Simulation of Spatial and Temporal Variability of Soil Moisture Using the Simultaneous Heat And Water (SHAW) Model: Applications to Passive Microwave Remote Sensing
Agricultural management practices and land surface heterogeneity may impact soil moisture retrieval at the footprint scales of passive microwave remote sensing. To evaluate the potential impact of land heterogeneity, it was necessary to identify a hydrological model that could simulate soil moisture spatial variation due to differences in soil texture, land management and crop type. In this study, the SHAW model was evaluated for its capacity to accurately simulate the impact of land management technique. SHAW simulated soil moisture showed good agreement with the observed temporal variations of soil moisture data. Given this performance, SHAW was coupled to a radiative transfer model and used to assess the impact of sub-pixel heterogeneity (e.g. soil moisture, texture, land cover) on measured brightness temperature. When the spatial variability was accounted for, the error between the simulated brightness temperatures and the SMOS (Soil Moisture and Ocean Salinity) satellite observations and was improved over simulations that do not account for sub-pixel variability. These results have importance for improving the assimilation of soil moisture and downscaling passive microwave estimates of soil moisture to smaller regions.