Modeling the spatial and temporal distribution of soil moisture at watershed scales using remote-sensing and GIS

Soil water content (2(v)) is of fundamental importance in meteorology, agriculture, and hydrology, among other scientific disciplines. In hydrology, 2(v) partitions rainfall into runoff and infiltration, thus impacting surface and groundwater recharge, flood forecasting, and flow routing modeling. Measurement of 2(v) at a point is straightforward, but point measurements are inadequate for watershed hydrology due to variability of soil properties, land cover, and meteorological inputs over space. Passive microwave remote sensing systems have been successfully used to provide regional estimates of surface 2(v) (0-5 cm surface layer) at the spatial resolution of the sensor. To extend these data to other depths and scales, a two-layer soil water budget model was used to combine remotely sensed estimates of 2(v) and spatial information on land cover, soil type and meteorological inputs to predict root zone 2(v) over a 611 km(2) watershed. A GIS was used to pre-process and geo-register spatial data sets for input into the soil water budget model, and analyze the results.