk management and climate adaptation in the UK and internationally.

Flood risk emerges from the dynamic interaction between natural hazards and human vulnerability. Methods for the quantification of flood risk are well established, but tend to deal with human and economic vulnerability as being static or changing with an exogenously defined trend. In this paper we present an Agent-Based Model (ABM) developed to simulate the dynamical evolution of flood risk and vulnerability, and facilitate an investigation of insurance mechanism in London. The ABM has been developed to firstly allow an analysis of the vulnerability of homeowners to surface water flooding, which is one of the greatest short term climate risks in the UK with estimated annual costs of £1.3bn to £2.2bn. These costs have been estimated to increase by 60-220% over the next 50 years due to climate change and urbanisation. Vulnerability is influenced by homeowner’s decisions to move house and/or install measures to protect their properties from flooding. In particular, the ABM focuses on the role of flood insurance, simulating the current public-private partnership between the government and insurers in the UK, and the forthcoming re-insurance scheme Flood Re, designed as a roadmap to support the future affordability and availability of flood insurance. The ABM includes interaction between homeowners, sellers and buyers, an insurer, a local government and a developer. Detailed GIS and qualitative data of the London borough of Camden are used to represent an area at high risk of surface water flooding. The ABM highlights how future development can exacerbate current levels of surface water flood risk in Camden. Investment in flood protection measures are shown to be beneficial for reducing surface water flood risk. The Flood Re scheme is shown to achieve its aim of securing affordable flood insurance premiums, however, is placed under increasing pressure in the future as the risk of surface water flooding continues to increase.

The risk of residential overheating and mortality is increasing due to the effects of global warming and the urban heat island effect and needs to be addressed through climate change adaptation. ‘Adaptation pathways’ have become widely recognised as an adaptation planning approach, but they have not been utilised for long-term planning for city-scale urban heat risk management. This paper applies adaptation pathway methodology to urban heat risk management. We use spatially coherent downscaled probabilistic climate change projections that account for changes in urban-land cover and the urban heat island to appraise adaptation pathways and inform long-term adaptation planning. We demonstrate that adaptation strategies focusing solely on urban greening or building level adaptation based on current best practice are unlikely to cope with the increasing levels of risk. Air-conditioning may play a growing role in managing heat-risk; however, increasing air-conditioning will exacerbate the urban heat island and further increase the risks of overheating.

Flooding is recognised as one of the most common and costliest natural disasters in England. Flooding in urban areas during heavy rainfall is known as ‘surface water flooding’, considered to be the most likely cause of flood events and one of the greatest short-term climate risks for London. In this paper we present results from a novel Agent-Based Model designed to assess the interplay between different adaptation options, different agents, and the role of flood insurance and the flood insurance pool, Flood Re, in the context of climate change. The model illustrates how investment in adaptation options could reduce London’s surface water flood risk, today and in the future. However, benefits can be outweighed by continued development in high risk areas and the effects of climate change. Flood Re is beneficial in its function to provide affordable insurance, even under climate change. However, it offers no additional benefits in terms of overall risk reduction, and will face increasing pressure due to rising surface water flood risk in the future. The modelling approach and findings are highly relevant for reviewing the proposed Flood Re scheme, as well as for wider discussions on the potential of insurance schemes, and broader multi-sectoral partnerships, to incentivise flood risk management in the UK and internationally.