Improving Flood Forecasting in the Susquehanna River Basin Using a Probabilistic Approach

Elaine Langone Center, Terrace Room

Accurate and reliable flood forecasts are important for flood prevention, minimizing flood damages, decision making and sustainable watershed management. Uncertainty in flood forecasting may arise from meteorological variables (i.e. precipitation and temperature) as well as different hydrologic sources, such as, hydrologic model structure, parameters, initial and boundary conditions. Probabilistic flood forecasting using ensembles can reduce the uncertainty in flood forecasting and improve accuracy. In this study, we use meteorological forecast ensembles (precipitation and land surface temperature) from the National Centers for Environmental Prediction (NCEP) 11-member Global Ensemble Forecast System Reforecast version 2 (GEFSRv2) to force a distributed hydrologic model and produce streamflow forecasts. The quality of streamflow forecasts are verified in a small headwater basin and a large basin in the north branch of Susquehanna River. The verification is done based on the streamflow amount, forecast lead time, season, and aggregation period for various forecasting scenarios. Ultimately, the verification results provide valuable and useful guidance regarding the potential application and accuracy of probabilistic flood forecasting in the Susquehanna River basin.