Spatial Distribution Analysis and Mapping of Groundwater Quality Parameters for the Sylhet City Corporation (SCC) Area Using GIS
Volume 3, Issue 1, January 2015, Pages: 1-10
Received: Feb. 3, 2015;
Accepted: Feb. 21, 2015;
Published: Mar. 2, 2015
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Gulam Md Munna, Dept. of Civil and Environmental Engineering, Shahjalal University of Science and Technology, Sylhet, Bangladesh
Numan-Al-Kibriya , Dept. of Civil and Environmental Engineering, Shahjalal University of Science and Technology, Sylhet, Bangladesh
Ahmad Hasan Nury, Dept. of Civil and Environmental Engineering, Shahjalal University of Science and Technology, Sylhet, Bangladesh
Shriful Islam, Dept. of Civil and Environmental Engineering, Shahjalal University of Science and Technology, Sylhet, Bangladesh
Hasina Rahman, Dept. of Civil and Environmental Engineering, Shahjalal University of Science and Technology, Sylhet, Bangladesh
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As Groundwater is a natural source of drinking water, it needs to be monitored regularly and people should be made aware of its quality. The unscientific management and exploration of groundwater resources has always been a serious problem in many cities in Bangladesh. As a result the quality of groundwater has become equally important as of its quantity. The present study is aimed to assess the current condition of groundwater quality and to analyze the spatial distribution of groundwater quality for the Sylhet City Corporation (SCC) area. The groundwater quality parameters were analyzed for 51 samples collected from the existing shallow tube wells from the twelve wards of SCC area. Arc GIS geostatistical analyst extension module was used for exploratory data analysis, semivariogram model selection, cross validation. Experimental semivariogram values are examined to find out the best fitted ordinary kriging (OK) models for eleven water quality parameters: pH, potassium, total hardness, alkalinity, turbidity, calcium, total dissolve solids, sulfate, nitrate, chloride and iron. The values of prediction errors i.e. mean square error (MSE), root mean square error (RMSE), average standard error (ASE), root mean square standardize error (RMSSE) were considered to justify the best fitted model. The interpolated spatial maps of different groundwater parameters shows that iron, alkalinity, total hardness and turbidity are vulnerable to groundwater quality within the study area.
Groundwater, Spatial Distribution, GIS, Geostatistics, Semivariogram
To cite this article
Gulam Md Munna,
Ahmad Hasan Nury,
Spatial Distribution Analysis and Mapping of Groundwater Quality Parameters for the Sylhet City Corporation (SCC) Area Using GIS, Hydrology.
Vol. 3, No. 1,
2015, pp. 1-10.
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