Abstract
This paper presents the results of employing a real-coded genetic algorithm (GA) to the problem of determining the optimal unit pulse response function (UPRF) using the historical data from watersheds. The existing linear programming (LP) formulation has been modified, and a new problem formulation is proposed. The proposed problem formulation consists of fewer decision variables, only one constraint, and a non-linear objective function. The proposed problem formulation can be used to determine an optimal UPRF of a watershed from a single storm or a composite UPRF from multiple storms. The proposed problem formulation coupled with the solution technique of real-coded GA is tested using the effective rainfall and runoff data derived from two different watersheds and the results are compared with those reported earlier by others using LP methods. The model performance is evaluated using a wide range of standard statistical measures. The results obtained in this study indicate that the real-coded GA can be a suitable alternative to the problem of determining an optimal UPRF from a watershed. The proposed problem formulation when solved using real-coded GA resulted in smoother optimal UPRF without the need of additional constraints. The proposed problem formulation can be particularly useful in determining the optimal composite UPRF from multiple storms in large watersheds having large time bases due to its limited number of decision variables and constraints.
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