Contaminant Plume Migration in an Aquifer: Finite Element Modeling for the Analysis of Remediation Strategies: A Case Study

Groundwater resources are becoming more and more endangered of being depleted by over-exploitation and of being polluted as a consequence of environmentally insensitive economic activities and population growth in many regions and countries of the world. Causes and consequences of quantitative and qualitative changes in groundwater states can be separated by decades and centuries. Once contaminated or depleted, groundwater resources may be permanently impaired. This fact becomes especially obvious in the case of groundwater pollution by hazardous wastes. Necessary remediation strategies may be extremely time and money consuming. Therefore, the optimal design of such remediation strategies is of great importance. The paper describes the results of a case study dealing with historical and predictive modeling of the migration of a real contaminant plume in an alluvial aquifer threatening the nearby operating extraction wells for municipal water supply. As a modeling case study it primarily aims at modeling and examining current and intended remediation strategies. The consequences and benefits of a hydraulic barrier in continuous or intermittent operation and their combination with pumpage from interception wells are investigated and discussed. For these purposes a horizontal plane transport model based on a finite element approach has been developed and applied. The model has been tested and calibrated through a history matching procedure comparing model computations with observed field data, where hydrodynamic dispersivities are identified as principal parameters. The obtained prognostic results allow several practical conclusions on the design of remediation strategies. The used finite element model simulator FEFLOW has proved to be a convenient and powerful tool in modeling the complex flow and transport processes of the contaminant plume. It demonstrates the abilities in prospective simulations for decision purposes