A new composite index for global soil plant atmosphere continuum drought monitoring combing remote-sensing based terrestrial water storage and vapor pressure deficit anomalies

Abstract

Drought is known as a complex natural phenomenon because of its multifaceted effect on the environment. Composite drought indices have been considered a useful tool to capture the compound drought impacts, however, few of them are capable of operating at multi-timescales. Moreover, the vast of composite drought indices fail to depict the whole water deficit on terrestrial because of the ignoring of groundwater. In this study, we linearly combined two satellite observed variables, TWS (Terrestrial Water Storage) and VPD (Vapor Pressure Deficit), to develop a new index WDDI (Water Deficit Drought Index). It can provide the global composite drought conditions at multi-timescales by different weight combinations. The global multiscalar SPEI (Standardized Precipitation Evapotranspiration Index) from 2002 to 2011 and 2012 to 2017 were selected to train and assess the weights respectively. Weights assessment results showed that SPEI and WDDI reached moderate correlations (r > 0.4) over the globe, especially stronger in the summer season (0.5 < r < 0.88). Good agreements between WDDI and scPDSI (self-calibrated Palmer Drought Severity Index), SPEI were found in the global historical drought area statistics, especially in area statistics of severe or worse drought conditions. WDDI at short and long timescales were found to be sensitive to drought signals in the meteorological and hydrological system respectively as it produced moderate or stronger correlations with VsmCI (Volumetric soil moisture Condition Index) and RCI (Runoff Condition Index) in most parts of the world. The application of WDDI in the specific drought events (the 2010 Russian drought and the 2012–2016 California drought) further reinforced the above inferences and revealed the unique superiority of considering groundwater deficit in hydrological drought monitoring. The new proposed multiscalar WDDI could help practitioners better identify the drought conditions and understand the drought propagation mechanism from the meteorological to the hydrological system.