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- W4285161811 abstract "The qualities of different groundwater parameters rely on the sources of groundwater recharge, industrial effluent, urban interactions, agriculture, aquifer pumping, and waste disposal. Domination of any of these factors alters the groundwater quality. GIS enables the tracking of changes throughout time within an area/ watershed and correlating changes in water quality with these alterations. Choosing an appropriate GIS-spatial interpolation technique is a critical success element in surface analysis since different interpolation methods might result in different surfaces and, eventually, different outcomes. Though no particular interpolation technique is completely optimum, the best interpolation method for a given circumstance can only be determined by comparing their results. An automated tool has been developed to assess popular interpolation techniques like inverse distance weightage, radial basis function, ordinary kriging, universal kriging, empirical Bayesian kriging, and kernel interpolation in terms of root mean square error and mean absolute error. The model provides researchers and official groundwater quality monitoring and assessment teams with the help to pick the optimal algorithm." @default.
- W4285161811 created "2022-07-14" @default.
- W4285161811 creator A5007373998 @default.
- W4285161811 creator A5062194857 @default.
- W4285161811 date "2022-01-01" @default.
- W4285161811 modified "2023-10-13" @default.
- W4285161811 title "An Automated Geoprocessing Model for Accuracy Assessment in Various Interpolation Methods for Groundwater Quality" @default.
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- W4285161811 doi "https://doi.org/10.1007/978-981-19-2083-7_16" @default.
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