Chloride-salinity as indicator of the chemical composition of groundwater: empirical predictive model based on aquifers in Southern Quebec, Canada.

The present study first describes the variations in concentrations of 12 chemical elements in groundwater relative to salinity levels in Southern Quebec (Canada) groundwater systems, and then uses this data to develop an empirical predictive model for evaluating groundwater chemical composition relative to salinity levels. Data is drawn from a large groundwater chemistry database containing 2608 samples. Eight salinity classes were established from lowest to highest chloride (Cl) concentrations. Graphical analyses were applied to describe variations in major, minor, and trace element concentrations relative to salinity levels. Results show that the major elements were found to be dominant in the lower salinity classes, whereas Cl becomes dominant at the highest salinity classes. For each of the major elements, a transitional state was identified between domination of the major elements and domination of Cl. This transition occurred at a different level of salinity for each of the major elements. Except for Si, the minor elements Ba, B, and Sr generally increase relative to the increase of Cl. The highest Mn concentrations were found to be associated with only the highest levels of Cl, whereas F was observed to be more abundant than Mn. Based on this analysis of the data, a correlation table was established between salinity level and concentrations of the chemical constituents. We thus propose a predictive empirical model, identifying a profile of the chemical composition of groundwater relative to salinity levels, to help homeowners and groundwater managers evaluate groundwater quality before resorting to laborious and costly laboratory analyses.

Finite element modelling to assess the submarine groundwater discharge in an over exploited multilayered coastal aquifer.

A three-dimensional variable-density finite element model was developed to quantify the impact of groundwater over use on submarine groundwater discharge (SGD). The model was applied to the Arani-Korttalaiyar river basin, north of Chennai, India. This region has an upper unconfined and lower semi-confined aquifer extending up to 30 km inland from the coast and beyond this distance; the two aquifers merge and become a single unconfined aquifer. The model simulated that during the period from 2000 to 2012, the flux of seawater to the aquifer has increased from 17,000 to 24,500 m3/day due to over-exploitation of groundwater from the semi-confined aquifer. Where as in the unconfined aquifer, SGD has been taking place. Scenarios showing the impact of newly constructed  managed aquifer recharge structures, 10% additional increase in rainfall recharge, and termination of pumping from five well-fields on the groundwater conditions in the area were studied. The model predicted a SGD of 85,243 m3/day from the unconfined aquifer and 22,414 m3/day from the semi-confined aquifer by the end of 2030. By adopting managed aquifer recharge methods, seawater intrusion (rate of 4,408 m3/day) can be reduced and SGD (rate of 22,414 m3/day) increased. The rate of SGD increase and the movement of seawater to aquifer can be completely prevented in the semi-confined aquifer by adopting these management options by 2030. Findings from this study have enhanced the understanding of SGD and water budget, which can be used by decision-makers for the sustainable management of groundwater resources in coastal aquifers.

Chemical, microbial and antibiotic susceptibility analyses of groundwater after a major flood event in Chennai.

During floods, human exposure to pathogens through contaminated water leads to the outbreak of epidemic diseases. This research presents the first extensive assessment of surface and groundwater samples collected immediately after a flood (December 2015) and post-flood (April 2016) from the Adyar River of Chennai, a major city in India, for major ions, trace metals, bacterial population, and pathogens. Severe rains in a short period of time resulted in flooding which inundated the wells, allowing the entry of sewage contaminated river water into the groundwater zone. This has led to bacterial counts and chemical ions exceeding Bureau of Indian Standard's recommended limits in most flood affected areas. Pathogens isolated from the groundwater showed resistance to antibiotics, namely ceftriaxone, doxycycline and nalidixic acid. However, they were sensitive to chloramphenicol, ciprofloxacin, norfloxacin, and tetracycline. Determining the antibiotic susceptibility of pathogens will help in the treatment of humans affected by contaminated water through an appropriate selection of prescribed medication.