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Development of a Multi-objective Optimal Operation Model of a Dam using Meteorological Ensemble Forecasts for Flood Control
Development of a Multi-objective Optimal Operation Model of a Dam using Meteorological Ensemble Forecasts for Flood Control
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Development of a Multi-objective Optimal Operation Model of a Dam using Meteorological Ensemble Forecasts for Flood Control
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Development of a Multi-objective Optimal Operation Model of a Dam using Meteorological Ensemble Forecasts for Flood Control
Development of a Multi-objective Optimal Operation Model of a Dam using Meteorological Ensemble Forecasts for Flood Control

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Development of a Multi-objective Optimal Operation Model of a Dam using Meteorological Ensemble Forecasts for Flood Control
Development of a Multi-objective Optimal Operation Model of a Dam using Meteorological Ensemble Forecasts for Flood Control
Journal Article

Development of a Multi-objective Optimal Operation Model of a Dam using Meteorological Ensemble Forecasts for Flood Control

2025
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Overview
Reservoir operation in flood conditions on hourly time scales poses significant difficulties due to the inherent uncertainty of inflow forecasts. Hence, incorporating ensemble flood forecasts into real-time reservoir operation optimization has rarely been investigated to effectively address uncertainties in inflow forecasts for flood control, let alone its added value compared to no-forecast operating scheme in multi-objective reservoir operating system. This research first investigates the potential of sequential Long Short-Term Memory networks to forecast one-day-ahead ensemble inflow floods based on numerical weather prediction data. Next, a new framework has been developed to incorporate ensemble inflow forecasts into multi-objective reservoir operation optimization using grid search-based genetic algorithm. Finally, we implemented our proposed ensemble-based operating method on the Dez dam basin in Iran and compared it with the benchmark no-forecast operating approach. The results revealed that the Long Short-Term Memory model reasonably performed well to propagate uncertainty in short-term ensemble inflow forecasts. In addition, the ensemble-based operating method could reduce release peaks and increase reservoir storage more than that of a deterministic (no-forecast) operating approach. Our findings demonstrated that the applicability of a skillful ensemble-based scheme in reservoir flood control operations could be effective in decreasing flood damage and water shortage.