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...

Full description

Saved in:
Bibliographic Details
Published inJournal of hydroinformatics Vol. 19; no. 1; pp. 97 - 114
Main Authors Sadeghi-Tabas, S., Samadi, S. Z., Akbarpour, A., Pourreza-Bilondi, M.
Format Journal Article
LanguageEnglish
Published London IWA Publishing 01.01.2017
Subjects
Online AccessGet full text
ISSN1464-7141
1465-1734
1465-1734
DOI10.2166/hydro.2016.006

Cover

More Information
Summary: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.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:1464-7141
1465-1734
1465-1734
DOI:10.2166/hydro.2016.006