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United States Department of Agriculture

Agricultural Research Service

Title: CONSTRAINING ROOT-ZONE SOIL MOISTURE ESTIMATES UNDER DENSE VEGETATION USING MULTI-FREQUENCY REMOTE SENSING OBSERVATIONS

Author
item CROW, WADE

Submitted to: American Geophysical Union
Publication Type: Abstract Only
Publication Acceptance Date: October 16, 2004
Publication Date: December 15, 2004
Citation: Crow, W.T. 2004. Constraining root-zone soil moisture estimates under dense vegetation using multi-frequency remote sensing observations [abstract]. Joint Assembly of the American Geophysical Union. 85(47):H12A-04.

Technical Abstract: Operational monitoring of surface soil moisture via spaceborne microwave radiometry should become a reality within the next decade. Unfortunately, the vertical support of these measurements is too shallow (top 2 to 5 cm of soil column) and the horizontal resolution too coarse (> 10 km) for many agricultural and water resource applications. The most viable solution for the lack of vertical measurement support is the use of data assimilation systems and multi-layer hydrologic modeling to estimate root-zone soil moisture based on sufficiently frequent surface soil moisture observations. While such inversion are theoretically possible using data assimilation systems, it is unclear how robust surface soil moisture data assimilation procedures will be over agricultural crops where root-zone soil water loses are dominated by root uptake of soil water at depths far greater than the measurement depth of the radiometer. Consequently, the most robust strategies for operationally monitoring root-zone soil moisture in agricultural areas are likely to be based on integrating both microwave surface soil moisture retrievals and surface energy balance predictions obtained from thermal surface radiometric temperature observations into a multi-layer hydrologic model. This research explores competing strategies for combining microwave soil moisture retrievals and radiometric surface temperature observations within a hydrologic modeling framework to improve the model's representation of the root-zone soil water balance. Remote sensing observations will be used to constrain key hydrologic fluxes into (and out of) the soil column root zone. Results will demonstrate circumstances under which the assimilation of surface soil moisture alone will be inadequate to fully constrain root-zone soil moisture estimates beneath heavily vegetated canopies and explore the potential for surface energy flux estimates from diagnostic remote sensing models to provide additional constraints.

Last Modified: 8/27/2014
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