Characterization of an old municipal landfill (Grindsted, Denmark) as a groundwater pollution source: landfill history and leachate composition

1998 ◽  
Vol 16 (1) ◽  
pp. 3-13 ◽  
Author(s):  
Peter Kjeldsen ◽  
Aase Grundtvig ◽  
Pia Winther ◽  
Jens S. Andersen
Keyword(s):  
Groundwater Pollution ◽  
Pollution Source ◽  
Municipal Landfill ◽  
Leachate Composition

Characterization of an old municipal landfill (Grindsted, Denmark) as a groundwater pollution source: landfill hydrology and leachate migration

1998 ◽  
Vol 16 (1) ◽  
pp. 14-22 ◽  
Author(s):  
Peter Kjeldsen ◽  
Poul L. Bjerg ◽  
Kirsten Rügge ◽  
Thomas H. Christensen ◽  
Jørn K. Pedersen
Keyword(s):  
Groundwater Pollution ◽  
Pollution Source ◽  
Municipal Landfill

An almost-parameter-free harmony search algorithm for groundwater pollution source identification

2013 ◽  
Vol 68 (11) ◽  
pp. 2359-2366 ◽  
Author(s):  
Simin Jiang ◽  
Yali Zhang ◽  
Pei Wang ◽  
Maohui Zheng
Keyword(s):  
Groundwater Pollution ◽  
Source Identification ◽  
Search Algorithm ◽  
Harmony Search ◽  
Identification Problem ◽  
Pollution Source ◽  
Harmony Search Algorithm ◽  
Optimization Approach ◽  
Pollution Source Identification

The spatiotemporal characterization of unknown sources of groundwater pollution is frequently encountered in environmental problems. This study adopts a simulation–optimization approach that combines a contaminant transport simulation model with a heuristic harmony search algorithm to identify unknown pollution sources. In the proposed methodology, an almost-parameter-free harmony search algorithm is developed. The performance of this methodology is evaluated on an illustrative groundwater pollution source identification problem, and the identified results indicate that the proposed almost-parameter-free harmony search algorithm-based optimization model can give satisfactory estimations, even when the irregular geometry, erroneous monitoring data, and prior information shortage of potential locations are considered.

scholarly journals Genetic algorithm hyper-parameter optimization using Taguchi design for groundwater pollution source identification

2018 ◽  
Vol 19 (1) ◽  
pp. 137-146 ◽  
Author(s):  
Xuemin Xia ◽  
Simin Jiang ◽  
Nianqing Zhou ◽  
Xianwen Li ◽  
Lichun Wang
Keyword(s):  
Genetic Algorithm ◽  
Groundwater Pollution ◽  
Parameter Tuning ◽  
Pollution Source ◽  
Heterogeneous Porous Media ◽  
Optimization Approach ◽  
Human Beings ◽  
Transient Transport ◽  
Tuning Method ◽  
Pollutant Source

Abstract Groundwater pollution has been a major concern for human beings, since it is inherently related to people's health and fitness and the ecological environment. To improve the identification of groundwater pollution, many optimization approaches have been developed. Among them, the genetic algorithm (GA) is widely used with its performance depending on the hyper-parameters. In this study, a simulation–optimization approach, i.e., a transport simulation model with a genetic optimization algorithm, was utilized to determine the pollutant source fluxes. We proposed a robust method for tuning the hyper-parameters based on Taguchi experimental design to optimize the performance of the GA. The effectiveness of the method was tested on an irregular geometry and heterogeneous porous media considering steady-state flow and transient transport conditions. Compared with traditional GA with default hyper-parameters, our proposed hyper-parameter tuning method is able to provide appropriate parameters for running the GA, and can more efficiently identify groundwater pollution.

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