A multi-level method for groundwater remediation management accommodating non-competitive objectives

Abstract

No attempts have been found on dealing with a set of non-competitive (or leader-follower-interactive) objectives when performing optimal groundwater remediation management. This study presents a multi-level nonlinear simulation-optimization (ML-NSO) model for groundwater remediation management when objectives should be satisfied at multiple levels. This model is formulated by integrating health-risk assessment (at the residential concern level), energy assessment (at the energy concern level) and contamination forecasting (at the environmental concern level) within a general framework. The capabilities and effectiveness of the developed model are illustrated through a real-world case located at Cantuar, Saskatchewan in Canada. Results facilitate (a) generating non-compromised solutions in association with the optimal strategies regarding groundwater injection and extraction, (b) displaying the distribution of contaminant concentration and carcinogenic risks for human health, and estimating the corresponding energy consumption, (c) resolving of conflicts and interactions among residential, energy, and environmental requirements. Moreover, the performance of ML-NSO model is enhanced by comparing with the single-level and multi-objective (SL-NSO and MO-NSO) models. Results show that ML-NSO model would assign higher priority on the residential and environmental concerns by tolerating a slight rise in energy cost. The ML-NSO model would provide more comprehensive and systematic policies with considering the leader-follower relationship within system.