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Predicting saltwater intrusion into aquifers in vicinity of deserts using spatio-temporal kriging

机译:使用时空克里金法预测沙漠地区咸水入侵到含水层中的情况

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The primary objective of this study was to provide a detailed framework to use the spatio-temporal kriging to model the spatio-temporal variations of salinity data and predict saltwater intrusion into freshwater aquifers in the vicinity of deserts. EC data, measured in extraction wells in the Mahvelat plain located in the Northeastern part of Iran, available from 2007 to 2013, were used to demonstrate the developed framework. The source of data was not a well-designed measurement network. Therefore, to homogenize the data, spatial analysis was used to find EC distribution in the area in each year of study. To conduct the spatial analysis, a guideline and a systematic process were developed to select an appropriate kriging method and optimize its parameters. This process can be applied to different variables. After spatial analysis of EC data for all the years of the analysis period using empirical Bayesian kriging (EBK) method with manually optimized parameters, spatio-temporal and corresponding variogram analysis was conducted using R software. This process was based on a separable product-sum model applied to the data from 2007 to 2012. The data of 2013 and the data available for the years 1999 and 2006 were used for evaluating the performance of the spatio-temporal model. The EC distribution maps, developed for different years until 2021, show a high level of EC in the north, south, and west of the study area and growing saltwater intrusion into the central freshwater aquifer. This result can be attributed to the over-exploitation of the aquifer and hydraulic head and gradient distribution in the area. The framework provided in this study for spatio-temporal analysis of unstructured EC data is useful for groundwater managers in making proper decisions.
机译:这项研究的主要目的是提供一个详细的框架,以使用时空克里金法对盐度数据的时空变化进行建模,并预测咸水入侵沙漠附近淡水含水层的情况。 EC数据是在2007年至2013年间从伊朗东北部Mahvelat平原的抽油井中测得的,这些数据可用于证明已开发的框架。数据源不是设计良好的测量网络。因此,为了使数据均匀化,在每个研究年度中都使用了空间分析来查找该区域的EC分布。为了进行空间分析,制定了指南和系统过程以选择合适的克里金法并优化其参数。该过程可以应用于不同的变量。在使用手动优化参数的经验贝叶斯克里格(EBK)方法对分析期间所有年份的EC数据进行空间分析之后,使用R软件进行了时空分析和相应的变异函数分析。此过程基于适用于2007年至2012年数据的可分离乘积和模型。2013年的数据以及1999年和2006年的可用数据用于评估时空模型的性能。 EC分布图(在2021年之前的不同年份开发)显示了研究区域的北部,南部和西部的EC较高,并且盐水侵入中央淡水含水层的比例不断增加。该结果可归因于含水层和水力压头的过度开采以及该地区的梯度分布。本研究中提供的用于非结构化EC数据的时空分析的框架对于地下水管理者做出适当的决策很有用。

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