Analysis of Flood Forecast Uncertainty Usingthe WRF Predictionof Precipitation and Air Temperature

Uncertainty in predicted precipitation and air temperature are the main sources of the uncertainty in flood forecasting. In this study, the fuzzy set theory is used for assessment of impact that uncertainty in precipitation and air temperature data has on flood forecasting in the Dez basin in southwestern Iran. The precipitation and air temperature were predicted using the Weather Research and Forecasting (WRF) model. The results showed that the uncertainty in peak discharge and flood hydrograph volume was considerably higher due to uncertainty in the precipitation than in air temperature. It was observed that the uncertainty of the peak discharge due to the 10% uncertainty in precipitation and air temperature is 14.8% and 5.6%, respectively. Also, the uncertainty of the flood hydrograph volume due to the 10% uncertainty in precipitation and air temperature is 13.1% and 4.6%, respectively. Therefore, to reduce uncertainty in peak discharge and flood hydrograph volume, precipitation should be predicted more precisely than air temperature.