Resumen
A comprehensive data set of extreme hydrological events (EHEs)—floods and droughts, consisting of 2,171 occurrences worldwide, during 1960-2014 was compiled, and then their economic losses were normalized using a price index in U.S. dollar. The data set showed a significant increasing trend of EHEs before 2000, while a slight post-2000 decline. Correspondingly, the EHE-caused economic losses increased obviously before 2000 followed by a slight decrease; the post-2000 decline could be partially attributed to the decreases in drought and flood-prone area or climate adaptation practices. Spatially, Asia experienced most EHEs (969), corresponding to the largest share of economic losses (approximately $868 billion for floods and $50 billion for droughts, respectively), while Oceania had the least EHEs (102) and the least economic losses (approximately $19 billion for floods and $45 billion for droughts). The five countries with the highest EHE-caused economic losses were China, United States, Canada, Australia, and India. Countries that suffered the highest flood-caused economic losses were China, United States, and Canada. This data set provides a quantitative linkage between climate science and economic losses at a global scale, and it is beneficial for the regional climatic impact assessments and strategical development for mitigating climate change impacts.
| Idioma original | English |
|---|---|
| Páginas (desde-hasta) | 5165-5175 |
| Número de páginas | 11 |
| Publicación | Water Resources Research |
| Volumen | 55 |
| N.º | 6 |
| DOI | |
| Estado | Published - jun 2019 |
Nota bibliográfica
Publisher Copyright:©2019. American Geophysical Union. All Rights Reserved.
Financiación
This study was partially supported by the Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, and the “Thousand Young Talents” program in China. The authors are grateful for the Campus Office of Undergraduate Research Initiatives (COURI) at the University of Texas El Paso and the San Diego State University for the facility support. This work partially used the Extreme Science and Engineering Discovery Environment (XSEDE), which is supported by National Science Foundation grant number ACI-1053575. Authors state that there is no conflict of interest. We are grateful for The International Disaster Database (http://www.emdat.be/database) and Dartmouth Flood Observatory (http://www.dartmouth.edu/~floods/Archives/index.html) for making their data set publicly accessible.
| Financiadores | Número del financiador |
|---|---|
| Campus Office of Undergraduate Research Initiatives | |
| Northeast Institute of Geography and Agroecology | |
| U.S. Department of Energy Chinese Academy of Sciences Guangzhou Municipal Science and Technology Project Oak Ridge National Laboratory Extreme Science and Engineering Discovery Environment National Science Foundation National Energy Research Scientific Computing Center National Natural Science Foundation of China | ACI-1053575 |
| U.S. Department of Energy Chinese Academy of Sciences Guangzhou Municipal Science and Technology Project Oak Ridge National Laboratory Extreme Science and Engineering Discovery Environment National Science Foundation National Energy Research Scientific Computing Center National Natural Science Foundation of China | |
| University of Texas at El Paso | |
| Chinese Academy of Sciences |
ODS de las Naciones Unidas
Este resultado contribuye a los siguientes Objetivos de Desarrollo Sostenible
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Climate action
ASJC Scopus subject areas
- Water Science and Technology
Huella
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