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Simultaneous estimation of groundwater recharge rates,associated zone structures, and hydraulic conductivity valuesusing fuzzy c-means clustering and harmony search optimisation algorithm: a case study of the Tahtali watershed

机译:地下水再充电率,相关区域结构和液压导电性的同时估计模糊C-MEARE聚类和和谐搜索优化算法 - 以塔哈利流域为例

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The aim of this study is to present a linked simulation-optimisation model to estimate the groundwater recharge rates, their associated zone structures, and hydraulic conductivity values for regional, steady-state groundwater flow models. For the zone structure estimation problem the fuzzy c-means clustering (FCM) method was used. The association of zone structures with the spatial distribution of groundwater recharge rates was then accomplished using an optimisation approach where the heuristic harmony search (HS) algorithm was used. Since the solution was obtained by a heuristic algorithm, the optimisation process was able to use a non-specific initial solution, i.e. an initial solution that does not have to be close to the final solution. The HS-based optimisation model determines the shape of zone structures, their corresponding recharge rates and hydraulic conductivity values by minimizing the root mean square error (R) between simulated and observed head values at observation wells and springs, respectively. To determine the best recharge zone structure, the identification procedure starts with computation of one zone and systematically increased the zone number until the optimum zone structure is identified. Subsequently, the performance of the proposed simulation-optimisation model was evaluated on the Tahtali watershed (Izmir, Turkey), an urban watershed for which a seasonal steady-state groundwater flow model was developed for a previous study. The results of our study demonstrated that the proposed simulation-optimisation model is an effective way to calibrate the groundwater flow models for the cases where tangible information about the groundwater recharge distribution does not exist.
机译:这项研究的目的是介绍一个链接仿真优化模型来估计地下水补给率,其相关的区域结构和液压电导率值区域,稳态地下水流模型。该区域结构估计问题聚类使用(FCM)方法模糊c均值。然后用地下水补给率的空间分布区域结构的相关性使用其中使用启发式和声搜索(HS)算法优化的方法来实现。由于该解决方案是通过一种启发式算法获得,优化过程能够使用非特异性初始解,即不具有为接近最终解的初始解。基于HS-优化模型通过在观测孔和弹簧,分别最小化模拟和观察到的头值之间的均方根误差(R)确定区的结构,其相应的补给速率和渗透系数的形状。以确定最佳的补给区结构,直到最佳区结构是确定与一个区的计算识别过程开始,系统地增加了区域号。随后,所提出的仿真优化模型的性能上Tahtali评估流域(土耳其伊兹密尔),用于其季节性的稳态地下水流模型是针对先前的研究开发了一个城市的分水岭。我们的研究结果表明,所提出的仿真优化模型来校准,其中对地下水的补给分发有形的信息不存在情况下的地下水流模型的有效途径。

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