Publications

Chatterjee, S; Desai, AR; Zhu, J; Townsend, PA; Huang, JY (2022). Soil moisture as an essential component for delineating and forecasting agricultural rather than meteorological drought. REMOTE SENSING OF ENVIRONMENT, 269, 112833.

Abstract
Drought is a recurring, complex, and extreme climatic phenomenon characterized by subnormal precipitation for months to years triggering negative impacts on agriculture, energy, tourism, recreation, and transportation sectors. Agricultural drought assessment is based on a deficit of soil moisture (SM) during the plant-growing season, whereas meteorological drought corresponds to subnormal precipitation over months to years. However, satellite-derived agricultural and meteorological drought indices (including those comprising root-zone SM) have not been comprehensively compared to evaluate their ability for drought delineation and particularly forecasting across climate regimes, land cover and soil types, and irrigation management (irrigated vs. rainfed) in the contiguous USA (CONUS). Here, we did so from 2015 to 2019 within the CONUS. In most regions except the US Midwest and Southeast, SM-based indices (e.g., Palmer Z, SMAP, SWDI) delineated agricultural drought better than meteorological (e.g., SPI, SPEI) and hybrid (Comprehensive Drought Index, CDI) drought indices. In contrast, the SPI and SPEI showed strong correlation with the aridity index in most part of the CONUS except the Midwest. SM-based and hybrid indices also demonstrated skills for agricultural drought forecasting (represented by end-of-year cumulative GPP), predominantly in the early growing season and particularly in irrigated rather than rainfed croplands. These findings indicate the leading role of SM in controlling ecosystem dryness and confirm drought memory, possibly due to SM-memory in land-atmosphere coupling. Proper application of meteorological and agricultural drought indices and their contrasting spatial-temporal controls on plant growth and ecosystem dryness has the potential to improve our understanding of drought evolution and provide early drought forecasting across large regions with diverse climate regimes, land cover types, soil textural classes, and irrigation management.

DOI:
10.1016/j.rse.2021.112833

ISSN:
1879-0704