Assimilation of active microwave observation data for soil moisture profile estimation

This paper discusses the potential of retrieving information about the soil moisture profile from measurements of the surface soil moisture content through active microwave observations of the Earth. Recently, Mancini et al. [1999] have shown through laboratory experiments that the volumetric moisture content of the first few centimeters of a bare soil can be determined within 5% vol accuracy by means of C and L band active microwave observations and inverse modeling. Here we use active microwave observations of the surface soil moisture content in a data assimilation framework to show that this allows the retrieval of the root zone soil moisture profile. The data assimilation procedure developed is based on the Kalman filter technique. Kalman filtering allows reconstruction of the state vector of a system when this system is represented by a dynamic model and when at least part of the state variables are observed regularly. The dynamic model of the system used here is based on the one-dimensional Richards equation. The observation equation is based on the Integral Equation Model [Fung et al., 1992; Fung, 1994] and is used to link the radar observations to surface soil moisture content. It is shown that even in the presence of model and observation noise and infrequent observations, accurate retrieval of the entire moisture profile is possible for a bare soil.