Solving the inverse problem for soil moisture and temperature profiles by sequential assimilation of multifrequency remotely sensed observations

An algorithm is developed to solve the inverse problem for the retrieval of the soil moisture and temperature profiles based on remotely sensed observations of multispectral irradiance. A model of coherent wave radiative transfer and a model of coupled heat and moisture diffusion in porous media are combined in order to estimate the liquid volumetric water content and temperature profiles in a soil column using low-frequency passive microwave and infrared emitted radiation observations and without the use of empirical relations. The central purpose of this mainly theoretical paper is to pose the inverse problem and present the physics-based algorithm as the solution. The algorithm is tested on a basic synthetic example in order to ascertain that the retrieval is feasible. Additional work in the future is necessary and planned in order to test the algorithm with field observations, extend it to include vegetation, and refine it for detail in the specification of heterogeneity in soil types and boundary conditions