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Title: Modeling and Assimilation of Root Zone Soil Moisture Using Remote Sensing Observations in Walnut Gulch Watershed During SMEX04

Author
item DAS, N - TEXAS A&M UNIVERSITY
item MOHANTY, B - TEXAS A&M UNIVERSITY
item Cosh, Michael
item Jackson, Thomas

Submitted to: Remote Sensing of Environment
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 4/10/2007
Publication Date: 2/15/2008
Citation: Das, N., Mohanty, B., Cosh, M.H., Jackson, T.J. 2008. Modeling and assimilation of root zone soil moisture using remote sensing observations in Walnut Gulch Watershed during SMEX04. Remote Sensing of Environment. 112:415-429.

Interpretive Summary: Water available to plants for growth is an important component of the water cycle across many spatial scales. The SMEX04 experiment in southeastern Arizona provided a good opportunity to study root zone moisture. Aircraft soil moisture data was assimilated into a moisture model to determine what effect this improved soil moisture estimate may have. The assimilation of the remotely sensed surface soil moisture observations had limited influence on the profile soil moisture. More specifically, root zone soil moisture depended mostly on the soil type. Modeled soil moisture profile estimates were compared to field measurements made periodically during the experiment at the ground based soil moisture stations in the watershed. Soil type played a more important role in the modeling of soil moisture.

Technical Abstract: Soil moisture status in the root zone is an important component of the water cycle at all spatial scales (e.g., point, field, catchment, watershed, and region). In this study, the spatio-temporal evolution of root zone soil moisture of the Walnut Gulch Experimental Watershed (WGEW) in Arizona was investigated during the Soil Moisture Experiment 2004 (SMEX04). Root zone soil moisture was estimated via assimilation of aircraft-based remotely sensed surface soil moisture into a distributed Soil-Water-Atmosphere-Plant (SWAP) model. An ensemble square root filter (EnSRF) based on a Kalman filtering scheme was used for assimilating the aircraft-based soil moisture observations at a spatial resolution of 800 m X 800 m. The SWAP model inputs were derived from the SSURGO.