@article{f264e1aa3dda47d79cbe5a253a1e00bf,
title = "Long-Term Changes in Global Socioeconomic Benefits of Flood Defenses and Residual Risk Based on CMIP5 Climate Models",
abstract = "A warmer climate is expected to accelerate the global hydrological cycle, causing more intense precipitation and floods. Despite recent progress in global flood risk assessment, the socioeconomic benefits of flood defenses (i.e., reduction in population/economic exposure) and the residual risk (i.e., residual population/economic exposure) are poorly understood globally and regionally. To address these knowledge gaps, we use the runoff data from a baseline and 11 Coupled Model Intercomparison Project Phase 5 (CMIP5) climate models to drive the Catchment-based Macro-scale Floodplain model incorporating the latest satellite river width information. From the simulated annual maxima, we use a Gumbel distribution to estimate the river water depth-flood return period relationship. We independently evaluate flood impacts on population and economy (i.e., gross domestic product) for a range of flood return periods. We estimate the socioeconomic benefits and the corresponding residual risk for the globe and 26 subcontinental regions. The global population (gross domestic product) exposed to flooding is ∼8% (∼7%) per year lower when implementing existing flood protection infrastructure extracted from the FLOod PROtection Standards database. If the current flood defenses were to be unchanged in the future (Representative Concentration Pathway 4.5 [RCP4.5] and RCP8.5, i.e., ∼2 to ∼4.3°C above the preindustrial levels), the globe and most of the regions (particularly where developing countries are concentrated) would experience an increase in residual risk. This increase is especially obvious when the gap of climate forcing between RCP8.5 and RCP4.5 widens by the end of the 21st century. We finally evaluate the impact of changed flood defense levels on the socioeconomic benefits and the corresponding residual risk.",
keywords = "benefits, climate change, flood defense, global scale, residual risk, river flooding",
author = "Lim, {Wee Ho} and Dai Yamazaki and Sujan Koirala and Yukiko Hirabayashi and Shinjiro Kanae and Dadson, {Simon J.} and Hall, {Jim W.} and Fubao Sun",
note = "Funding Information: This study was financially supported by the National Key Research and Development Program of China (2016YFA0602402), the Oxford Martin Programme on Resource Stewardship in the Oxford Martin School, the Chinese Academy of Sciences President{\textquoteright}s International Fellowship Initiative (W. H. L., 2017PC0068), the Chinese Academy of Sciences Pioneer Hundred Talents Program (F. S.), and the Environmental Research and Technology Development Fund (Y. H., S-14, MiLAi) of the Ministry of the Environment, Japan. We thank Sen Li, Michael Gilmont, Raghav Pant, Michael Simpson, and Matthew Ives for helpful discussions. We are very grateful to an anonymous reviewer for helpful comments. We acknowledge the World Climate Research Programme{\textquoteright}s Working Group on Coupled Modelling, which is responsible for CMIP, and we thank the climate modeling groups (Table 1 in this manuscript) for producing and making available their model output. For CMIP the U.S. Department of Energy{\textquoteright}s Program for Climate Model Diagnosis and Intercomparison provides coordinating support and led development of software infrastructure in partnership with the Global Organization for Earth System Science Portals. The CMIP5 climate models used in this study are sourced from http://cmip-pcmdi.llnl.gov/cmip5/ index.html. The CaMa-Flood model and GWD-LR data set are accessible at http://hydro.iis.u-tokyo.ac.jp/∼yamadai/ cama-flood/. The FLOPROS data set can be downloaded from the Supplement section of Scussolini et al. (2016): https://www.nat-hazards-earth-syst-sci. net/16/1049/2016/. The GPWv3 population data are available here: http://sedac.ciesin.columbia.edu/data/ collection/gpw-v3. The World Bank country population and GDP data can be downloaded from https://data. worldbank.org/. Funding Information: This study was financially supported by the National Key Research and Development Program of China (2016YFA0602402), the Oxford Martin Programme on Resource Stewardship in the Oxford Martin School, the Chinese Academy of Sciences President's International Fellowship Initiative (W. H. L., 2017PC0068), the Chinese Academy of Sciences Pioneer Hundred Talents Program (F. S.), and the Environmental Research and Technology Development Fund (Y. H., S-14, MiLAi) of the Ministry of the Environment, Japan. We thank Sen Li, Michael Gilmont, Raghav Pant, Michael Simpson, and Matthew Ives for helpful discussions. We are very grateful to an anonymous reviewer for helpful comments. We acknowledge the World Climate Research Programme's Working Group on Coupled Modelling, which is responsible for CMIP, and we thank the climate modeling groups (Table in this manuscript) for producing and making available their model output. For CMIP the U.S. Department of Energy's Program for Climate Model Diagnosis and Intercomparison provides coordinating support and led development of software infrastructure in partnership with the Global Organization for Earth System Science Portals. The CMIP5 climate models used in this study are sourced from http://cmip-pcmdi.llnl.gov/cmip5/index.html. The CaMa-Flood model and GWD-LR data set are accessible at http://hydro.iis.u-tokyo.ac.jp/~yamadai/cama-flood/. The FLOPROS data set can be downloaded from the Supplement section of Scussolini et al. (): https://www.nat-hazards-earth-syst-sci.net/16/1049/2016/. The GPWv3 population data are available here: http://sedac.ciesin.columbia.edu/data/collection/gpw-v3. The World Bank country population and GDP data can be downloaded from https://data.worldbank.org/. Publisher Copyright: {\textcopyright}2018. The Authors.",
year = "2018",
month = jul,
doi = "10.1002/2017EF000671",
language = "English",
volume = "6",
pages = "938--954",
journal = "Earth's Future",
issn = "2328-4277",
publisher = "John Wiley and Sons Inc.",
number = "7",
}