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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 #320367

Research Project: Leveraging Remote Sensing, Land Surface Modeling and Ground-based Observations ... Variables within Heterogeneous Agricultural Landscapes

Location: Hydrology and Remote Sensing Laboratory

Title: Parametric exponentially correlated surface emission model for L-band passive microwave soil moisture retrieval

Author
item ZHAO, T. - Collaborator
item SHI, J. - Collaborator
item BINDLISH, R. - Collaborator
item Jackson, Thomas
item Cosh, Michael
item LINGMEI, J. - Collaborator
item ZHONGJUN, Z. - Collaborator
item HUIMIN, L. - Collaborator

Submitted to: Physics and Chemistry of the Earth
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 11/1/2015
Publication Date: 12/30/2015
Citation: Zhao, T., Shi, J., Bindlish, R., Jackson, T.J., Cosh, M.H., Lingmei, J., Zhongjun, Z., Huimin, L. 2015. Parametric exponentially correlated surface emission model for L-band passive microwave soil moisture retrieval. Physics and Chemistry of the Earth. 83-84:65-74.

Interpretive Summary: An L-band parametric emission model for exponentially correlated surfaces was developed and implemented in a soil moisture retrieval algorithm. The approach was based on the parameterization of an effective roughness parameter in relation with the geometric roughness variables and incidence angle. The parameterization was developed based on a large set of simulations using an analytical approach over a wide range of geophysical properties. The results showed that the parametric model can be used in place of the complex model to more efficiently model microwave soil emission. Surface soil moisture is an important parameter in hydrology and climate investigations. Current and future satellite missions with L-band passive microwave radiometers can provide valuable information for monitoring the global soil moisture.

Technical Abstract: Surface soil moisture is an important parameter in hydrology and climate investigations. Current and future satellite missions with L-band passive microwave radiometers can provide valuable information for monitoring the global soil moisture. A factor that can play a significant role in the modeling and inversion of microwave emission from land surfaces is the surface roughness. In this study, an L-band parametric emission model for exponentially correlated surfaces was developed and implemented in a soil moisture retrieval algorithm. The approach was based on the parameterization of an effective roughness parameter of Hp in relation with the geometric roughness variables (root mean square height s and correlation length l) and incidence angle. The parameterization was developed based on a large set of simulations using an analytical approach incorporated in the advanced integral equation model (AIEM) over a wide range of geophysical properties. It was found that the effective roughness parameter decreases as surface roughness increases, but increases as incidence angle increases. In contrast to previous research, Hp was found to be expressed as a function of a defined slope parameter m = s2/l, and coefficients of the function could be well described by a quadratic equation. The parametric model was then tested with L-band satellite data in soil moisture retrieval algorithm over the Little Washita watershed, which resulted in an unbiased root mean square error of about 0.03 m3/m3 and 0.04 m3/m3 for ascending and descending orbits, respectively.