Review: Coastal groundwater optimization—advances, challenges, and practical solutions

Decision models are essential tools for coastal groundwater management (CGM). A combined simulation-optimization framework is employed to develop these models. One of the main barriers in the widespread application of these models for real-world cases is their large computational burden. Recent adva...

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Bibliographic Details
Published inHydrogeology journal Vol. 23; no. 6; pp. 1129 - 1154
Main Authors Ketabchi, Hamed, Ataie-Ashtiani, Behzad
Format Journal Article Book Review
LanguageEnglish
Published Berlin/Heidelberg Springer Berlin Heidelberg 01.09.2015
Springer Nature B.V
Subjects
Algorithms
Aquatic Pollution
Barriers
Climate change
Coastal
Coastal zone management
Computation
Computer simulation
Data acquisition
Earth and Environmental Science
Earth Sciences
Environmental impact
Geology
Geophysics/Geodesy
Groundwater flow
Groundwater management
Hydrogeology
Hydrology/Water Resources
Iran
Mathematical models
Optimization
Optimization techniques
Parallel processing
solutions
system optimization
systematic review
Waste Water Technology
Water Management
Water Pollution Control
Water Quality/Water Pollution
ISW, Iran
Iran
Parallel processing
Coastal groundwater
Evolutionary algorithms
Iran
Optimization
Online AccessGet full text
ISSN1431-2174
1435-0157
DOI10.1007/s10040-015-1254-1

