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A new trend function-based regression kriging for spatial modeling of groundwater hydraulic heads under the sparse distribution of measurement sites
Mohanasundaram S., Udmale Parmeshwar, Shrestha Sangam, Baghel Triambak, Chetan Doshi Smit, ,
Published in Springer Science and Business Media LLC
Volume: 68
Issue: 3
Pages: 751 - 772

Discrete groundwater level datasets are interpolated often using kriging group of models to produce a spatially continuous groundwater level map. There is always some level of uncertainty associated with different interpolation methods. Therefore, we developed a new trend function with the mean groundwater level as a drift variable in the regression kriging approach to predict the groundwater levels at the unvisited locations. Groundwater level data for 29 observation wells in Adyar River Basin were used to assess the performance of the developed regression kriging models. The cross-validation results shows that the proposed regression kriging method in the spatial domain outperforms other physical and kriging-based methods with R2 values of 0.96 and 0.98 during pre-monsoon and post-monsoon seasons, respectively.

About the journal
JournalData powered by TypesetActa Geophysica
PublisherData powered by TypesetSpringer Science and Business Media LLC
Open AccessNo