Evaluation of Water Quality using Bhargava Water Quality Index Method and GIS, Case Study: Euphrates River in Al-Najaf CityJournal: International Journal of Science and Research (IJSR) (Vol.6, No. 7)
Publication Date: 2017-07-05
Authors : Mustafa Muwafaq Noori; Khalid Adel Abdulrazzaq; Athraa Hashim Mohammed;
Page : 1286-1295
Keywords : Euphrates River; WTP; water quality index; GIS; IDW;
In this study, water quality index (WQI) was calculated to classify the flowing water in the Euphrates River at Al-Najaf City and try to correlate the results with the satellite image for making colored analytical models to the river that can be used to predict the classification of river water quality for drinking purpose. Bhargava WQI method was adopted to evaluate and judge the suitability of Euphrates River in Al-Najaf City, this was done by testing the water quality of the samples collected from intakes of two stations (Al-Kufa Water Project and Manathira Water Project) in Al-Najaf city. The analysis includes different polluted parameters Total Hardness (T. H), Sulfate (SO4-2), Chloride (Cl-1), Total Dissolve Solids (TDS), Calcium (Ca+2), pH value, and Biochemical Oxygen Demand (BOD) as a monthly average base during the year 2015. The results from WQI analysis classified the Euphrates River acceptable to polluted at Al-Kufa station while it was acceptable to severely polluted at Manathira station. WQI reached a maximum value of 43.65 in July at Manathira station through the study period, while the average annual overall WQI was 33.34 at Al-Kufa station and 29.67 at Manathira station. The high value of average annual overall WQI obtained is a result of the high concentrations of Sulfate, Total Dissolve Solids, Calcium and Total Hardness which can be attributed to the various human and industrial activities taking place at the river banks. The results are analyzed by using the Geographic Information System (GIS) which requires building a network database linked to GIS for making benefit from its analysis power and geographical distribution of data across the study area.
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