A hybrid simulation–optimization approach for solving the areal groundwater pollution source identification problems

Autor: M. Tamer Ayvaz
Rok vydání: 2016
Předmět:
Groundwater flow
0208 environmental biotechnology
Generalized reduced gradient methods
02 engineering and technology
Binary genetic algorithm
hydrological modeling
Pollution source identification
Hybrid simulation optimizations
Gradient methods
pollutant source
genetic algorithm
ILL-posed inverse problem
pollutant transport
Groundwater
Hybrid optimization approaches
Water Science and Technology
media_common
Groundwater pollution
concentration (composition)
geography.geographical_feature_category
spatial distribution
Simulation-optimization
MODFLOW
Pollution
Aquifers
inverse problem
Wells
Inverse problems
Optimization
Mathematical optimization
media_common.quotation_subject
Aquifer
Pollution sources
Genetic algorithm
Groundwater resources
Areal sources
Hydrology
geography
Genetic algorithms
020801 environmental engineering
Pollution concentration
Simulation optimization
time series analysis
Environmental science
Gradient method
hydraulic conductivity
Zdroj: Journal of Hydrology. 538:161-176
ISSN: 0022-1694
Popis: In this study, a new simulation-optimization approach is proposed for solving the areal groundwater pollution source identification problems which is an ill-posed inverse problem. In the simulation part of the proposed approach, groundwater flow and pollution transport processes are simulated by modeling the given aquifer system on MODFLOW and MT3DMS models. The developed simulation model is then integrated to a newly proposed hybrid optimization model where a binary genetic algorithm and a generalized reduced gradient method are mutually used. This is a novel approach and it is employed for the first time in the areal pollution source identification problems. The objective of the proposed hybrid optimization approach is to simultaneously identify the spatial distributions and input concentrations of the unknown areal groundwater pollution sources by using the limited number of pollution concentration time series at the monitoring well locations. The applicability of the proposed simulation-optimization approach is evaluated on a hypothetical aquifer model for different pollution source distributions. Furthermore, model performance is evaluated for measurement error conditions, different genetic algorithm parameter combinations, different numbers and locations of the monitoring wells, and different heterogeneous hydraulic conductivity fields. Identified results indicated that the proposed simulation-optimization approach may be an effective way to solve the areal groundwater pollution source identification problems. © 2016 Elsevier B.V..
Databáze: OpenAIRE
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