A coupled simulation-optimization approach for groundwater remediation design under uncertainty: An application to a petroleum-contaminated site

A new surrogate-assisted optimization formulation for groundwater remediation design was developed. A stationary Eulerian travel time model was used in lieu of a conservative solute transport model. The decision variables of the management model are well locations and their flow rates. The objective function adjusts the residence time distribution between all pairs of injection-production wells in the remediation system. This goal is achieved by using the Lorenz coefficient as an effective metric to rank the relative efficiency of many remediation policies. A discrete adjoint solver was developed to provide the sensitivity of the objective function with respect to changes in decision variables. The quality management model was checked with simple solutions and then applied to hypothetical two- and three-dimensional test problems. The performance of the simulation-optimization approach was evaluated by comparing the initial and optimal remediation designs using an advective-dispersive solute transport simulator. This study shows that optimal designs simultaneously delay solute transport breakthrough at pumping wells and improve the sweep efficiency leading to smaller cleanup times. Well placement optimization in heterogeneous porous media was found to be more important than well rate optimization. Additionally, optimal designs based on two-dimensional models were found to be more optimistic suggesting a direct use of three-dimensional models in a simulation-optimization framework. The computational budget was drastically reduced because the proposed surrogate-based quality management model is generally cheaper than one single solute transport simulation. The introduced model could be used as a fast, but first-order, approximation method to estimate pump-and-treat capital remediation costs. The results show that physically based low-fidelity surrogate models are promising computational approaches to harness the power of quality management models for complex applications with practical relevance.

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Comparing Formulations for Multi-Objective Groundwater Remediation Design Under Uncertainty

Critical Transitions in Water and Environmental Resources Management ◽

10.1061/40737(2004)237 ◽

2004 ◽

Cited By ~ 1

Author(s):

Omar Beckford ◽

Amy B. Chan-Hilton

Keyword(s):

Groundwater Remediation ◽

Design Under Uncertainty ◽

Multi Objective ◽

Remediation Design

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Health-Risk-Included Optimal Model for Groundwater Remediation Design under Uncertainty: A Case Study in Western Canada

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.955-959.1065 ◽

2014 ◽

Vol 955-959 ◽

pp. 1065-1068

Author(s):

Xing Fan ◽

Jing Li ◽

Jia Qi Zhang ◽

Li He ◽

Hong Wei Lu

Keyword(s):

Health Risk ◽

Groundwater Remediation ◽

Optimal Strategies ◽

Contaminated Site ◽

Risk Level ◽

Western Canada ◽

Optimal Model ◽

Remediation Strategies ◽

Remediation Design

Groundwater has been polluted in different countries, and the pollutants threat to public health. In groundwater remediation design, it is necessary to take health risk level into consideration, which should be as important as the environmental standards. This study advances a health-risk-included optimal model for groundwater remediation design under relaxed environmental standard constraints. It can simulate and optimize the groundwater remediation strategies, and help the decision makers to obtain optimal strategies from various remediation alternatives. The model is applied for a petroleum contaminated site in western Canada to simulate the Pump and Treat system.

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