Integrated geostatistics and GIS techniques for assessing groundwater contamination

The sustainable development in El Arish area (North Sinai, Egypt) is retarded by serious environmental problems, where the land use and land cover of the region is changing over time. The fast growth of the human activities in the study area is accompanied by the destruction and over-exploitation of the nature. The present study applies the multivariate statistics (factor and cluster analyses) and GIS techniques for the identification of anthropogenic and natural processes affecting groundwater quality of the Quaternary aquifer. The aim of this study was to investigate the impacts on groundwater resources, the potential pollution sources and to identify the main anthropogenic inputs affecting heavy metal contents. Since the depth to the water table is shallow and the aquifer has poor buffering capacity, the pollution risk is very high. Groundwater chemistry in this coastal region has complex contaminant sources, where, intensive farming activities and untreated wastes put stress on groundwater quality. Nemours areal distribution maps were constructed for correlating water quality with possible contributing factors such as location, land use and aquifer depth. These maps identified both anthropogenic and natural processes affecting groundwater quality of the studied aquifer. Cluster analysis was used to classify water chemistry and determine the hydrochemical groups, Q-mode dendrogram is interpreted and there are three main clusters. Factor analyses identify the contamination sources affecting groundwater hydrochemistry such as: nitrate, sulphate, phosphate and potassium fertilizers, pesticides, sewage ponds wastes, salinization due to circulation of dissolved salts in the irrigation water itself