Integrated drought risk assessment of multi-hazard-affected bodies based on copulas in the Taoerhe Basin, China

被引:16
作者
Wang, Rui [1 ,2 ,3 ]
Zhang, Jiquan [1 ,2 ,3 ]
Guo, Enliang [4 ,5 ]
Alu, Si [1 ,2 ,3 ]
Li, Danjun [1 ,2 ,3 ]
Ha, Si [1 ,2 ,3 ]
Dong, Zhenhua [4 ]
机构
[1] Northeast Normal Univ, Sch Environm, Changchun 130024, Peoples R China
[2] Northeast Normal Univ, State Environm Protect Key Lab Wetland Ecol & Veg, Changchun 130024, Peoples R China
[3] Minist Educ, Key Lab Vegetat Ecol, Changchun 130024, Peoples R China
[4] Inner Mongolia Normal Univ, Coll Geog Sci, Hohhot 010000, Peoples R China
[5] Inner Mongolia Key Lab Disaster & Ecol Secur Mong, Hohhot 010022, Peoples R China
基金
美国国家科学基金会;
关键词
AGRICULTURAL DROUGHT; DISASTER RISK; VULNERABILITY; MAIZE; PRECIPITATION; TEMPERATURE; RAINFALL; PROVINCE; IMPACTS; WHEAT;
D O I
10.1007/s00704-018-2374-z
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
Along with global warming, drought disasters are occurring more frequently and are seriously affecting normal life and food security in China. Drought risk assessments are necessary to provide support for local governments. This study aimed to establish an integrated drought risk model based on the relation curve of drought joint probabilities and drought losses of multi-hazard-affected bodies. First, drought characteristics, including duration and severity, were classified using the 1953-2010 precipitation anomaly in the Taoerhe Basin based on run theory, and their marginal distributions were identified by exponential and Gamma distributions, respectively. Then, drought duration and severity were related to construct a joint probability distribution based on the copula function. We used the EPIC (Environmental Policy Integrated Climate) model to simulate maize yield and historical data to calculate the loss rates of agriculture, industry, and animal husbandry in the study area. Next, we constructed vulnerability curves. Finally, the spatial distributions of drought risk for 10-, 20-, and 50-year return periods were expressed using inverse distance weighting. Our results indicate that the spatial distributions of the three return periods are consistent. The highest drought risk is in Ulanhot, and the duration and severity there were both highest. This means that higher drought risk corresponds to longer drought duration and larger drought severity, thus providing useful information for drought and water resource management. For 10-, 20-, and 50-year return periods, the drought risk values ranged from 0.41 to 0.53, 0.45 to 0.59, and 0.50 to 0.67, respectively. Therefore, when the return period increases, the drought risk increases.
引用
收藏
页码:577 / 592
页数:16
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