Improving Seasonal Streamflow Forecasts for Surface Water Irrigation Districts By Incorporating Soil Moisture Information Derived from Remote Sensing

Surface water managers in the Great Plains face major challenges due to the regions drought-prone climate and large inter-annual variability in rainfall and streamflow, and they do not have access to seasonal streamflow forecasts like those widely-used in the snow-dominated watersheds of the western US. Recently completed work by the PIs shows that in-situ soil moisture measurements can be used to produce accurate streamflow forecasts in rainfall-dominated regions and are able to provide >50% improvement over streamflow forecasts based on antecedent precipitation alone. However, the use of this method is currently restricted to watersheds where data from in-situ soil moisture monitoring stations are readily available. The goal of the current research is to determine whether utilizing remotely-sensed soil moisture data will allow the creation of similarly effective seasonal streamflow forecasts in areas lacking in-situ soil moisture monitoring networks. Preliminary results indicate that forecasts which incorporate remote sensing-based soil moisture and groundwater level information are improved over precipitation-only forecasts in five test watersheds.