Appraisal of surface-groundwater anthropogenic indicators and associated human health risk in El Sharqia Governorate, Egypt.

The aim of this study was to integrate hydrogeochemistry with a multivariate statistical approach to understand the various processes that control the evolution/contamination of water resources in El Sharqia Governorate, Egypt with a particular emphasis on direct/indirect risks to human health. To achieve this, a representative collection of 21 groundwater and 35 drainage samples was taken and examined for physical, chemical, and trace element measurements. Results indicated that in shallow groundwater and drainage water samples, the relative abundance of major cations is Na+ > Mg2+ > Ca2+ > K+, and for anions it is HCO3- > Cl- > SO42- (on a molar basis). Natural processes involving the dissolution/precipitation of some minerals and other processes including leaching of solid waste, overuse of agricultural fertilizers application, and high loads of discharged sewage water are responsible for the evolution of water resources in El Sharqia Governorate. Ammonia, nitrate, biological oxygen demand (BOD), phosphate, turbidity, iron, manganese, lead, and aluminum concentrations were found to be higher than the limits set by internatio2nal drinking water regulations. The health risk index (HRI) values for children were found to be higher than those for adults when the water resources are used for drinking purposes, which poses a risk to human health.

Groundwater quality assessment using water quality index and multivariate statistical analysis case study: East Matrouh, Northwestern coast, Egypt.

Rapid urbanisation has had a significant negative influence on the water bodies that flow through and around urban areas. This study aims to evaluate the water quality and analyse the suitability for drinking and irrigation uses. This study envisaged assessing the water quality status of the groundwater using the pollution index of groundwater (PIG), ecological risk index (ERI) and multivariate statistical techniques, namely cluster analysis (CA) and principal component analysis (PCA), that were applied to differentiate the sources of water quality variation and determine the cause of pollution in the study area. Most groundwater is unsuitable for drinking and irrigation consumption, depending on analyses. PIG values indicated high pollution levels in the studied water body, rendering it unsuitable for any practical purpose. CA results showed the impact of surface water and treatment plant on groundwater. PCA was used to identify four important factors in the groundwater, including mineral and nutrient pollution, heavy metal pollution, organic pollution and faecal contamination. The deteriorating water quality of the groundwater was demonstrated to originate from vast sources of anthropogenic activities, especially municipal sewage discharge. Study wells had greater concentrations of Cl- and Na+ in their water because seawater flows into the aquifer system and mixes with the marine aquifer matrix. Thus, the current work reveals how to employ the PIG and multivariate statistical approaches to obtain more accessible and more meaningful information about the water quality of groundwater and to identify the sources of pollution.