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  • 标题:Spatial Distribution of TDS in Drinking Water of Tehsil Jampur using Ordinary and Bayesian Kriging
  • 本地全文:下载
  • 作者:Maqsood Ahmad ; Sohail Chand
  • 期刊名称:Pakistan Journal of Statistics and Operation Research
  • 印刷版ISSN:2220-5810
  • 出版年度:2015
  • 卷号:11
  • 期号:3
  • 页码:377-386
  • DOI:10.18187/pjsor.v11i3.894
  • 语种:English
  • 出版社:College of Statistical and Actuarial Sciences
  • 摘要:In this research article, level of TDS in groundwater with spatial domain Tehsil Jampur, Pakistan is considered as response variable. Its enhanced level in drinking water produces both the human health concerns and aquatic ecological impacts. Its high value causes several diseases like bilestone, joints stiffness, obstruction of blood vessel and kidney stones. Some Geostatistical techniques were used to interpolate TDS at unmonitored locations of Tehsil Jampur. Four estimation techniques were comparatively studied for fitting well known matern spatial covariance models. Model based Ordinary Kriging (OK) and Bayesian Kriging (BK) were used for spatial interpolation at unmonitored locations. Cross validation statistic was used to select best interpolation technique with reduced RMSPE. Prediction maps were generated for visual presentation of interpolated sited for both techniques. This study revealed that among thirty observed locations, 56% water samples exceed the maximum permissible limit (1000g/ml) of TDS as described by WHO
  • 其他摘要:In this research article, level of TDS in groundwater with spatial domain Tehsil Jampur, Pakistan is considered as response variable. Its enhanced level in drinking water produces both the human health concerns and aquatic ecological impacts. Its high value causes several diseases like bilestone, joints stiffness, obstruction of blood vessel and kidney stones. Some Geostatistical techniques were used to interpolate TDS at unmonitored locations of Tehsil Jampur. Four estimation techniques were comparatively studied for fitting well known matern spatial covariance models. Model based Ordinary Kriging (OK) and Bayesian Kriging (BK) were used for spatial interpolation at unmonitored locations. Cross validation statistic was used to select best interpolation technique with reduced RMSPE. Prediction maps were generated for visual presentation of interpolated sited for both techniques. This study revealed that among thirty observed locations, 56% water samples exceed the maximum permissible limit (1000g/ml) of TDS as described by WHO
  • 关键词:Spatial Interpolation;Box-Cox transformation;Bayesian Kriging;TDS
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