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Article

Quantitative Agricultural Flood Risk Assessment Using Vulnerability Surface and Copula Functions

1
Grassland Research Institute, Chinese Academy of Agricultural Science, Hohhot 010010, China
2
College of Geographical Science, Inner Mongolia Normal University, Hohhot 010022, China
3
Inner Mongolia Key Laboratory of Disaster and Ecological Security on the Mongolian Plateau, Hohhot 010022, China
*
Author to whom correspondence should be addressed.
Water 2018, 10(9), 1229; https://doi.org/10.3390/w10091229
Received: 20 July 2018 / Revised: 29 August 2018 / Accepted: 1 September 2018 / Published: 12 September 2018
(This article belongs to the Section Hydrology)
Agricultural flood disaster risk assessment plays a vital role in agricultural flood disaster risk management. Extreme precipitation events are the main causes of flood disasters in the Midwest Jilin province (MJP). Therefore, it is important to analyse the characteristics of extreme precipitation events and assess the flood risk. In this study, the Multifractal Detrended Fluctuation Analysis (MF-DFA) method was used to determine the threshold of extreme precipitation events. The total duration of extreme precipitation and the total extreme precipitation were selected as flood indicators. The copula functions were then used to determine the joint distribution to calculate the bivariate joint return period, which is the flood hazard. Historical data and flood indicators were used to build an agricultural flood disaster vulnerability surface model. Finally, the risk curve for agricultural flood disasters was established to assess the flood risk in the MJP. The results show that the proposed approaches precisely describe the joint distribution of the flood indicators. The results of the vulnerability surface model are in accordance with the spatiotemporal distribution pattern of the agricultural flood disaster loss in this area. The agricultural flood risk of the MJP gradually decreases from east to west. The results provide a firm scientific basis for flood control and drainage plans in the area. View Full-Text
Keywords: agricultural flood risk; extreme precipitation events; MF-DFA; joint return period; vulnerability surface model agricultural flood risk; extreme precipitation events; MF-DFA; joint return period; vulnerability surface model
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MDPI and ACS Style

Wang, Y.; Liu, G.; Guo, E.; Yun, X. Quantitative Agricultural Flood Risk Assessment Using Vulnerability Surface and Copula Functions. Water 2018, 10, 1229. https://doi.org/10.3390/w10091229

AMA Style

Wang Y, Liu G, Guo E, Yun X. Quantitative Agricultural Flood Risk Assessment Using Vulnerability Surface and Copula Functions. Water. 2018; 10(9):1229. https://doi.org/10.3390/w10091229

Chicago/Turabian Style

Wang, Yongfang, Guixiang Liu, Enliang Guo, and Xiangjun Yun. 2018. "Quantitative Agricultural Flood Risk Assessment Using Vulnerability Surface and Copula Functions" Water 10, no. 9: 1229. https://doi.org/10.3390/w10091229

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