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Determination of an optimal unit of hydrograph of river basin using genetic algorithm

机译:用遗传算法确定流域水文最佳单位

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Unit hydrograph (UH) is used as a conceptual rainfall-runoff model for estimating peak discharge, timing of peak, and/or flood volume from design storms of a river basin, which are key inputs in the planning, design, operation, and management of various water resources projects in the basin and is the focus of hydrological modeling. In the past, majority of the optimal programs for determining the ordinates of a UH have employed objective functions and constraints that are linear in nature. Recently, evolutionary computing methods such as genetic algorithm (GA) have provided the researchers and modelers with tools that can model a highly non-linear, dynamic, and complex physical system with great ease. Most of the GA applications in engineering use binary-coded genetic algorithm, which has certain shortcomings such as precision, hill climbing etc., to overcome such problems of binary coded GA, real-coded GA (RGA) can be employed. The objectives of the present study are to (a) develop an optimal program consisting of non-linear objective function and constraints for the determination of the ordinates of a UH, and (b) solve the developed problem using real-coded GA. A new optimal program is proposed, which consists of fewer decision variables and constraints, and an objective function that is non-linear in nature. This paper presents the findings of probably the first attempt of employing the new solution technique of real-coded GA to the problem of determination of an optimal UH using the historical rainfall and runoff data from a basin. The rainfall-runoff data derived from Nenagh River basin, for twenty two storms have been employed to determine optimal UHs and test the performance of the new solution technique. Certain standard statistical performance evaluation measures was employed to evaluate the performance of the methodology developed. The preliminary results obtained are highly encouraging and indicate that the new technique of real-coded GA can be successfully applied to the problem of determining an optimal UH of a river basin.
机译:单位水位图(UH)用作概念性降雨径流模型,用于估算流域设计风暴中的峰值流量,峰值时间和/或洪水量,这是规划,设计,运营和管理的关键输入流域内各种水资源项目的研究,是水文模拟的重点。过去,大多数用于确定UH坐标的最佳程序都采用了本质上是线性的目标函数和约束。最近,诸如遗传算法(GA)之类的进化计算方法为研究人员和建模人员提供了可轻松建模高度非线性,动态和复杂物理系统的工具。工程中大多数遗传算法应用都是采用二进制编码遗传算法,该算法具有精度,爬坡等缺点,为克服二进制编码遗传算法的这些问题,可以采用实数编码遗传算法(RGA)。本研究的目的是(a)开发一个由非线性目标函数和约束组成的最优程序,用于确定UH的纵坐标,以及(b)使用实编码GA解决所开发的问题。提出了一种新的最优程序,该程序由较少的决策变量和约束以及性质为非线性的目标函数组成。本文介绍了可能的首次尝试,即使用实编码GA的新求解​​技术来解决基于盆地的历史降雨和径流数据确定最佳UH的问题。来自尼纳河流域的降雨-径流数据用于22次暴风雨,已被用来确定最佳的超高声速,并测试了新解决方案技术的性能。某些标准的统计性能评估方法用于评估所开发方法的性能。初步结果令人鼓舞,表明实码遗传算法的新技术可以成功地应用于确定流域最佳水位的问题。

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