A novel simulation–optimization strategy for stochastic‐based designing of flood control dam: A case study of Jamishan dam

This study presents a novel stochastic simulation–optimization approach for optimum designing of flood control dam through incorporation of various sources of uncertainties. The optimization problem is formulated based on two objective functions, namely, annual cost of dam implementation and dam overtopping probability, as those are the two major concerns in designing flood control dams. The nondominated solutions are obtained through a multi‐objective particle swarm optimization (MOPSO) approach. Results indicate that stochastic sources have a significant impact on Pareto front solutions. The distance index ( DI ) reveals the rainfall depth ( DI = 0.41 ) as the most significant factor affecting the Pareto front and the hydraulic parameters ( DI = 0.02 ) as the least. The dam overtopping probability is found to have a higher sensitivity to the variability of stochastic sources compared to annual cost of dam implementation. The values of interquartile range ( IQR ) indicate that the dam overtopping probability is least uncertain when all stochastic sources are considered ( IQR = 0.25% ). The minimum annual cost of dam implementation (2.79 M$) is also achieved when all stochastic sources are considered in optimization process. The results indicate the potential of the proposed method to be used for better designing of flood control dam through incorporation of all sources of uncertainty.

Abstract licence: CC BY-NC

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