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Abstract

Summary

The Water Elevation Surface (WES) of May 2021, measured by 160 piezometers in the California state, is mapped by two geostatistical methods: ordinary and universal kriging. The dataset being non-stationary, the variographical analysis on the raw data shows zonal anisotropy, i.e. a more important variability along Y than along X. In addition, the fitted variogram model is valid for distances inferior to 40 km. Over this distance, the mathematical model is based on extrapolation. To exclude the extrapolation window of variogram from the interpolation process of ordinary kriging, a neighbourhood limit could be considered to restrict the selected measurements to a radius of 20 to 25 km around the interpolation target. The method of ordinary kriging is applied with the neighbourhood limit of 25 km, then without neighbourhood limit. The latter is not recommended for the non-stationary datasets; meanwhile the artefacts are reduced, and for the target points far from the measurement values, the WES is extrapolated. On the map of universal kriging, the extrapolated values follow the spatial drift. Finally, according to the cross-validation method of leave-one-out, the universal kriging has the least error, and the ordinary kriging without limit of neighbourhood has the highest error.

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/content/papers/10.3997/2214-4609.2024101306
2024-06-10
2025-07-08

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References

  1. California-Department-of-Water-Resources, “Periodic Groundwater Level Measurements (online platform, accessed on 11/28/2023), https://data.cnra.ca.gov/dataset/periodic-groundwater-level-measurements.” 2023.
     [Google Scholar]
  2. M.Karanovic, M.Tonkin, and D.Wilson, “KT3D-H2O: A program for kriging water level data using hydrologic drift terms,” Ground Water, vol. 47, no. 4, pp. 580–586, 2009.
     [Google Scholar]
  3. M. J.Tonkin and S. P.Larson, “Kriging Water Levels with a Regional‐Linear and Point‐Logarithmic Drift,” Groundwater, vol. 40, no. 2, pp. 185–193, Mar. 2002.
     [Google Scholar]
  4. S.S. Papadopulos & Associates. Inc., KT3D_H2O Version 3.0 - A Program for Kriging Water Level Data using Hydrologic Drift Terms. S. S. Papadopulos & Associates, Inc.
     [Google Scholar]
  5. P.Masoudi, “Fuzzy membership function for weighting pairs in variographical analysis,” Spat. Stat., vol. 52, p. 100717, Dec. 2022.
     [Google Scholar]
  6. A. G.Journel and C. J.Huijbregts, Mining geostatistics. Blackburn Press, 2003.
     [Google Scholar]
  7. H.Wackernagel, Multivariate Geostatistics. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003.
     [Google Scholar]
  8. Geovariances, “Isatis.neo (TM).” 2023.
     [Google Scholar]
  9. J.Vann, S.Jackson, and O.Bertoli, “Quantitative kriging neighbourhood analysis for the mining geologist-a description of the method with worked case examples,” … Min. Geol. …, no. November, pp. 17–19, 2003.
     [Google Scholar]
/content/papers/10.3997/2214-4609.2024101306
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Mapping Groundwater Level by Geostatistical Methods: Ordinary Versus Universal Kriging; Alongside a Discussion on Neighbourhood
Conference Proceedings 2024, 1 (2024); https://doi.org/10.3997/2214-4609.2024101306
/content/papers/10.3997/2214-4609.2024101306
/content/papers/10.3997/2214-4609.2024101306
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