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A Framework for Global Multicategory and Multiscalar Drought Characterization Accounting for Snow Processes
Author(s) -
Zhang Baoqing,
Xia Youlong,
Huning Laurie S.,
Wei Jiahua,
Wang Guangqian,
AghaKouchak Amir
Publication year - 2019
Publication title -
water resources research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.863
H-Index - 217
eISSN - 1944-7973
pISSN - 0043-1397
DOI - 10.1029/2019wr025529
Subject(s) - snow , environmental science , latitude , water balance , atmospheric sciences , geology , meteorology , geography , geotechnical engineering , geodesy
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 SZI snow , 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 SZI snow and SZI in drought identification globally across various time scales using observed multicategory drought evidences from several sources. Results show that the SZI snow agrees better with the observed changes in hydrological and agricultural droughts than the SZI, particularly over basins with high snow accumulation. Furthermore, the SZI snow is more consistent with the residual water‐energy ratio than the SZI over snow‐influenced regions. Overall, the SZI snow can be either a complement or an improvement over the SZI for identifying, monitoring, and characterizing hydrological and agricultural droughts at various scales (e.g., 1–48 months) over high‐latitude and high‐elevation regions that receive snow.