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Dr. Mohana Sundaram Shanmugam
Water Engineering and Management Program, Department of Civil and Infrastructure Engineering, School of Engineering and Technology, Asian Institute of Technology, Pathum Thani 12120, Thailand

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0 Crop modelling
0 irrigation water management
0 Unsaturated zone hydrology
0 Fate and transport modelling of contaminants
0 Climate change impacts and adaptation strategies

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Research article hydrology
Published: 20 April 2020 in Acta Geophysica
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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.

ACS Style

S. Mohanasundaram; Parmeshwar Udmale; Sangam Shrestha; Triambak Baghel; Smit Chetan Doshi; Balaji Narasimhan; G. Suresh Kumar. A new trend function-based regression kriging for spatial modeling of groundwater hydraulic heads under the sparse distribution of measurement sites. Acta Geophysica 2020, 68, 751 -772.

AMA Style

S. Mohanasundaram, Parmeshwar Udmale, Sangam Shrestha, Triambak Baghel, Smit Chetan Doshi, Balaji Narasimhan, G. Suresh Kumar. A new trend function-based regression kriging for spatial modeling of groundwater hydraulic heads under the sparse distribution of measurement sites. Acta Geophysica. 2020; 68 (3):751-772.

Chicago/Turabian Style

S. Mohanasundaram; Parmeshwar Udmale; Sangam Shrestha; Triambak Baghel; Smit Chetan Doshi; Balaji Narasimhan; G. Suresh Kumar. 2020. "A new trend function-based regression kriging for spatial modeling of groundwater hydraulic heads under the sparse distribution of measurement sites." Acta Geophysica 68, no. 3: 751-772.