Abstract
From an agricultural perspective, drought refers to an unusual deficiency of plant available water in the root-zone of the soil profile. This paper focuses on evaluating the benefit of assimilating soil moisture retrievals from the Soil Moisture Active Passive (SMAP) mission into the USDA-FAS Palmer model for agricultural drought monitoring. This will be done by examining the standardized soil moisture anomaly index. The skill of the SMAP-enhanced Palmer model is assessed over three agricultural regions that have experienced major drought since the launch of SMAP in early 2015: (1) the 2015 drought in California (CA), USA, (2) the 2017 drought in South Africa, and (3) the 2018 mid-winter drought in Australia. During these three events, the SMAP-enhanced Palmer soil moisture estimates (PM+SMAP) are compared against the Climate Hazards group Infrared Precipitation with Stations (CHIRPS) rainfall dataset and Normalized Difference Vegetation Index (NDVI) products. Results demonstrate the benefit of assimilating SMAP and confirm its potential for improving U.S. Department of Agriculture-Foreign Agricultural Service root-zone soil moisture information generated using the Palmer model. In particular, PM+SMAP soil moisture estimates are shown to enhance the spatial variability of Palmer model root-zone soil moisture estimates and adjust the Palmer model drought response to improve its consistency with ancillary CHIRPS precipitation and NDVI information.
Highlights
And routine knowledge of expected crop yield production is important for farmers, agricultural agencies, insurance companies, aid organization and other end-users because it drives food supply/price projections, impacts trade markets, and identifies food insecure areas
Our analysis focuses on exploring the agreement between Palmer model (PM) rootzone soil moisture (RZSM) products with independent estimates of rainfall and vegetation health captured by Climate Hazards group Infrared Precipitation with Stations (CHIRPS) and GIMSS Moderate Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI), respectively
The convergence of evidence approach employed by the USDA-FAS crop analysts is based on evaluating current crop status relative to some expected normal level using a variety of geospatial variables linked to agricultural productivity
Summary
And routine knowledge of expected crop yield production is important for farmers, agricultural agencies, insurance companies, aid organization and other end-users because it drives food supply/price projections, impacts trade markets, and identifies food insecure areas. The two factors of the highest significance for crop growth and yield accumulation are heat (i.e., air temperature and radiation budget) and plant available water (i.e., soil moisture) (Lobell et al, 2009). In relation to plant development and health and yield formation, the three most important aspects of agricultural drought are its duration (i.e., how long is the period of limited soil moisture conditions), timing (i.e., when does the water stress occur during the growing season), and severity (Abendroth et al, 2011; Licht, 2014; Mladenova et al, 2017). Crop yields are generally most susceptible to water deficiency during the reproductive crop development stage associated with grainfilling and formation As these requirements are relatively wellknown, the eventual (yield-based) impact of drought can often be estimated within season
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