The depth of water table was interpolated by using geo statistical method of ordinary
Kriging. The results shows that in 1990 the depth of water table more than 10 meter increase from 0.2% to 17.5 % of total study area during pre-monsoon and in 2013 the depth of water table more than 10 meter increase from 0.74 % to 23% of total study area during post monsoon.
However it is a fact that IDW and
Kriging methods of interpolation have also been used in international research for the mapping of drought indices.
In order to interpolate TDS parameter, used IDW, RBF and Ordinary
Kriging methods.
Kriging and the Bayesian maximum entropy (BME) framework are interpolation methods that assign a series of weights to observed monitoring station data to compute interpolated values of pollutants at unmonitored sites (Bell 2006; Bogaert et al.
Varouchakis and Hristopulos (2013) have compared class of deterministic interpolation methods (Inverse Distance Weighted and Minimum Curvature) with Stochastic methods (ordinary
Kriging and universal
Kriging).
Kriging metamodels [14] were originally proposed by the South African mining engineer named Danie Gerhardus Krige.
The second stage has focus on the geostatistical estimation of data of porosity by means of
kriging method.
Commonly used global approximation surrogate models such as
Kriging [7], Radial Basis Functions [8] (RBFs) and polynomial response surface model [9] (RSM), attempt to approximate the primary objective function landscape, which in turn are inexpensive to evaluate within an optimisation cycle.
Based on the Master's thesis of Daniel Gerhardus Krige, the theory using
kriging for interpolation and extrapolation was developed by the French mathematician Georges Matheron (1963).