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A comparative study in aquifer parameter estimation using MFree point collocation method with evolutionary algorithms

Journal of hydroinformatics, 2019-05, Vol.21 (3), p.455-473 [Peer Reviewed Journal]

Copyright IWA Publishing May 2019 ;ISSN: 1464-7141 ;EISSN: 1465-1734 ;DOI: 10.2166/hydro.2019.105

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Title:
A comparative study in aquifer parameter estimation using MFree point collocation method with evolutionary algorithms
Author: Thomas, Alice ; Eldho, T. I. ; Rastogi, A. K. ; Majumder, Partha
Subjects: Aquifers ; Collocation methods ; Comparative analysis ; Comparative studies ; Computer simulation ; Confined aquifers ; Contaminants ; Evolutionary algorithms ; Evolutionary computation ; Finite element method ; Genetic algorithms ; Groundwater ; Groundwater flow ; Groundwater movement ; Groundwater pollution ; Heuristic ; Hydraulic engineering ; Hydrology ; Inverse problems ; Mathematical models ; Meshless methods ; Methods ; Objective function ; Optimization ; Optimization techniques ; Parameter estimation ; Parameters ; Piezometric head ; Reliability analysis ; Simulation ; State variable ; Studies ; Swarm intelligence ; Transmissivity ; Transport processes ; Water flow
Is Part Of: Journal of hydroinformatics, 2019-05, Vol.21 (3), p.455-473
Description: Abstract In this study, we present a comparative assessment of simulation-optimization (S-O) models to estimate aquifer parameters such as transmissivity, longitudinal dispersivity, and transverse dispersivity. The groundwater flow and contaminant transport processes are simulated using the mesh-free radial basis point collocation method (RPCM). Four different S-O models are developed by combining the RPCM model separately with genetic algorithm (GA), differential evolution (DE), cat swarm optimization (CSO), and particle swarm optimization (PSO). The objective of the S-O model is to minimize a composite objective function with transmissivity, longitudinal dispersivity, and transverse dispersivity as decision variables. Hydraulic head and contaminant concentration at observation points are the state variables. The S-O models are used to estimate aquifer parameters of a confined aquifer with nine zones. It is found that RPCM-based DE, CSO, and PSO models are more accurate in estimating aquifer parameters than RPCM-GA. However, for noisy observed data, the RPCM-CSO model outperforms other models. The efficiency of the RPCM-CSO model over other models is further established by performing reliability analysis to the noisy observed data set. The comparative study reflects the efficacy of CSO over GA, DE, and PSO.
Publisher: London: IWA Publishing
Language: English
Identifier: ISSN: 1464-7141
EISSN: 1465-1734
DOI: 10.2166/hydro.2019.105
Source: ProQuest Central

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A comparative study in aquifer parameter estimation using MFree point collocation method with evolutionary algorithms

Copyright IWA Publishing May 2019 ;ISSN: 1464-7141 ;EISSN: 1465-1734 ;DOI: 10.2166/hydro.2019.105

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