Development and evaluation of a physically based multiscalar drought index: The Standardized Moisture Anomaly Index. Issue 22 (27th November 2015)

• Record Type: Journal Article
• Authors: Zhang, Baoqing; Zhao, Xining; Jin, Jiming; Wu, Pute
• Is Part Of: Journal of geophysical research. Volume 120:Issue 22(2015:Dec.)
• Page Start: 11, 575
• Page End: 11, 588
• Publication Date: 2015-11-27
• Subjects: drought -- the Loess Plateau -- Yellow River -- SZI -- SPEI -- PDSI; Atmospheric physics -- Periodicals; Geophysics -- Periodicals; 551.5
• DOI: 10.1002/2015JD023772
• Languages: English
• ISSNs: 2169-897X

Abstract

Abstract: In this study, a new physically based multiscalar drought index, the Standardized Moisture Anomaly Index (SZI), was developed and evaluated, which combines the advantages of the Palmer Drought Severity Index (PDSI) and the Standardized Precipitation Evapotranspiration Index (SPEI). The SZI is based on the water budget simulations produced with a sophisticated hydrological model, and it also includes a multiscalar feature to quantify drought events at different temporal scales taken from SPEI. The Chinese Loess Plateau was selected to evaluate the performance of the SZI. Our evaluation indicates that the SZI accurately captures the onset, duration, and ending of a multiyear drought event through its multiscalar feature, while the PDSI, which lacks this feature, is often unable to describe the evolution of a multiyear drought event. In addition, the variability of the SZI is more consistent with observed streamflow and the satellite normalized difference vegetation index than that of the Standardized Precipitation Index and the SPEI. Although the SPEI includes potential evapotranspiration (PE) as water demand, water demand is often unrealistically estimated based solely on PE, especially over arid and semiarid regions. The improved drought quantification with the SZI is the result of a more reasonable estimation of water demand by including evapotranspiration, runoff, and any change in soil moisture storage. In general, our newly developed SZI is physically based and includes a multiscalar feature, which enables it to provide better information for drought monitoring and identification at different temporal scales. Key Points: A new physically based multiscalar drought index (SZI) was developed The SZI has a multiscalar character that is lacking in the PDSI The SZI provides more reasonable estimation of water demand than SPEI