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Global Flash Drought Monitoring Using Surface Soil Moisture
Author(s) -
Sehgal Vinit,
Gaur Nandita,
Mohanty Binayak P.
Publication year - 2021
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 - 10.1029/2021wr029901
Subject(s) - environmental science , water content , flash flood , footprint , flash (photography) , moisture , soil water , climatology , remote sensing , meteorology , atmospheric sciences , soil science , geology , geography , art , paleontology , geotechnical engineering , archaeology , visual arts , flood myth
Abrupt onset and swift intensification characterize flash droughts. Global surface soil moisture ( θ RS ) from NASA's Soil Moisture Active Passive (SMAP) satellite can facilitate a near‐real‐time assessment of emerging flash droughts at a 36‐km footprint. However, a robust flash drought monitoring using θ RS must account for the (a) short observation record of SMAP, (b) nonlinear geophysical controls over θ RS dynamics, and (c) emergent meteorological drivers of flash droughts. We propose a new method for near‐real‐time characterization of droughts using Soil Moisture Stress (SMS, drought stress) and Relative Rate of Drydown (RRD, drought stress intensification rate)—developed using SMAP θ RS (March 2015–May 2021), footprint‐scale seasonal soil water retention parameters and land‐atmospheric coupling strength. SMS and RRD are nonlinearly combined to develop Flash Drought Stress Index (FDSI) to characterize emerging flash droughts (FDSI ≥ 0.71 for moderate to high RRD and SMS). Globally, FDSI shows a high correlation with concurrent meteorological anomalies. A mechanistic evaluation of flash droughts is presented for the Northern Great Plains, Central South Africa, and Eastern Australia using FDSI, SMS, and RRD. About 5.6% of the earth's landmass experienced flash droughts of varying intensity and duration during 2015–2021 (FDSI ≥ 0.71 for >30 consecutive days), majorly in global drylands. FDSI shows high skill in forecasting vegetation health with a lead of 0–2 weeks, with exceptions in irrigated croplands and mixed forests. With readily available parameters, low data latency, and no dependence on model simulations, we provide a robust tool for global near‐real‐time flash drought monitoring using SMAP.