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首页> 外文期刊>Journal of Hydrology >Estimating net aquifer recharge and zonal hydraulic conductivity values for Mahi Right Bank Canal project area, India by genetic algorithm
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Estimating net aquifer recharge and zonal hydraulic conductivity values for Mahi Right Bank Canal project area, India by genetic algorithm

机译:用遗传算法估算印度马希右岸运河项目区净含水层补给量和地层导水率

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摘要

The paper presents a recent approach for inverse modeling of groundwater systems based upon a generic algorithm (GA) global optimization technique which is coupled with a Galerkin's finite element (FEM) flow simulation mode]. Applicability, adequacy and robustness of the developed numerical model is tested by estimating the transmissivity parameter in various zones of a synthetic confined aquifer. The numerical model is applied to estimate hydraulic conductivity and recharge parameters of various zones in the Mahi Right. Bank Canal (MRBC) project area. The solutions of synthetic and field aquifer problems are compared with another inverse model using the Gauss-Newton-Marquardt (GNM) method. Largely, the GA results are better compared to GNM parameter estimates, except, when no measurement errors in the observation head values are assumed. Head distribution computed using the estimated parameters for the MRBC aquifer is found closer to observed head distribution in the aquifer domain. From the adequacy of the estimated parameters the study concludes that the genetic algorithm approach can be successfully used for inverse modeling of regional aquifers where reliable parameter estimation is an important but difficult task: for real system simulation. (C) 2001 Elsevier Science B.V. All rights reserved. [References: 20]
机译:本文提出了一种基于通用算法(GA)全局优化技术并结合Galerkin有限元(FEM)流量模拟模式的地下水系统逆建模方法。通过估算合成密闭含水层各个区域的透射率参数,测试了所开发数值模型的适用性,充分性和鲁棒性。数值模型被用来估计马希河右岸各个区域的水力传导率和补给参数。银行运河(MRBC)项目区。使用高斯-牛顿-马夸特(GNM)方法,将合成和田间含水层问题的解决方案与另一个反模型进行了比较。在很大程度上,与GNM参数估计值相比,GA结果要好一些,除非假定观测头值中没有测量误差。发现使用MRBC含水层的估计参数计算的水头分布更接近在含水层域中观察到的水头分布。从估计参数的充分性来看,研究得出结论,遗传算法方法可以成功地用于区域含水层的反演,而可靠的参数估计是一项重要但艰巨的任务:用于真实系统仿真。 (C)2001 Elsevier Science B.V.保留所有权利。 [参考:20]

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