Run Theory and Copula-Based Drought Risk Analysis for Songnen Grassland in Northeastern China

Rina Wu, Jiquan Zhang, Yuhai Bao and Enliang Guo
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Rina Wu: School of Geography, Liaoning Normal University, Dalian 116029, China
Jiquan Zhang: School of Environment, Northeast Normal University, Changchun 130024, China
Yuhai Bao: College of Geography, Inner Mongolia Normal University, Hohhot 010022, China
Enliang Guo: College of Geography, Inner Mongolia Normal University, Hohhot 010022, China

Sustainability, 2019, vol. 11, issue 21, 1-17

Abstract: Droughts are among the more costly natural hazards, and drought risk analysis has become urgent for the proper planning and management of water resources in grassland ecosystems. We chose Songnen grassland as a case study, used a standardized precipitation evapotranspiration index (SPEI) to model drought characteristics, employed run theory to define the drought event, and chose copula functions to construct the joint distribution for drought variables. We applied two kinds of return periods to conduct a drought risk assessment. After evaluating and comparing several distribution functions, drought severity (DS) was best described by the generalized extreme value (GEV) distribution, whereas drought duration (DD) was best fitted by gamma distribution. The root mean square error (RMSE) and Akaike Information Criterion (AIC) goodness-of-fit measures to evaluate their performance, the best-performing copula is Frank copula to model the joint dependence structure for each drought variables. The results of the secondary return periods indicate that a higher risk of droughts occurs in Keshan county, Longjiang county, Qiqiha’er city, Taonan city, and Baicheng city. Furthermore, a relatively lower risk of drought was found in Bei’an city, Mingquan county, Qinggang county, and qian’an county, and also in the Changling county and Shuangliao city. According to the calculation of the secondary return periods, which considered all possible scenarios in our study, we found that the secondary return period may be the best indicator for evaluating grassland ecosystem drought risk management.

Keywords: drought risk analysis; the secondary return period; run theory; copula (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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