Optimal remediation design and simulation of groundwater flow coupled to contaminant transport using genetic algorithm and radial point collocation method (RPCM)

Seyedpour, Seyed Morteza; Kirmizakis, Panagiotis; Brennan, Peter A.; Doherty, Rory; Ricken, Tim

doi:10.1016/j.scitotenv.2019.01.409

Cited by 41 publications

(14 citation statements)

References 37 publications

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“…The problem can thus be formulated as determining the location and number of wells as well as the required pumping rates at these wells such that the cost is minimum and the desired quality levels are maintained. Several studies used EAs for solving the groundwater remediation problems via the simulation-optimization framework such as GA (Huang & Mayer 1997;Wang & Zheng 1997;Sun & Zheng 1999;Smalley et al 2000;Yoon & Shoemaker 2001;Zheng & Wang 2002;Babbar & Minsker 2006;Wu et al 2006;Park et al 2007;Bayer et al 2008;Seyedpour et al 2019), SA (Kobayashi et al 2008); MOGA (Erickson et al 2002;Mantoglou & Kourakos 2007;Singh et al 2008), NSGA-II (Singh & Chakrabarty 2011;Ouyang et al 2017), etc. More details of these EAs applications are also elaborated in Table 9.…”

Section: Applications In Reservoir Operation and Irrigation Systemsmentioning

confidence: 99%

Evolutionary algorithms, swarm intelligence methods, and their applications in water resources engineering: a state-of-the-art review

Reddy

Kumar

2020

H2Open Journal

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During the last three decades, the water resources engineering field has received a tremendous increase in the development and use of meta-heuristic algorithms like evolutionary algorithms (EA) and swarm intelligence (SI) algorithms for solving various kinds of optimization problems. The efficient design and operation of water resource systems is a challenging task and requires solutions through optimization. Further, real-life water resource management problems may involve several complexities like nonconvex, nonlinear and discontinuous functions, discrete variables, a large number of equality and inequality constraints, and often associated with multi-modal solutions. The objective function is not known analytically, and the conventional methods may face difficulties in finding optimal solutions. The issues lead to the development of various types of heuristic and meta-heuristic algorithms, which proved to be flexible and potential tools for solving several complex water resources problems. This paper provides a review of state-of-the-art methods and their use in planning and management of hydrological and water resources systems. It includes a brief overview of EAs (genetic algorithms, differential evolution, evolutionary strategies, etc.) and SI algorithms (particle swarm optimization, ant colony optimization, etc.), and applications in the areas of water distribution networks, water supply, and wastewater systems, reservoir operation and irrigation systems, watershed management, parameter estimation of hydrological models, urban drainage and sewer networks, and groundwater systems monitoring network design and groundwater remediation. This paper also provides insights, challenges, and need for algorithmic improvements and opportunities for future applications in the water resources field, in the face of rising problem complexities and uncertainties.

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Section: Applications In Reservoir Operation and Irrigation Systemsmentioning

confidence: 99%

Evolutionary algorithms, swarm intelligence methods, and their applications in water resources engineering: a state-of-the-art review

Reddy

Kumar

2020

H2Open Journal

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“…The concept inspired by the process of natural selection consisted of selection, crossover, mutation, reproduction and replacement searches for a global optimal or a near-global optimal solution. For a comprehensive understanding of GA and its application in water resources management, readers are referred to [54][55][56][57][58][59]. The GA method follows these steps:…”

Section: Appendix B Particle Swarm Optimization (Pso)mentioning

confidence: 99%

Multi-well capture zones in strip-shaped aquifers

2020

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“…The representation of the geological structure through a 3D model facilitates its understanding and depicts the hydrogeological setting [22]. The dynamics linked to the groundwater flow play a fundamental role in the transport of contaminants [23]. The geolocalization of the concentration data of chemical species provides a complete picture on the trend in time and space of contaminant concentrations.…”

Section: The Integrated Geodatabase To Support the Remediation Strategymentioning

confidence: 99%

Hydrogeochemical Model Supporting the Remediation Strategy of a Highly Contaminated Industrial Site

Ciampi

Esposito

Papini

2019

Water

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Delineation and understanding the geology and the hydrogeology of a contaminated site, considering its chemical and its biological aspects, are fundamental requirements for successful environmental remediation. The aim of this research is to provide some evidence about the effectiveness of a hydrogeochemical geodatabase to facilitate the integrated management, representation and analysis of heterogeneous data, enabling the appropriate selection, design and optimization of an effective remediation strategy. This study investigates a new technology for the remediation of a dense non-aqueous phase liquid aged source zone, with the aim of enhancing in situ bioremediation by coupling groundwater circulation wells with a continuous production system of electron donors. The technology was verified through a pilot test carried out at an industrial site highly contaminated by chlorinated aliphatic hydrocarbons. The multidisciplinary conceptual model confirmed a complex hydrogeological situation, with the occurrence of active residual sources in low permeability layers. The pilot test results clearly demonstrate a significant mobilization of contaminants from the low permeability zone, and the possibility of favoring the in situ natural attenuation mechanisms based upon biological reductive dechlorination. Different information related to the hydrogeochemical sphere must be integrated and taken into consideration when developing a reliable remediation strategy for contaminated sites.

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Optimal remediation design and simulation of groundwater flow coupled to contaminant transport using genetic algorithm and radial point collocation method (RPCM)

Abstract: et al., Optimal remediation design and simulation groundwater flow coupled to contaminant transport using genetic algorithm and radial point collocation method (RPCM), Science of the Total Environment,

Cited by 41 publications

References 37 publications

Evolutionary algorithms, swarm intelligence methods, and their applications in water resources engineering: a state-of-the-art review

Evolutionary algorithms, swarm intelligence methods, and their applications in water resources engineering: a state-of-the-art review

Multi-well capture zones in strip-shaped aquifers

Hydrogeochemical Model Supporting the Remediation Strategy of a Highly Contaminated Industrial Site

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