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• W2962078324 startingPage "3754" @default.
• W2962078324 abstract "This study investigates the trends in economic damages caused by three types of inland floods (flash flood, flood, and heavy rain) in the United States and the variations in related hazard and vulnerability indicators between 1996 and 2016. We explore the underlying mechanisms based on a survey-based dataset maintained by the National Oceanic and Atmospheric Administration (NOAA) National Weather Service. An annual average of 6518 flood occurrences was reported, which caused economic damages of 3351 million USD per year. Flash flood and flood contributed to 53% and 32% of total occurrences and was associated with a larger share of damaging events (SDE). Results show that the higher impacts by flood and flash flood on property and crop are partly attributed to the greater intensity of rainfall. In addition, flood has the highest unit cost of damages. Notably, despite an upward tendency in economic damages by flash floods, no evident change trend is observed for inland floods as a whole. Further analysis shows changes in economic damages by heavy rain and flash flood are mainly governed by the increased annual frequency and hazard intensity, but the change of trend in their vulnerability indicators (i.e., SDE and Damage Per Event (DPE)) is not obvious. Regarding floods, it was not possible to attribute the variations in economic losses to hazard and vulnerability, as no significant tendency is found except for an increasing SDE. Despite limitations of length of records, data collection, and methodology, the difference in economic impacts and the related hazard and vulnerability revealed in this study can help better target future adaptation and mitigation measures." @default.
• W2962078324 created "2019-07-23" @default.
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• W2962078324 date "2019-07-09" @default.
• W2962078324 modified "2023-09-26" @default.
• W2962078324 title "The Role of Hazard and Vulnerability in Modulating Economic Damages of Inland Floods in the United States Using a Survey-Based Dataset" @default.
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• W2962078324 doi "https://doi.org/10.3390/su11133754" @default.
• W2962078324 hasPublicationYear "2019" @default.
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