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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Vydané v:Journal of hydroinformatics Ročník 19; číslo 1; s. 97 - 114
Hlavní autori: Sadeghi-Tabas, S., Samadi, S. Z., Akbarpour, A., Pourreza-Bilondi, M.
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: London IWA Publishing 01.01.2017
Predmet:
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
ISSN:1464-7141, 1465-1734
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Shrnutí: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.
Bibliografia:ObjectType-Article-1
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ISSN:1464-7141
1465-1734
DOI:10.2166/hydro.2016.006