Technical Papers
Feb 18, 2014

Genetic Programming in Groundwater Modeling

Publication: Journal of Hydrologic Engineering
Volume 19, Issue 12

Abstract

Determination of water-table elevation corresponding to aquifer recharge or discharge is an important issue in sustainable groundwater management. This approach necessitates the application of numerical simulation models that may require substantial amounts of input data related to aquifer parameters and specifications, even for modeling only part of the aquifer, which makes the calculations expensive. Moreover, comprehensive aquifer modeling is a time-consuming and computationally intensive process. Artificial intelligence tools can replace simulation models and decrease computational efforts by using input and output data sets without considering complex relations of the system to be modeled. This paper employs an adaptive neural fuzzy inference system (ANFIS) and genetic programming (GP) as artificial intelligence tools to extract governing groundwater flow equations in Ghaen and Karaj aquifers in Iran. For both aquifers, several input-output data sets, for both training and testing data sets, are determined by using a developed numerical simulation model [iterative alternating direction implicit method (IADIM)]. In addition, the water table elevation at each cell in the model is considered to be a function of aquifer recharge and discharge at the current period as well as water table elevation at the previous period. Application of ANFIS and GP models in these case studies illustrates the superior flexibility of GP over ANFIS in time series modeling. In fact, GP provides water-table elevation results with less root mean squared error (RMSE) as the error criterion, especially in the testing data set. Thus, GP is a good candidate for use in groundwater modeling.

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Go to Journal of Hydrologic Engineering
Journal of Hydrologic Engineering
Volume 19Issue 12December 2014

History

Received: Apr 10, 2013
Accepted: Feb 16, 2014
Published online: Feb 18, 2014
Published in print: Dec 1, 2014
Discussion open until: Dec 16, 2014

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Authors

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Elahe Fallah-Mehdipour, Ph.D. [email protected]
Dept. of Irrigation and Reclamation Engineering, Faculty of Agricultural Engineering and Technology, College of Agriculture and Natural Resources, Univ. of Tehran, Karaj, 3158777871 Tehran, Iran. E-mail: [email protected]
Omid Bozorg Haddad [email protected]
Associate Professor, Dept. of Irrigation and Reclamation Engineering, Faculty of Agricultural Engineering and Technology, College of Agriculture and Natural Resources, Univ. of Tehran, Karaj, 3158777871 Tehran, Iran (corresponding author). E-mail: [email protected]
Miguel A. Mariño, Dist.M.ASCE [email protected]
Distinguished Professor Emeritus, Dept. of Land, Air and Water Resources, Dept. of Civil and Environmental Engineering, and Dept. of Biological and Agricultural Engineering, Univ. of California, 139 Veihmeyer Hall, Davis, CA 95616-8628. E-mail: [email protected]

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