In this paper we present an on-going effort to utilize available soil moisture data. This study evaluates the performance of a distributed hydrological model using runoff and soil moisture over 75 basins with watershed areas varying from 20 km2 to 15,000 km2. These basins are selected in a region where unique soil moisture data of the Oklahoma Mesonet are available. While simulated runoff is compared to measured streamflow at a basin outlet, simulated soil moisture is compared to basin average soil moisture derived from Oklahoma Mesonet observations. Our results show that the modified Sacramento model driven by a priori parameters performs reasonably well and allows explicit estimation of soil moisture at desired layers. Annual, monthly, and 10-day runoff volumes are found in good agreement with observed data for a range of spatial scales. Simulated and observed soil moisture of the 0–25 cm layer agrees well with a slight (9%) negative bias. However, 25–75 cm layer soil moisture shows a significant (26%) negative bias for most watersheds located in a dry region with P/PE<0.8.
Distributed model, Prediction, Runoff, Soil moisture, Space-time averaging
