A hybrid drought index combining meteorological, hydrological, and agricultural information based on the entropy weight theory

作者：Zhu, Jiwei; Zhou, Linan; Huang, Shengzhi^*

来源：Arabian Journal of Geosciences, 2018, 11(5): 91.

DOI：10.1007/s12517-018-3438-1

• Hybrid drought index
• Entropy weight method
• Variable fuzzy set theory
• Northwest China

Drought assessment would be insufficient and unreliable when using the existing indicators based on a single variable (e.g., precipitation) or a combination of two variables (e.g., precipitation and runoff). Therefore, the entropy theory was utilized to develop a hybrid drought index (HDI) that combines meteorological, hydrological, and agricultural information based on precipitation, runoff, and soil moisture data, respectively, and it was applied to characterize the drought condition in Northwest China. Furthermore, the linkages between the atmospheric circulation anomaly/sunspot activities and the HDI series in Northwest China were explored through cross wavelet analysis. The results indicated that (1) HDI has a good performance to capture drought in Northwest China due to its consideration of multiple variables; (2) the annual HDI series in Northwest China was dominated by an insignificantly upward trend, except for Xinjiang, and this trend will be the opposite in the near future; and (3) generally, all of the sunspot activities, El Nino-Southern Oscillation (ENSO) events, AMO (Atlantic Multidecadal Oscillation), and PDO (Pacific Decadal Oscillation) had strong associations with the HDI series in Northwest China, in which sunspot activities had the strongest effects on drought conditions, whereas the AMO had the relatively lowest impacts. This study sheds new light on developing the hybrid drought index, and the findings are valuable for local drought mitigation.

• 出版日期2018-3
• 单位西安理工大学