Assessing groundwater quality using GIS |
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Authors: | Insaf S Babiker Mohamed A A Mohamed Tetsuya Hiyama |
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Affiliation: | (1) Hydrospheric Atmospheric Research Center, Nagoya University, Furo-cho, Chikusa-ku Nagoya, 464-8601, Japan;(2) Graduate School of Environmental Studies, Nagoya University, Furo-cho, Chikusa-ku Nagoya, 464-8601, Japan |
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Abstract: | Assessing the quality of groundwater is important to ensure sustainable safe use of these resources. However, describing the
overall water quality condition is difficult due to the spatial variability of multiple contaminants and the wide range of
indicators (chemical, physical and biological) that could be measured. This contribution proposes a GIS-based groundwater
quality index (GQI) which synthesizes different available water quality data (e.g., Cl−, Na+, Ca2+) by indexing them numerically relative to the World Health Organization (WHO) standards. Also, introduces an objective procedure
to select the optimum parameters to compute the GQI, incorporates the aspect of temporal variation to address the degree of
water use sustainability and tests the sensitivity of the proposed model. The GQI indicated that the groundwater quality in
the Nasuno basin, Tochigi Prefecture, Japan, is generally high (GQI <90). It has also displayed the natural (depth to groundwater
table, geomorphologic structures) and/or anthropogenic (land-use and population density) controls over the spatial variability
of groundwater quality in the basin. Temporally, groundwater quality is more variable in the upper and lower parts of the
basin (variation, V, 15–30%) compared to the middle part (V, <15%) probably attributed to the seasonality of precipitation and irrigation of rice. In the lower southeastern part of
the Nasuno basin and the vicinity of the Naka and Houki rivers the sustainable use of groundwater is constrained by the relatively
low and variable groundwater quality. The model sensitivity analysis indicated that parameters which reflect relatively lower
water quality (high mean rank value) and those of significant spatial variability imply larger impacts on the GQI and must
be carefully and accurately mapped. Optimum index factor technique allows the selection of the best combination of parameters
dictating the variability of groundwater quality and enables an objective and fair representation of the overall groundwater
quality. |
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Keywords: | Groundwater quality Major ions WHO standards Temporal variation Spatial variation GIS Sensitivity analysis |
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