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Spatial analyses of groundwater levels using universal kriging

机译:使用通用克里金法对地下水位进行空间分析

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For water levels, generally a non-stationary variable, the technique of universal kriging is applied in preference to ordinary kriging as the interpolation method. Each set of data in every sector can fit different empirical semivariogram models since they have different spatial structures. These models can be classified as circular, spherical, tetraspherical, pentaspherical, exponential, gaussian, rational quadratic, hole effect, K-bessel, J-bessel and stable. This study aims to determine which of these empirical semivariogram models will be best matched with the experimental models obtained from groundwater-table values collected from Mustafakemalpasa left bank irrigation scheme in 2002. The model having the least error was selected by comparing the observed water-table values with the values predicted by empirical semivariogram models. It was determined that the rational quadratic empirical semivariogram model is the best fitted model for the studied irrigation area.
机译:对于水位(通常是非平稳变量),普遍克里金法比插值法优先于普通克里金法应用。每个扇区中的每个数据集都可以适合不同的经验半变异函数模型,因为它们具有不同的空间结构。这些模型可以分为圆形,球形,四球形,五球形,指数型,高斯型,有理二次型,空穴效应,K贝塞尔,J贝塞尔和稳定。本研究旨在确定哪种经验半变异函数模型与2002年从Mustafakemalpasa左岸灌溉计划收集的地下水位值获得的实验模型最匹配。通过比较观测到的地下水位,选择误差最小的模型由经验半变异函数模型预测的值。确定有理二次经验半变异函数模型是研究灌溉区的最佳拟合模型。

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