Date of Award
Master of Science
Geological and Atmospheric Sciences
National Weather Service (NWS) forecasters currently have access to a limited set of models that may not be suitable for all Iowa basins or forecasting situations, such as small, fast responding streams. Flexible modeling systems that allow model configurations to change according to the watershed characteristics may provide useful predictive information to supplement existing forecast products. The United States Army Corps of Engineers (USACE) Hydrologic Engineering Center's Hydrological Modeling System (HEC-HMS) was examined for operational streamflow forecasting using two watersheds in central Iowa. The Green & Ampt equation was used for the infiltration component with soil parameters derived from the Water Erosion Prediction Project (WEPP) model run at Iowa State University. Observed precipitation data was obtained from the city of Ames' flash flood Alert network and radar precipitation estimates were obtained through the University of Iowa's Hydro-NEXRAD project. Calibration and verification of the modeling system was done through an operational perspective to test the model's applicability at NWS Weather Forecast Offices (WFO). Model development was done using observed precipitation and was conducted in several stages. The average peak timing error and average discharge peak error were reduced from 5.3 hours to 3.0 hours and 46% to 25%, respectively, from the first to the last calibration attempt. The calibrated model was tested with bias corrected NEXRAD precipitation estimations, which were derived using the Constant Altitude Plan Position Indicator (CAPPI) algorithm. The bias correction scheme was computed and applied at the watershed scale. When used as input to the HEC-HMS model, the NEXRAD precipitation estimates increased the peak timing error to 8.8 hours, but the discharge peak error decreased to 20%.
William Scott Lincoln
Lincoln, William Scott, "A modeling approach for operational flash flood forecasting for small-scale watersheds in central Iowa" (2009). Graduate Theses and Dissertations. 10715.