Document Type : Research Article
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Abstract
In geo-statistics, prediction of an unknown value of random field has been performed in specified time and position, using spatio-temporal Kriging. In some circumstances, a suitable covariate increase the estimation prediction. Geo-statistical methods of Universal Kriging (UK) and Kriging with External Trend (KwET) were applied to Mashhad plain water quality data sets. The optimal network to monitor groundwater quality was presented, using Entropy. All wells ranked based on the criterion of Entropy and mutual information. Then, the optimal network was determined based on the percentages of acquired information and relying on the spatio-temporal Kriging. Based on UK and KwET, electrical conductivity (EC) was the best covariate. KwET with EC as a covariate was the superior Kriging method. A network covering 111 wells showed to be as informative as the existing monitoring network with a total of 237 wells.
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