A new trend function-based regression kriging for spatial modeling of groundwater hydraulic heads under the sparse distribution of measurement sites

Acta Geophysica

article

Mohanasundaram, S.¹  Udmale, Parmeshwar¹  Shrestha, Sangam¹  Baghel, Triambak¹  Doshi, Smit Chetan¹  Narasimhan, Balaji²  Suresh Kumar, G.³ 

[1] Water Engineering and Management, Department of Civil and Infrastructure Engineering, School of Engineering and Technology, Asian Institute of Technology;Department of Civil Engineering, Indian Institute of Technology Madras;Department of Ocean Engineering, Indian Institute of Technology Madras

关键词: Regression kriging;    Digital elevation model;    Mean groundwater level;    Geostatistics;    Trend function;    Prediction error variance;   

DOI  :  10.1007/s11600-020-00427-y

学科分类：地球科学(综合)

来源: Polska Akademia Nauk * Instytut Geofizyki

【 摘 要 】

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.

【 授权许可】

Unknown