A Comparison of Some Interpolation Techniques for Determining Spatial Distribution of Nitrogen Compounds in Groundwater

By U. Bronowicka-Mielniczuk, J. Mielniczuk, R. Obroślak, W. Przystupa. International Journal of Environmental Research, 2019

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The aim of the study was to analyse spatial variability of selected parameters of subsurface waters in the area of approximately 10 ha, located in the valley of the Ciemięga River in the village of Snopków, near Lublin, Poland. For the purpose of this study, nine sections were delimited, each with four points of collecting groundwater. In the groundwater samples, there were measured $${\text{NH}}_{4}^{ + }$$NH4+, $${\text{NO}}_{3}^{-} ,$$NO3-, and $${\text{NO}}_{2}^{-}$$NO2-. Due to the small number of samples, the analysis was limited to deterministic interpolation methods. The following methods were compared using leave-one-out cross-validation procedure: triangulation, inverse distance weighting, radial base function, and modified Shepard’s method. The methods which proved to be optimal were used to create spatial variability maps of the analysed parameters. Spatial interpolation and visualization of the results were performed in Surfer ver.16, and other calculations were conducted using R software.Article HighlightsThe selection of an appropriate interpolation technique is the crucial factor in producing a reliable map of spatial variability in environmental research.Both the spatial distribution and the number of the sample data being interpolated have to be included in the decision making process.Radial basis function and modified Shepard’s methods were superior to other methods in preserving the original sample point values.Spatial interpolation by inverse distance weighting method performed among the poorest interpolators.There are strong arguments for using simple interpolation techniques in the case of data sets spread over a wide range.

Subfields: Environmental Engineering, Law, Water Science and Technology

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