Sustainable groundwater modeling using single- and multi-objective optimization algorithms
This study presents the first attempt to link the multi-algorithm genetically adaptive search method (AMALGAM) with a groundwater model to define pumping rates within a well distributed set of Pareto solutions. The pumping rates along with three minimization objectives, i.e. minimizing shortage affe...
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| Published in | Journal of hydroinformatics Vol. 19; no. 1; pp. 97 - 114 |
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| Main Authors | , , , |
| Format | Journal Article |
| Language | English |
| Published |
London
IWA Publishing
01.01.2017
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| Subjects | |
| Online Access | Get full text |
| ISSN | 1464-7141 1465-1734 1465-1734 |
| DOI | 10.2166/hydro.2016.006 |
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| Abstract | This study presents the first attempt to link the multi-algorithm genetically adaptive search method (AMALGAM) with a groundwater model to define pumping rates within a well distributed set of Pareto solutions. The pumping rates along with three minimization objectives, i.e. minimizing shortage affected by the failure to supply, modified shortage index and minimization of extent of drawdown within prespecified regions, were chosen to define an optimal solution for groundwater drawdown and subsidence. Hydraulic conductivity, specific yield parameters of a modular three-dimensional finite-difference (MODFLOW) groundwater model were first optimized using Cuckoo optimization algorithm (COA) by minimizing the sum of absolute deviation between the observed and simulated water table depths. These parameters were then applied in AMALGAM to optimize the pumping rate variables for an arid groundwater system in Iran. The Pareto parameter sets yielded satisfactory results when maximum and minimum drawdowns of the aquifer were defined in a range of −40 to +40 cm/year. Overall, ‘Modelling – Optimization – Simulation’ procedure was capable to compute a set of optimal solutions displayed on a Pareto front. The proposed optimal solution provides sustainable groundwater management alternatives to decision makers in arid region. |
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| AbstractList | This study presents the first attempt to link the multi-algorithm genetically adaptive search method (AMALGAM) with a groundwater model to define pumping rates within a well distributed set of Pareto solutions. The pumping rates along with three minimization objectives, i.e. minimizing shortage affected by the failure to supply, modified shortage index and minimization of extent of drawdown within prespecified regions, were chosen to define an optimal solution for groundwater drawdown and subsidence. Hydraulic conductivity, specific yield parameters of a modular three-dimensional finite-difference (MODFLOW) groundwater model were first optimized using Cuckoo optimization algorithm (COA) by minimizing the sum of absolute deviation between the observed and simulated water table depths. These parameters were then applied in AMALGAM to optimize the pumping rate variables for an arid groundwater system in Iran. The Pareto parameter sets yielded satisfactory results when maximum and minimum drawdowns of the aquifer were defined in a range of −40 to +40 cm/year. Overall, ‘Modelling – Optimization – Simulation’ procedure was capable to compute a set of optimal solutions displayed on a Pareto front. The proposed optimal solution provides sustainable groundwater management alternatives to decision makers in arid region. |
| Author | Akbarpour, A. Sadeghi-Tabas, S. Samadi, S. Z. Pourreza-Bilondi, M. |
| Author_xml | – sequence: 1 givenname: S. surname: Sadeghi-Tabas fullname: Sadeghi-Tabas, S. organization: Department of Civil Engineering, Iran University of Science and Technology (IUST), Tehran, Iran E-mail: sadeghitabas@yahoo.com, Department of Water Engineering, University of Birjand, Birjand, Iran – sequence: 2 givenname: S. Z. surname: Samadi fullname: Samadi, S. Z. organization: Department of Civil and Environmental Engineering, University of South Carolina, Columbia, South Carolina – sequence: 3 givenname: A. surname: Akbarpour fullname: Akbarpour, A. organization: Department of Civil Engineering, University of Birjand, Birjand, Iran – sequence: 4 givenname: M. surname: Pourreza-Bilondi fullname: Pourreza-Bilondi, M. organization: Department of Water Engineering, University of Birjand, Birjand, Iran |
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| SubjectTerms | Adaptive algorithms Adaptive search techniques Algorithms Annealing Aquifers Arid regions Arid zones Computer simulation Decision making Drawdown Elitism Finite difference method Fuzzy sets Genetic algorithms Groundwater Groundwater management Groundwater table Linear programming Mathematical models Methods Modelling Multiple objective analysis Objectives Optimization Parameters Pareto optimum Problems Pumping Pumping rates Solutions Specific yield Subsidence Sustainability Sustainability management Three dimensional models Water shortages Water table |
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| Title | Sustainable groundwater modeling using single- and multi-objective optimization algorithms |
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