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Assessment and modeling of groundwater quality using WQI and GIS in Upper Egypt area

Research Authors
Ragab ElSayed Rabeiy
Research Year
2017
Research Journal
Environmental Science and Pollution Research
Research Publisher
NULL
Research Vol
NULL
Research Rank
1
Research_Pages
NULL
Research Website
http://link.springer.com/article/10.1007/s11356-017-8617-1?wt_mc=Internal.Event.1.SEM.ArticleAuthorOnlineFirst
Research Abstract

The continuous growth and development of population need more fresh water for drinking, irrigation, and domestic in arid countries like Egypt. Evaluation the quality of groundwater is an essential study to ensure its suitability for different purposes. In this study, 812 groundwater samples were taken within the middle area of Upper Egypt (Sohag Governorate) to assess the quality of groundwater for drinking and irrigation purposes. Eleven water parameters were analyzed at each groundwater sample (Na+, K+, Ca2+, Mg2+, HCO3− SO42−, Fe2+, Mn2+, Cl−, electrical conductivity, and pH) to exploit them in water quality evaluation. A classical statistics were applied for the raw data to examine the distribution of physicochemical parameters in the investigated area. The relationship between groundwater parameters was tested using the correlation coefficient where a strong relationship was found between several water parameters such as Ca2+ and Cl−. Water quality index (WQI) is a mathematical model used to transform many water parameters into a single indicator value which represents the water quality level. Results of WQI showed that 20% of groundwater samples are excellent, 75% are good for drinking, and 7% are very poor water while only 1% of samples are unsuitable for drinking. To test the suitability of groundwater for irrigation, three indices are used; they are sodium adsorption ration (SAR), sodium percentage (Na%), and permeability index (PI). For irrigation suitability, the study proved that most sampling sites are suitable while less than 3% are unsuitable for irrigation. The spatial distribution of the estimated values of WQI, SAR, Na%, PI, and each groundwater parameter was spatially modeled using GIS.