A Framework for Global Multicategory and Multiscalar Drought Characterization Accounting for Snow Processes.

ABSTRACT: Drought indices do not always provide the most relevant information for water resources management as most of them neglect the role of snow in the land surface water balance. In this study, a physically based drought index, the Standardized Moisture Anomaly Index (SZI), was modified and improved by incorporating the effects of snow dynamics for drought characterization at multiple time scales. The new version of the SZI, called SZIsnow, includes snow in both the water supply and demand in drought characterization by using the water-energy budgets from the Global Land Data Assimilation Systems product. We compared and evaluated the performance of SZIsnow and SZI in drought identification globally across various time scales using observed multicategory drought evidences from several sources.

SUBMITTER: Zhang B 

PROVIDER: S-EPMC6988450 | biostudies-literature | 2019 Nov

REPOSITORIES: biostudies-literature