Cover

Abstract Decision models are essential tools for coastal groundwater management (CGM). A combined simulation-optimization framework is employed to develop these models. One of the main barriers in the widespread application of these models for real-world cases is their large computational burden. Recent advances in efficient computational approaches and robust optimization methods can crack this barrier. This study surveys the scientific basis of CGM to provide an overview on this subject and reviews the-state-of-the-art to clarify recent developments and to outline ideas for improving the computational performance. Key details are presented on the performance and choice of possible robust tools such as efficient evolutionary algorithms (EAs), surrogate models, and parallel processing techniques. Then, the potential challenges remaining in this context are scrutinized, demonstrating open fields for further research, which include issues related to advances in simulating and optimizing phases such as introducing new robust algorithms and considering multi-objective purposes, implementing novel and high-performance tools, considering global concerns (e.g. climate change impacts), enhancing the existing models to fit the real world, and taking into account the complexities of real-world applications (e.g. uncertainties in the modeling parameters, and data acquisition). Finally, the outcomes of the systematic review are applied to solve a real-world CGM problem in Iran, to quantitatively examine the performance of combined implementation of some of the suggested tools. It is revealed that the required computational time is considerably reduced by as much as three orders of magnitude when correct combinations of robust EAs, surrogate model, and parallelization technique are utilized.
AbstractList Decision models are essential tools for coastal groundwater management (CGM). A combined simulation-optimization framework is employed to develop these models. One of the main barriers in the widespread application of these models for real-world cases is their large computational burden. Recent advances in efficient computational approaches and robust optimization methods can crack this barrier. This study surveys the scientific basis of CGM to provide an overview on this subject and reviews the-state-of-the-art to clarify recent developments and to outline ideas for improving the computational performance. Key details are presented on the performance and choice of possible robust tools such as efficient evolutionary algorithms (EAs), surrogate models, and parallel processing techniques. Then, the potential challenges remaining in this context are scrutinized, demonstrating open fields for further research, which include issues related to advances in simulating and optimizing phases such as introducing new robust algorithms and considering multi-objective purposes, implementing novel and high-performance tools, considering global concerns (e.g. climate change impacts), enhancing the existing models to fit the real world, and taking into account the complexities of real-world applications (e.g. uncertainties in the modeling parameters, and data acquisition). Finally, the outcomes of the systematic review are applied to solve a real-world CGM problem in Iran, to quantitatively examine the performance of combined implementation of some of the suggested tools. It is revealed that the required computational time is considerably reduced by as much as three orders of magnitude when correct combinations of robust EAs, surrogate model, and parallelization technique are utilized.Original Abstract: Des modeles d'aide a la decision sont des outils essentiels pour la gestion des eaux souterraines cotieres (GESC). Un cadre combinant simulation et optimisation est utilise pour developper ces modeles. Un des principaux obstacles dans l'application generalisee de ces modeles pour des cas reels est leur grande charge de calcul. Les avancees recentes dans les approches efficaces de calcul et les methodes robustes d'optimisation peuvent faire sauter ces obstacles. Cette etude recense les bases scientifiques de la gestion des eaux souterraines cotieres afin de fournir une revue du sujet et examine l'etat de l'art afin de clarifier les recents developpements et d'esquisser des idees pour l'amelioration des performances de calcul. Des details clefs sont presentes sur la performance et le choix des outils robustes possibles, tels que les algorithmes d'efficacite evolutionnaires (AEE), les modeles de substitution, et les techniques de calcul en parallele. Ensuite, les defis potentiels restant dans ce contexte sont examines, afin de demontrer les champs ouverts pour de plus amples recherches, qui comprennent les questions liees aux progres des phases de simulation et d'optimisation comme l'introduction de nouveaux algorithmes robustes et la consideration d'approches multi-objectifs, la mise en oeuvre de nouveaux outils a haute performance, le fait de surmonter des problemes globaux (impacts du changement climatique par ex.), l'amelioration des modeles existants pour s'adapter au monde reel, et la prise en consideration de la complexite des applications du monde reel (par exemple, les incertitudes dans les parametres de modelisation, et l'acquisition des donnees). Finalement, les resultats de cette revue systematique sont appliques pour resoudre un probleme reel de GESC en Iran, afin d'examiner quantitativement la performance de la mise en oeuvre combinee de certains outils proposes. Cela revele que le temps de calcul necessaire est considerablement reduit de plus de trois ordres de grandeur lorsque les combinaisons appropriees d'AEE, de modele de substitution, et de technique de parallelisation sont utilisees.
Decision models are essential tools for coastal groundwater management (CGM). A combined simulation-optimization framework is employed to develop these models. One of the main barriers in the widespread application of these models for real-world cases is their large computational burden. Recent advances in efficient computational approaches and robust optimization methods can crack this barrier. This study surveys the scientific basis of CGM to provide an overview on this subject and reviews the-state-of-the-art to clarify recent developments and to outline ideas for improving the computational performance. Key details are presented on the performance and choice of possible robust tools such as efficient evolutionary algorithms (EAs), surrogate models, and parallel processing techniques. Then, the potential challenges remaining in this context are scrutinized, demonstrating open fields for further research, which include issues related to advances in simulating and optimizing phases such as introducing new robust algorithms and considering multi-objective purposes, implementing novel and high-performance tools, considering global concerns (e.g. climate change impacts), enhancing the existing models to fit the real world, and taking into account the complexities of real-world applications (e.g. uncertainties in the modeling parameters, and data acquisition). Finally, the outcomes of the systematic review are applied to solve a real-world CGM problem in Iran, to quantitatively examine the performance of combined implementation of some of the suggested tools. It is revealed that the required computational time is considerably reduced by as much as three orders of magnitude when correct combinations of robust EAs, surrogate model, and parallelization technique are utilized.
Issue Title: Optimization for Groundwater Characterization and Management Decision models are essential tools for coastal groundwater management (CGM). A combined simulation-optimization framework is employed to develop these models. One of the main barriers in the widespread application of these models for real-world cases is their large computational burden. Recent advances in efficient computational approaches and robust optimization methods can crack this barrier. This study surveys the scientific basis of CGM to provide an overview on this subject and reviews the-state-of-the-art to clarify recent developments and to outline ideas for improving the computational performance. Key details are presented on the performance and choice of possible robust tools such as efficient evolutionary algorithms (EAs), surrogate models, and parallel processing techniques. Then, the potential challenges remaining in this context are scrutinized, demonstrating open fields for further research, which include issues related to advances in simulating and optimizing phases such as introducing new robust algorithms and considering multi-objective purposes, implementing novel and high-performance tools, considering global concerns (e.g. climate change impacts), enhancing the existing models to fit the real world, and taking into account the complexities of real-world applications (e.g. uncertainties in the modeling parameters, and data acquisition). Finally, the outcomes of the systematic review are applied to solve a real-world CGM problem in Iran, to quantitatively examine the performance of combined implementation of some of the suggested tools. It is revealed that the required computational time is considerably reduced by as much as three orders of magnitude when correct combinations of robust EAs, surrogate model, and parallelization technique are utilized.
Author Ataie-Ashtiani, Behzad
Ketabchi, Hamed
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Tue Oct 07 10:01:03 EDT 2025
Fri Jul 25 19:18:40 EDT 2025
Wed Oct 01 01:37:18 EDT 2025
Thu Apr 24 23:11:48 EDT 2025
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Issue 6
Keywords Parallel processing
Coastal groundwater
Evolutionary algorithms
Iran
Optimization
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PublicationSubtitle Official Journal of the International Association of Hydrogeologists
PublicationTitle Hydrogeology journal
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PublicationYear 2015
Publisher Springer Berlin Heidelberg
Springer Nature B.V
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Issue Title: Optimization for Groundwater Characterization and Management Decision models are essential tools for coastal groundwater management (CGM). A...
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SubjectTerms Algorithms
Aquatic Pollution
Barriers
Climate change
Coastal
Coastal zone management
Computation
Computer simulation
Data acquisition
Earth and Environmental Science
Earth Sciences
Environmental impact
Geology
Geophysics/Geodesy
Groundwater flow
Groundwater management
Hydrogeology
Hydrology/Water Resources
Iran
Mathematical models
Optimization
Optimization techniques
Parallel processing
solutions
system optimization
systematic review
Waste Water Technology
Water Management
Water Pollution Control
Water Quality/Water Pollution
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