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Optimal Design of Groundwater Monitoring Network Using the Combined Election-Kriging Method

机译:采用竞选 - 克里格化方法的地下水监测网络最优设计

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Groundwater monitoring requires a great deal of cost and time that optimizing the quantitative groundwater monitoring network with selecting the optimal number of sampling wells and determining their optimal location for reducing the cost and time of quantitative groundwater assessment are necessary. The data from 110 observation wells of Neyshabur plain in Iran range from the year 1986 to 2016 were studied. The combined Election-Kriging method was used to analyze these data, and the Pareto chart was plotted to determine the optimal number and location in two scenarios. The first scenario was to determine the optimal wells location among the existing wells and the second scenario was to determine the optimal wells location for monitoring groundwater levels throughout the plain. To limit the search space, the maximum and minimum number of monitoring network wells were selected 30 and 85 respectively. Based on the results, the selected method accurately provided the appropriate location of wells, so that in the first scenario, the RMSE values for the number of wells were in the range of 0.71 to 2.34 m. which are acceptable. In the second scenario, the RMSE values of between 1.04 and 2.89 m were obtained, which are appropriate values according to the objective of the problem. Also, the distribution of the wells selected in the area is also uniform in most numbers according to the second scenario, which indicates the good accuracy of the method.
机译:地下水监测需要大量的成本和时间,优化定量地下水监测网络,选择采样井的最佳数量并确定其最佳位置,以降低定量地下水评估的成本和时间。研究了来自1986年至2016年的伊朗Neyshabur平原的110个观察韦尔斯的数据。组合的election-Kriging方法用于分析这些数据,绘制帕圈图图表以确定两种情况的最佳数量和位置。第一场景是确定现有井中的最佳井位置,第二种情况是确定在整个平原上监测地下水位的最佳井位置。为了限制搜索空间,分别选择30和85的监控网络井的最大数量和最小数量。基于结果,所选方法准确地提供井的适当位置,从而在第一场景中,井数的RMSE值在0.71至2.34米的范围内。这是可接受的。在第二场景中,获得了1.04和2.89米之间的RMSE值,这是根据问题的目的的适当值。而且,根据第二场景,在该区域中选择的孔的分布也是均匀的,这表明该方法的良好精度。

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