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Spatial Variability Zonation of Groundwater-table by UseGeo-statistical Methods in Central Region of Hamadan province

机译:利用地统计学的哈马丹省中部地区地下水位空间变异性分区

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Today’s population explosion, industrial improve and agricultural development has increased the extraction of groundwater resources, As groundwater resources are the most important factors for development of arid and semiarid areas. In this study the geo-statistics methods are used to examine the spatial and timing variability of groundwater table of Central region of Hamadan Province in Iran, So the ground water statistical data in this region were accumulated and a data bank was prepared, Then the quality and the accuracy of data were controlled, Next the different interpolation techniques including Kriging, Inverse Distance Weight (IDW) to the power of 1 to 5, and Radial Basis Function method (Thin Plate Radial Function, Inverse Multi Quadratic and Multi Quadratic) and Cokriging method were used; After choosing the best interpolation methods using GSD and RMSE the spatial zonation map of groundwater table were drawn by Arc GIS. The analysis of geostatistical results appeared that the Spherical model was the best variogram specified to groundwater data in 1989, Circular model was the best in 1993 and 1999, and pent-spherical model was the best in 2006. Our findings got from investigation of interpolation methods by Cross validation showed that in all years of investigation, Cokriging method has had the less amount error in estimation and is the most suitable method. According these results the variable table of groundwater during the years of our research showed that the water table in this region has decreased noticeably and the use of these sources should be limited
机译:当今的人口爆炸,工业发展和农业发展增加了对地下水资源的开采,因为地下水资源是干旱和半干旱地区发展的最重要因素。本研究采用地统计学方法研究了伊朗哈马丹省中部地区地下水位的空间和时间变化,因此积累了该地区的地下水统计数据并准备了一个数据库,然后对其质量进行了分析。然后控制不同的插值技术,包括克里格(Kriging),反距离权重(IDW)至1到5的幂,径向基函数方法(薄板径向函数,多二次方和多二次方逆矩阵)和协同克里格使用方法在使用GSD和RMSE选择最佳插值方法后,用Arc GIS绘制了地下水位的空间分区图。地统计结果分析表明,球形模型是1989年地下水数据的最佳变异函数,圆形模型是1993年和1999年的最佳变量,五球形模型是2006年的最佳变量。我们的发现来自插值方法的研究交叉验证的结果表明,在所有的调查年份中,Cokriging方法的估计量误差较小,是最合适的方法。根据这些结果,我们研究期间的地下水变量表表明该地区的地下水位明显减少,应限制使用这些水源。

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