Influence of Different Sample Well Densities and Interpolation Methods on the Spatial Distribution of Groundwater Quality
Different sample well densities and interpolation methods significantly affect the spatial variability assessment of groundwater quality.The methods of inverse distance weighted(IDW),ordinary Kriging and radial basis function(RBF)were applied to predict the spatial concentration of 3 chemicals(chloride,sulphate,sodium)in the groundwater of Heze City in order to select an appropriate interpolation method producing a reliable map.The mean errors,mean relative errors and root mean square errors were compared to assess the best-fit interpolation method.The results show that in the study area with evenly distributed groundwater sample wells,the ordinary Kriging method gives optimum prediction results for all 3 involved chemicals.The areas of 5 groundwater quality grades were estimated for different sample well densities namely:5 wells,4 wells and 3 wells/103 km2.The estimated grade areas with Kriging method have less differences when the prediction results are interpolated with the density of 4 wells per 103km2 or above.The estimated areas of Ⅰ～Ⅲ grade for chloride,sulphate,sodium in the groundwater of Heze City in 2019 are 6 868.0km2,8 125.75km2 and 4 770km2 while the areas of over the third grade limitations are 5 299.5km2,4 041.75km2 and 7 397.50km2 respectively.A thorough understanding of the groundwater quality status in the case study area is a significant tool for water resources management and decision-makers.
groundwater quality assessmentspatial interpolationsample well densityKrigingRBFIDWinterpolation accuracy
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