loading page

Soil Moisture Plays Crucial Role in Delineating and Forecasting Agricultural and Meteorological Drought.
  • +2
  • Sumanta Chatterjee,
  • Ankur Desai,
  • Jun Zhu,
  • Philip Townsend,
  • Jingyi Huang
Sumanta Chatterjee
University of Wisconsin Madison

Corresponding Author:schatterje22@wisc.edu

Author Profile
Ankur Desai
University of Wisconsin Madison
Author Profile
Jun Zhu
University of Wisconsin Madison
Author Profile
Philip Townsend
University of Wisconsin
Author Profile
Jingyi Huang
University of Wisconsin Madison
Author Profile

Abstract

Drought is a recurring and extreme hydroclimatic hazard with serious impacts on agriculture and overall society. Delineation and forecasting of agricultural and meteorological drought are essential for water resource management and sustainable crop production. Agricultural drought assessment is defined as the deficit of root-zone soil moisture (RZSM) during active crop growing season, whereas meteorological drought is defined as subnormal precipitation over months to years. Several indices have been used to characterize droughts, however, there is a lack of study focusing on comprehensive comparison among different agricultural and meteorological drought indices for their ability to delineate and forecast drought across major climate regimes and land cover types. This study evaluates the role of RZSM from Soil Moisture Active Passive (SMAP) mission along with two other soil moisture (SM) based indices (e.g., Palmer Z and SWDI) for agricultural and meteorological drought monitoring in comparison with two popular meteorological drought indices (e.g., SPEI and SPI) and a hybrid (Comprehensive Drought Index, CDI) drought index. Results demonstrate that SM-based indices (e.g., Palmer Z, SMAP, SWDI) delineated agricultural drought events better than meteorological (e.g., SPI, SPEI) and hybrid (CDI) drought indices, whereas the latter three performed better in delineating meteorological drought across the contiguous USA during 2015–2019. SM-based indices showed skills for forecasting agricultural drought (represented by end-of-growing season gross primary productivity) in the early growing seasons. The results further confirm the key role of SM on ecosystem dryness and corroborate the SM-memory in land-atmosphere coupling.