Assimilation of active microwave measurements for soil moisture profile retrieval under laboratory conditions

The authors discuss the potential of retrieving information on the soil moisture profile from measurements of the surface soil moisture content through active microwave observations. They use active microwave observations of the surface soil moisture content in a data assimilation framework to show that this allows the retrieval of the entire soil moisture profile. The data assimilation procedure demonstrated is based on the Kalman filter technique. Kalman filtering allows reconstruction of the state vector when at least part of the state variables are observed regularly. The dynamic model of the system used is based on the 1D Richards equation. The observation equation is based on the integral equation model of A. K. Fung et al. (1992) and is used to link the radar observations to surface soil moisture content. Recently, M. Mancini et al. (1999) reported about laboratory experiments investigating the use of active microwave observations to estimate surface soil moisture content. The present authors apply the data assimilation scheme to the radar measurements of these experiments to retrieve the entire soil moisture profile in the soil sample used, and compare these results with the soil moisture profile measurements (using TDR). It is shown that with a limited number of radar measurements accurate retrieval of the entire soil moisture profile is possible.