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<p>Groundwater quality assessment is crucial for safe drinking water, especially in fluoride-affected regions. This study examines the spatial variability of groundwater fluoride concentration in the Bargarh Block of Bargarh District, western Odisha, during the pre-monsoon season. A total of 45 groundwater samples were collected and analyzed, revealing fluoride concentrations ranged from 0.20 to 3.35&#xa0;mg/L, with a mean of 1.51&#xa0;mg/L. Geostatistical interpolation using Ordinary Kriging was performed with spherical, exponential, and Gaussian semivariogram models. The best-fit model for accurate spatial prediction was identified. The Spherical model performed best, giving the lowest root mean square error (RMSE = 0.647). Using this model, about 175.42 km<sup>2</sup> of the study area was identified with fluoride levels exceeding the World Health Organization’s safe limit of 1.5&#xa0;mg/L. This study identified hotspot zones of fluoride contamination and offers valuable input for groundwater management and public health planning.</p>

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Comparative Semivariogram Modelling Approach for Predicting Pre-Monsoon Groundwater Fluoride Content in a Fluoride Prone Region of Western Odisha, India

  • 期刊论文

  • 发表日期：

    2025年10月18日

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  • Krishna Manjari Jena,
  • Prasanta Kumar Patra,
  • Duryadhan Behera,
  • Shreerup Goswami

摘要

Groundwater quality assessment is crucial for safe drinking water, especially in fluoride-affected regions. This study examines the spatial variability of groundwater fluoride concentration in the Bargarh Block of Bargarh District, western Odisha, during the pre-monsoon season. A total of 45 groundwater samples were collected and analyzed, revealing fluoride concentrations ranged from 0.20 to 3.35 mg/L, with a mean of 1.51 mg/L. Geostatistical interpolation using Ordinary Kriging was performed with spherical, exponential, and Gaussian semivariogram models. The best-fit model for accurate spatial prediction was identified. The Spherical model performed best, giving the lowest root mean square error (RMSE = 0.647). Using this model, about 175.42 km2 of the study area was identified with fluoride levels exceeding the World Health Organization’s safe limit of 1.5 mg/L. This study identified hotspot zones of fluoride contamination and offers valuable input for groundwater management and public health planning.