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<p>This study evaluates the groundwater quality of the Moghan Plain using the Water Quality Index (WQI) in conjunction with advanced geostatistical interpolation techniques. Kriging-based estimators were employed due to their capability to determine optimal interpolation weights that minimize the variance of the deterministic estimator, thereby enabling a rigorous assessment of both prediction accuracy and the spatial distribution of estimation uncertainty. The spatial structure of the WQI and the auxiliary variable (electrical conductivity) was modeled using the Stable variogram, which exhibited a zero nugget effect for both variables. The sill values(0.88) for WQI and 1.07 for electrical conductivity. Indicate the dominance of the structured spatial component, thereby demonstrating strong spatial continuity across the study area. Among the evaluated techniques, simple Co-kriging produced the highest predictive performance, with a coefficient of determination of 0.96 and a root mean square error of 0.2. Spatial estimation results reveal that most groundwater in the Moghan Plain falls within the WQI range of 100–200, corresponding to poor drinking-water quality. In total, 94% of the region’s groundwater is classified as unsuitable for drinking purposes. These findings emphasize the critical role of geostatistical estimation, especially kriging, as a highly accurate and robust tool for assessing groundwater quality at a regional scale, and also emphasize the use of this method in the assessment and sustainable management of water resources in groundwater-dependent areas.</p>

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Assessment of Groundwater Quality Using Geostatistical Methods and WQI in the Moghan Plain, Iran

  • 期刊论文

  • 发表日期：

    2026年2月9日

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  • Yaser Hoseini

摘要

This study evaluates the groundwater quality of the Moghan Plain using the Water Quality Index (WQI) in conjunction with advanced geostatistical interpolation techniques. Kriging-based estimators were employed due to their capability to determine optimal interpolation weights that minimize the variance of the deterministic estimator, thereby enabling a rigorous assessment of both prediction accuracy and the spatial distribution of estimation uncertainty. The spatial structure of the WQI and the auxiliary variable (electrical conductivity) was modeled using the Stable variogram, which exhibited a zero nugget effect for both variables. The sill values(0.88) for WQI and 1.07 for electrical conductivity. Indicate the dominance of the structured spatial component, thereby demonstrating strong spatial continuity across the study area. Among the evaluated techniques, simple Co-kriging produced the highest predictive performance, with a coefficient of determination of 0.96 and a root mean square error of 0.2. Spatial estimation results reveal that most groundwater in the Moghan Plain falls within the WQI range of 100–200, corresponding to poor drinking-water quality. In total, 94% of the region’s groundwater is classified as unsuitable for drinking purposes. These findings emphasize the critical role of geostatistical estimation, especially kriging, as a highly accurate and robust tool for assessing groundwater quality at a regional scale, and also emphasize the use of this method in the assessment and sustainable management of water resources in groundwater-dependent areas.