User's guide of Proceessing Modflow 5.0

200 Processing Modflow
- Akima's bivariate interpolation: This method creates a triangulation of the
measurement data points and performs interpolation by using a bivariate fifth order
polynomial of Hermite type for the interpolation within a triangle. It uses a user-specified
number of data points closest to a model cell for estimating the value at the cell.
- Renka's triangulation: This method creates a triangulation of the measurement data
points and uses a global derivative-estimation procedure to compute estimated partial
derivatives at each point. The program determines a piecewise cubic function F(x,y). F
has continuous first derivates over the created mesh and extends beyond the mesh
boundary allowing extrapolation.
5.2 The Field Interpolator
Fig. 5.2 Effects of different weighting exponents
- Kriging: The Kriging method has been popularized by Mathéron (1963) and is named in
honor of D. G. Krige, a noted South African mining geologist and statistician. PMWIN
assumes that the measurement data are stationary and isotropic. The Kriging method
estimates the value at a model cell from a user-specified number of adjacent data values
while considering the interdependence expressed in the variogram.
A variogram is a plot of semivariance ( versus vector distance h. The variogram is used
(h)
to define the relationship of the measurement values or to estimate the distance over which
measurement values are interdependent. When you select Kriging as the gradding method,
a Variogram appears. Click this button to display the Variogram dialog box (Fig. 5.3). You
need to select a variogram model from the drop-down box and specify the parameters for the
selected variogram model. PMWIN does not provide a procedure for fitting the selected
variogram curve to the measurement data. This is a task for geostatistical software, e.g.,
VarioWin (Y. Pannatier, 1996) or GEO-EAS (E. Englund and A. Sparks, 1991) by the US-