Author/Authors :
zhang, qiang ministry of education, beijing normal university - key laboratory of environmental change and natural disaster, Beijing, China , zhang, qiang ministry of education/ministry of civil affairs, beijing normal university - faculty of geographical science, Beijing, China , zhang, qiang beijing normal university - state key laboratory of earth surface processes and resources ecology, Beijing, China , li, qin sun yat-sen university - department of water resources andenvironment, Guangzhou, China , li, qin texas a m university - department of biological and agricultural engineering, zachry department of civil engineering, Texas, USA , shi, peijun ministry of education/ministry of civil affairs, beijing normal university - faculty of geographical science, academy of disaster reduction and emergency management, Beijing, China , shi, peijun anhui normal university - college of territorial resourceand tourism, Anhui, China , shi, peijun ministry of education, beijing normal university - key laboratory of environmental change and natural disaster, Beijing, China , shi, peijun beijing normal university - state key laboratory of earth surface processes and resources ecology, Beijing, China , shi, peijun sun yat-sen university - department of water resources and environment, Guangzhou, China
Abstract :
Drought is a major natural hazard that has massive impacts on the society. How to monitor drought is critical for its mitigation and early warning. This study proposed a modified version of the multivariate standardized drought index (MSDI) based on precipitation, evapotranspiration, and soil moisture, i.e., modified multivariate standardized drought index (MMSDI). This study also used nonparametric joint probability distribution analysis. Comparisons were done between standardized precipitation evapotranspiration index (SPEI), standardized soil moisture index (SSMI), MSDI, and MMSDI, and real-world observed drought regimes. Results indicated that MMSDI detected droughts that SPEI and/or SSMI failed to do. Also, MMSDI detected almost all droughts that were identified by SPEI and SSMI. Further, droughts detected by MMSDI were similar to real-world observed droughts in terms of drought intensity and drought-affected area. When compared to MMSDI, MSDI has the potential to overestimate drought intensity and drought-affected area across China, which should be attributed to exclusion of the evapotranspiration components from estimation of drought intensity. Therefore, MMSDI is proposed for drought monitoring that can detect agrometeorological droughts. Results of this study provide a framework for integrated drought monitoring in other regions of the world and can help to develop drought mitigation.
