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Assessment of Re-Forecast Data in the Modeling of Extreme Rainfall-Runoff Events (Case Study: Floods in the Bakhtiari Basin, Iran, March-April 2019) | ||
Water Harvesting Research | ||
دوره 7، شماره 2، آذر 2024، صفحه 246-257 اصل مقاله (1001.84 K) | ||
نوع مقاله: Research Paper | ||
شناسه دیجیتال (DOI): 10.22077/jwhr.2024.7445.1157 | ||
نویسندگان | ||
Amin Eidipour؛ Mohammad Amin Maddah* ؛ Ali Mohammad Akhoond-Ali | ||
Department of Hydrology and Water Resources, Faculty of Water and Environmental Engineering, Shahid Chamran University of Ahvaz, Ahvaz, Iran. | ||
چکیده | ||
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 GEFSv12 re-forecast data as an input of the HEC-HMS model for forecasting floods due to the extreme precipitation in March/April 2019 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 10 days. A sequence of predictions for flood warnings was analyzed when 50% of the members exceeded the threshold inflows of 1000 and 1500 m³/s. The relative volume error values for the control member and the ensemble mean for five days ahead were -15% and -22%, 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 1500 m³/s, flood warnings are issued with a lead time of 5 to 8 days. | ||
کلیدواژهها | ||
Ensemble Forecasting؛ Flood Warning؛ GEFSv12؛ Hydrological Model؛ Reservoir Operation | ||
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