Spatial Distribution of TDS in Drinking Water of Tehsil Jampur using Ordinary and Bayesian Kriging

Maqsood Ahmad, Sohail Chand

Abstract


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

Keywords


Spatial Interpolation; Box-Cox transformation; Bayesian Kriging; TDS

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DOI: http://dx.doi.org/10.18187/pjsor.v11i3.894

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Title

Spatial Distribution of TDS in Drinking Water of Tehsil Jampur using Ordinary and Bayesian Kriging

Keywords

Spatial Interpolation; Box-Cox transformation; Bayesian Kriging; TDS

Description

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

Date

2015-09-08

Identifier


Source

Pakistan Journal of Statistics and Operation Research; Vol. 11 No. 3, 2015



Print ISSN: 1816-2711 | Electronic ISSN: 2220-5810