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ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Hydrology and Remote Sensing Laboratory » Research » Publications at this Location » Publication #362041

Research Project: Integrating Remote Sensing, Measurements and Modeling for Multi-Scale Assessment of Water Availability, Use, and Quality in Agroecosystems

Location: Hydrology and Remote Sensing Laboratory

Title: Evaluating the operational application of SMAP for global agricultural drought monitoring

item MLADENOVA, I. - Goddard Space Flight Center
item BOLTEN, J. - Goddard Space Flight Center
item Crow, Wade
item SAZIB, N. - Goddard Space Flight Center
item Cosh, Michael
item TUCKER, C.J. - Goddard Space Flight Center
item REYNOLDS, C. - Collaborator

Submitted to: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 7/20/2019
Publication Date: 9/1/2019
Citation: Mladenova, I., Bolten, J., Crow, W.T., Sazib, N., Cosh, M.H., Tucker, C., Reynolds, C. 2019. Evaluating the operational application of SMAP for global agricultural drought monitoring. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 12(9):3387-3397.

Interpretive Summary: The ability to accurately monitor the onset of agricultural drought (i.e., a deficit of root-zone soil water availability for adequate crop and forage production) at large scales is critical for drought mitigation and humanitarian applications. Recent research has focused on the use of surface soil moisture estimates acquired from satellite-based microwave radiometers to enhance global agricultural drought monitoring efforts. However, the added benefits associated with leveraging such observations has not yet been objectively quantified. This paper evaluates the ability of soil moisture observations acquired from the NASA Soil Moisture Active/Passive (SMAP) mission to enhance our ability to globally monitor agricultural drought. Results show clear added value especially in data-poor regions prone to food insecurity (e.g., the Horn of Africa). The results of this study are currently being used by the USDA's Foreign Agricultural Service to improve their ability to globally monitor the extent, duration and severity of agricultural drought conditions using SMAP soil moisture data.

Technical Abstract: Remote sensing over the past two decades have made possible the routine global monitoring of surface soil moisture. Regional agricultural drought monitoring is one of the most logical application areas for such monitoring. However, remote sensing alone provides soil moisture information for only the top five centimeters of the soil profile, while agricultural drought monitoring requires knowledge of the amount of water present in the root zone. The assimilation of remotely sensed soil moisture products into continuous soil water balance models provides a way of addressing these shortcomings. Here, we describe the assimilation of NASA’s Soil Moisture Active Passive (SMAP) surface soil moisture data into the USDA Foreign Agricultural Service (USDA FAS) Palmer model and assess the impact of SMAP on the USDA FAS drought monitoring capabilities. The assimilation of SMAP is specifically designed to enhance the model skill and the USDA FAS drought capabilities by correcting for random errors contained in rainfall forcing data. The performance of this SMAP-based assimilation system is evaluated using two approaches. At global scale the accuracy of the system was assessed by examining the lag correlation agreement between soil moisture and the Normalized Difference Vegetation index (NDVI). Additional regional-scale evaluation using in situ-based soil moisture estimates was carried out at seven of the SMAP core Cal/Val sites located in the USA. Both types of analysis demonstrated the value of assimilating SMAP into the USDA FAS Palmer model and its potential to enhance the operational USDA FAS root-zone soil moisture information.