Yin, Zhiqiang, Hu, Yixin, Jenkins, Katie ORCID: https://orcid.org/0000-0002-6740-5139, He, Yi, Forstenhäusler, Nicole, Warren, Rachel
ORCID: https://orcid.org/0000-0002-0122-1599, Yang, Lili, Jenkins, Rhosanna and Guan, Dabo
(2021)
Assessing the economic impacts of future fluvial flooding in six countries under climate change and socio-economic development.
Climatic Change, 166 (3-4).
ISSN 0165-0009
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Abstract
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.
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