Analyzing Forecasting Techniques for Optimizing Flow Releases in Multi-Storage Systems for Flood Mitigation

As floods become more frequent and severe globally, effective flood control measures are essential for mitigating the impacts of such events. Multi-storage systems, consisting of multiple reservoirs or storage facilities, offer a viable approach for managing floodwaters. However, determining the optimal flow releases from these systems to minimize flood risks requires accurate forecasting techniques. The review surveys relevant studies and research articles that focus on the forecasting of optimal flow releases in multi-storage systems for controlling floods. It examines various forecasting methods and models used in the literature, such as linear programming, dynamic programming, genetic algorithms, and particle swarm optimization. The strengths, limitations, and applications of these techniques are assessed, considering factors such as accuracy, lead time, and the ability to incorporate system constraints. This paper highlights the importance of accurate flow release forecasting for effective flood control in multi-storage systems. It identifies gaps and challenges in the previous works and suggests areas for further exploration. The outcomes of this review advance our knowledge of the state of the art in forecasting optimal flow releases for flood control in multi-storage systems, providing valuable insights for researchers, practitioners, and decision-makers involved in water resources management and flood risk reduction.