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Title: Predictability of state-level flood damage in the conterminous United States: the role of hazard, exposure and vulnerability

Abstract

Understanding historical changes in flood damage and the underlying mechanisms is critical for predicting future changes for better adaptations. In this study, a detailed assessment of flood damage for 1950–1999 is conducted at the state level in the conterminous United States (CONUS). Geospatial datasets on possible influencing factors are then developed by synthesizing natural hazards, population, wealth, cropland and urban area to explore the relations with flood damage. A considerable increase in flood damage in CONUS is recorded for the study period which is well correlated with hazards. Comparably, runoff indexed hazards simulated by the Variable Infiltration Capacity (VIC) model can explain a larger portion of flood damage variations than precipitation in 84% of the states. Cropland is identified as an important factor contributing to increased flood damage in central US while urbanland exhibits positive and negative relations with total flood damage and damage per unit wealth in 20 and 16 states, respectively. Altogether, flood damage in 34 out of 48 investigated states can be predicted at the 90% confidence level. In extreme cases, ~76% of flood damage variations can be explained in some states, highlighting the potential of future flood damage prediction based on climate change and socioeconomic scenarios.

Authors:
 [1];  [2];  [2]
  1. Guangdong Univ. of Technology, Guangzhou (China); Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
  2. Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Publication Date:
Research Org.:
Battelle Memorial Institute, Columbus, OH (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Biological and Environmental Research (BER) (SC-23)
OSTI Identifier:
1393484
Grant/Contract Number:
SC0013680
Resource Type:
Journal Article: Accepted Manuscript
Journal Name:
Scientific Reports
Additional Journal Information:
Journal Volume: 7; Journal Issue: 1; Journal ID: ISSN 2045-2322
Publisher:
Nature Publishing Group
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES; Hydrology; Natural hazards

Citation Formats

Zhou, Qianqian, Leng, Guoyong, and Feng, Leyang. Predictability of state-level flood damage in the conterminous United States: the role of hazard, exposure and vulnerability. United States: N. p., 2017. Web. doi:10.1038/s41598-017-05773-4.
Zhou, Qianqian, Leng, Guoyong, & Feng, Leyang. Predictability of state-level flood damage in the conterminous United States: the role of hazard, exposure and vulnerability. United States. doi:10.1038/s41598-017-05773-4.
Zhou, Qianqian, Leng, Guoyong, and Feng, Leyang. 2017. "Predictability of state-level flood damage in the conterminous United States: the role of hazard, exposure and vulnerability". United States. doi:10.1038/s41598-017-05773-4. https://www.osti.gov/servlets/purl/1393484.
@article{osti_1393484,
title = {Predictability of state-level flood damage in the conterminous United States: the role of hazard, exposure and vulnerability},
author = {Zhou, Qianqian and Leng, Guoyong and Feng, Leyang},
abstractNote = {Understanding historical changes in flood damage and the underlying mechanisms is critical for predicting future changes for better adaptations. In this study, a detailed assessment of flood damage for 1950–1999 is conducted at the state level in the conterminous United States (CONUS). Geospatial datasets on possible influencing factors are then developed by synthesizing natural hazards, population, wealth, cropland and urban area to explore the relations with flood damage. A considerable increase in flood damage in CONUS is recorded for the study period which is well correlated with hazards. Comparably, runoff indexed hazards simulated by the Variable Infiltration Capacity (VIC) model can explain a larger portion of flood damage variations than precipitation in 84% of the states. Cropland is identified as an important factor contributing to increased flood damage in central US while urbanland exhibits positive and negative relations with total flood damage and damage per unit wealth in 20 and 16 states, respectively. Altogether, flood damage in 34 out of 48 investigated states can be predicted at the 90% confidence level. In extreme cases, ~76% of flood damage variations can be explained in some states, highlighting the potential of future flood damage prediction based on climate change and socioeconomic scenarios.},
doi = {10.1038/s41598-017-05773-4},
journal = {Scientific Reports},
number = 1,
volume = 7,
place = {United States},
year = 2017,
month = 7
}

Journal Article:
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