Journal
WATER
Volume 10, Issue 9, Pages -Publisher
MDPI
DOI: 10.3390/w10091229
Keywords
agricultural flood risk; extreme precipitation events; MF-DFA; joint return period; vulnerability surface model
Categories
Funding
- Science and Technology Innovation Project Grassland Non-biological Disaster Prevention and Mitigation Team of Chinese Academy of Agricultural Sciences [CAAS-ASTIP-IGR2015-04]
- National Science Foundation for Young Scientists of China [41807507]
- China the Science and Technology Project of Inner Mongolia Autonomous Region [201502095]
- Postdoctoral Science Foundation Funded Project [2017M620975]
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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.
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