Assessing data-scarce contaminated groundwater sites surrounding petrochemical industries

Abstract

A common problem when studying groundwater contamination in low-income countries is that data required for a detailed risk assessment are limited. This study presents a method for assessment of the potential impact of groundwater contamination by total petroleum hydrocarbons (TPH) in a data-scarce region. Groundwater modeling, using the MODFLOW, was used to simulate regional-scale flow pattern. Then, a semi-analytical contamination transport model was calibrated by minimization of the absolute errors between measured and modeled concentrations. The method was applied to a case study in Kazakhstan to assess the potential spreading of a TPH plume, based on historical observations. The limited data included general information about the local geology, observations of GW level in the area, and concentrations during 5 years of TPH in monitoring wells surrounding the source of the pollution. The results show that the plume could spread up to 2–6 km from the source, depending on estimate of the initial concentrations, until the concentration reaches permissible levels. Sensitivity analysis identified parameters of longitudinal and transverse dynamic dispersivity together with the plume of TPH spreading, as the priority subjects for future investigations. The proposed approach can be used as a tool for governmental and municipal decision-makers to better plan the usage of affected groundwater sites in data-scarce regions. It can also help to decrease the negative impact of contaminated GW on human health and to better manage the industrial pollution.

INSIDE-T: A Groundwater Contamination Transport Model for Sustainability Assessment in Remediation Practice

“…Our study, however, provides this room. INSIDE-T shows all the data and processes in a contaminant transport model in the most transparent way (spreadsheets, [68]) to let the manager(s) incorporate their judgements and considerations about the efficiency of remediation scenarios. After all, the transport model and adapted DSS can provide decision-makers with more reliable hydrogeological insights at the screening and preliminary management stage, and thereby enhance the overall sustainability scoring of potential remediation options.…”