综合干旱指数研究进展

Research progress of composite drought index

干旱时空演变过程复杂,影响因素众多,单一的干旱指数往往难以反映干旱的多类型和多尺度特征,融合多源信息构建综合干旱指数是干旱监测的重要发展趋势。系统回顾了综合干旱指数的研究进展,总结了3种常用的综合干旱指数构建方法:权重组合、多变量联合分布和机器学习方法,分析了这几类综合干旱指数的优势与不足;详细介绍了综合干旱指数在美国、欧洲和中国干旱监测业务中的应用情况;最后指出综合干旱指数应从加强内在机理性、提高多源信息融合水平、完善评价体系等方面继续深入研究。

Drought has very complex spatiotemporal evolution process and is highly impacted by various factors.Drought indices or indicators assimilated from only one drought-related variable are typically insufficient in characterizing different drought types at multiple scales.To overcome this problem,composite drought indexes via integrating multi-source information have been proposed in recent years.This study reviews the current status of composite drought indexes and summarizes three commonly utilized methods for constructing the indexes including weight combination method,multivariable joint distribution function method,and machine-learning-based modelling method.Moreover,we introduce the applications of composite drought indicators in the operational drought monitoring services in the United States,Europe,and China.Further research should focus on the mechanism of drought propagation,multi-source data merging,and the evaluation of composite drought indexes.