A robust ensemble drought index: construction and assessment

Qianchuan Mi, Chuanyou Ren (), Yanhua Wang (), Xining Gao, Limin Liu and Yue Li
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Qianchuan Mi: Shenyang Agricultural University
Chuanyou Ren: Shenyang Agricultural University
Yanhua Wang: Shenyang Agricultural University
Xining Gao: Shenyang Agricultural University
Limin Liu: Shenyang Agricultural University
Yue Li: Shenyang Agricultural University

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2023, vol. 116, issue 1, No 48, 1139-1159

Abstract: Abstractref Drought indices have been widely used in drought monitoring and assessments, but it is difficult to select a uniform index suitable for different geographical and climatic conditions. In addition, the statistical parameters of drought index also vary with fitting reference period, which brings more challenges to the practicality of drought index under climate change. In this study, a new multitimescale and more robust integrated drought index, the EDI was constructed by integrating the common components of seven single drought indices (including SPI, PDSI_th, PDSI_pm, scPDSI_th, scPDSI_pm, SPEI_th and SPEI_pm). The EDI was compared with the single drought index over China in terms of the occurrence ability of historical drought events, the dependence of statistical parameters on reference periods, the goodness-of-fit of standard normal distribution and the correlation with soil moisture and runoff. We find that the EDI could more accurately reproduce the location and intensity of historical drought events, reduce the uncertainty caused by both potential evapotranspiration estimation and the reference period, has higher goodness-of-fit of standard normal distribution, higher correlation with soil moisture, more robust performance in hydrologic drought monitoring and less affected by the difference of geographical and climatic conditions. Moreover, the EDI improved the accuracy of drought monitoring in arid and semiarid regions of China, where assessment is always complex. Furthermore, the available evidence supports that a long-term stationary climate variables series could provide more accurate drought assessment.

Keywords: Drought index; Agricultural drought assessment; Hydrological drought assessment; Principal component analysis (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s11069-022-05715-y

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