Assessment of Re-Forecast Data in the Modeling of Extreme Rainfall-Runoff Events (Case Study: Floods in the Bakhtiari Basin, Iran, March-April ۲۰۱۹)

Predicting inflow into reservoirs is essential for their operation during floods, particularly in mountainous watersheds characterized by snow-rain regimes. The objective of this research is to evaluate the GEFSv۱۲ re-forecast data as an input of the HEC-HMS model for forecasting floods due to the extreme precipitation in March/April ۲۰۱۹ in the reservoir of Bakhtiari dam in southwestern Iran. So, ensemble flood forecasting (control and ensemble members) was conducted using extracted precipitation and temperature data with the lead-time up to ۱۰ days. A sequence of predictions for flood warnings was analyzed when ۵۰% of the members exceeded the threshold inflows of ۱۰۰۰ and ۱۵۰۰ m³/s. The relative volume error values for the control member and the ensemble mean for five days ahead were -۱۵% and -۲۲%, respectively. While previous studies in catchments with snow-rain regimes anticipated challenges in flood forecasting at mid-lead times, this research demonstrated that the proposed probabilistic framework could effectively issue flood warnings for events with a lead time of five days. To address and predict flooding at the Bakhtiari Dam with a threshold of ۱۵۰۰ m³/s, flood warnings are issued with a lead time of ۵ to ۸ days.

کلیدواژه ها:

ensemble forecasting ، flood warning ، GEFSv۱۲ ، hydrological model ، reservoir operation