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Geostatistical based framework for spatial modeling of groundwater level during dry and wet seasons in an arid region: a case study at Hadat Ash-Sham experimental station, Saudi Arabia
Stochastic Environmental Research and Risk Assessment ( IF 3.9 ) Pub Date : 2021-01-22 , DOI: 10.1007/s00477-021-01971-9
Jaka S. Budiman , Nassir S. Al-Amri , Anis Chaabani , Amro M. M. Elfeki

Saudi Arabia (SA) lies in an arid region where groundwater is the main natural resource; therefore, it is essential to understand the groundwater dynamics for the best groundwater management practice in SA. In Hadat Ash-Sham Farm Experimental Station, SA, water table data from 11 wells and rainfall data were monitored for 16 months. The water table (WT) data is analyzed using the geostatistical method with the ordinary Kriging technique to generate the best WT spatial distribution map for each month and the expected flow direction. The cross-validation technique is used to evaluate the goodness of the developed WT maps. The Kriging maps show two regimes: weak spatial dependence (WSD, the ratio of the nugget to sill > 75%) and strong spatial dependence (SSD, the ratio of the nugget to sill < 25%). The WSD regime happens during dry seasons, while the SSD happens during wet seasons. The SSD gives better results and accuracy when compared to WSD. The root-mean-square error (RMSE) of WT varies between 0.26 and 3.4 m in the case of SSD, while it varies between 0.51 and 4.8 m in the case of WSD. WT maps show that the groundwater flow direction is from south-east to north-west during the wet season (SSD). This direction is in the orientation of surface stream with higher elevation (in the south) to the surface stream with lower elevation (in the north), where the study area is between these surface streams. While during the dry season (WSD), there is no preferred direction since there is almost no flow.



中文翻译:

基于地统计学的干旱地区干湿季地下水位空间建模框架:以沙特阿拉伯Hadat Ash-Sham实验站为例

沙特阿拉伯(SA)位于干旱地区,那里的地下水是主要自然资源。因此,必须了解地下水动力学,才能在SA中获得最佳的地下水管理实践。在SA的Hadat Ash-Sham农场实验站,对11口井的地下水位数据和降雨数据进行了16个月的监测。使用地统计学方法和普通的Kriging技术分析地下水位(WT)数据,以生成每个月和预期水流方向的最佳WT空间分布图。交叉验证技术用于评估已开发的WT映射的优良性。克里格图显示了两种状态:弱空间依赖性(WSD,金块与窗台的比率> 75%)和强空间依赖性(SSD,金块与窗台的比率<25%)。水务署的政权发生在旱季,而SSD则发生在雨季。与WSD相比,SSD可以提供更好的结果和准确性。在SSD情况下,WT的均方根误差(RMSE)在0.26至3.4 m之间变化,而在WSD情况下,其均方根误差在0.51至4.8 m之间变化。WT地图显示,在雨季(SSD),地下水的流动方向是从东南向西北。该方向是高海拔地表水流(南部)到低海拔地表水流(北部)的方向,研究区域位于这些地表水流之间。在干旱季节(WSD)期间,由于几乎没有流量,因此没有首选方向。使用SSD时为4 m,而使用WSD时为0.51至4.8 m。WT地图显示,在雨季(SSD),地下水的流动方向是从东南向西北。该方向是高海拔地表水流(南部)到低海拔地表水流(北部)的方向,研究区域位于这些地表水流之间。在干旱季节(WSD)期间,由于几乎没有流量,因此没有首选方向。使用SSD时为4 m,而使用WSD时为0.51至4.8 m。WT地图显示,在雨季(SSD),地下水的流动方向是从东南向西北。该方向是高海拔地表水流(南部)到低海拔地表水流(北部)的方向,研究区域位于这些地表水流之间。在干旱季节(WSD)期间,由于几乎没有流量,因此没有首选方向。研究区域在这些表面流之间。在干旱季节(WSD)期间,由于几乎没有流量,因此没有首选方向。研究区域在这些表面流之间。在干旱季节(WSD)期间,由于几乎没有流量,因此没有首选方向。

更新日期:2021-01-22
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