Assessment of spatial and temporal changes in groundwater quality in a rural municipality using the CCME WQI water quality indicator - Balla, Dániel; Kiss, Emőke; Zichar, Marianna; Mester, Tamás (JOURNAL OF LANDSCAPE ECOLOGY, 2024)
Urban groundwater pollution is a global phenomenon requiring several environmental measures to reduce. In our study, we investigated the changes in water quality following the construction of a sewerage network in a municipal setting between 2013 and 2022 in a long-term monitoring framework by regularly sampling 40 municipal groundwater wells. The changes in groundwater levels before (2013) and after (2017, 2022) the construction of a sewerage network were assessed based on the groundwater levels measured during the sampling. In 2013, the groundwater level was very close to the surface (<3 m). The groundwater level was highest in the inner parts of the municipality, while the most profound water level was measured in the southern parts. The groundwater table measured in 2017 and 2022 showed a sharp decline due to the cessation of sewage discharge. The monitoring data were categorized into water quality categories using the CCME WQI water quality index, which revealed high levels of contamination in the year before the sewerage system was installed (2013), with most wells falling into the contaminated and highly contaminated categories. In the monitoring period following the sewerage, we found a significant positive change in most water chemistry parameters tested (pH, EC, NH4+, NO2-, NO3-, PO43-, COD, Na+).). Based on thematic point maps, a growing area shows good to fair water quality. This was confirmed by discriminant analysis, as it was possible to determine with 87.4% accuracy whether a given sample was from the pre or post-serage period based on the water chemistry parameters. However, eight years after sewerage, inorganic nitrogen forms and organic matter concentrations remain high, indicating that contaminants accumulated in the area are still present. Further long-term monitoring is needed to understand the dynamics of the clean-up processes.