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GROUNDWATER QUALITY ANALYSIS OF MANIKGANJ DISTRICT USING WATER QUALITY INDEX AND PRINCIPAL COMPONENT ANALYSIS

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Water Quality Index (WQI) is one of the simplest, most understandable and effective way to determine overall quality of drinking water as well as water used for other purposes. A study was attempted to assess the spatial variability of groundwater quality index of Manikganj district of Bangladesh. For this purpose, 31 water samples were collected and analyzed for potential sources and of contamination. pH, Total Dissolved Solids (TDS), Electric Conductivity (EC), Total Hardness (TH), Total Alkalinity (TA), Iron (Fe), Manganese (Mn), Sulphate (SO₄²- ), Chloride (Cl− ) and Turbidity were measured for calculating WQI. Their mean values were 7.05, 313.07 mg/L, 625.62 µS/cm, 207.35 mg/L, 214.57 mg/L, 5.0 mg/L, 0.093 mg/L, 14.16 mg/L, 104.38 mg/L and 62.06 respectively. The obtained values of WQI were distributed spatially through mapping using IDW interpolation via ESRI ArcGIS software. These values were categorized as excellent, good, poor, very poor, and unfit for every purposes. The WQI values ranged from 7 to 683 with an average value of 134.19. Among the 31 samples, 29.03% were excellent quality, 38.71% were good quality, 9.67% poor quality, 12.9% very poor and 9.67% were unfit for all purposes. The Kaiser–Meyer–Olkin test was 0.747 confirming that the dataset was sufficient for component analysis. The entire dataset could be represented by two components which accounted for 63.53% of the total variance of the dataset. Through PCA the influential contaminants came to light informing that naturally occurring Fe and Mn contaminations resulted in most of the pollution. Through this study, it can be proved that Spatial mapping and PCA are effective tools for determining ground water quality. The results of this study can be used to improve the current water quality situation of Manikganj district and ensure higher quality water resources for the citizens of this district.

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GROUNDWATER QUALITY ANALYSIS OF MANIKGANJ DISTRICT USING WATER QUALITY INDEX AND PRINCIPAL COMPONENT ANALYSIS

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