Verification Using Remotely Sensed Data

Soil moisture is an important hydrologic variable that controls various land surface processes. In spite of its importance to agriculture and drought monitoring, soil moisture information is not widely available on a regional scale. However, long-term soil moisture information is essential for agricultural drought monitoring and crop yield prediction. The hydrologic model Soil and Water Assessment Tool (SWAT) was used to develop a long-term record of soil water at a fine spatial (16 km2) and temporal (weekly) resolution from historical weather data. The model was calibrated and validated using stream flow data. However, stream flow accounts for only a small fraction of the hydrologic water balance. Due to the lack of measured evapotranspiration or soil moisture data, the simulated soil water was evaluated in terms of vegetation response, using 16 years of normalized difference vegetation index (NDVI) derived from NOAA-AVHRR satellite data. The simulated soil water was well-correlated with NDVI (r as high as 0.8 during certain years) for agriculture and pasture land use types, during the active growing season April-September, indicating that the model performed well in simulating the soil water. The study provides a framework for using remotely sensed NDVI to verify the soil moisture simulated by hydrologic models in the absence of auxiliary measured data on ET and soil moisture, as opposed to just the traditional stream flow calibration and