Parameterisation options

Stochastic parameterisation

SPRING allows the stochastic generation of spatially correlated or non-correlated input parameters like hydraulic conductivity.

1. Stochastic generation of (spatially uncorrelated) data

Stochastically generated parameter (following a defined function) are assigned to all or individual nodes respectively elements of a layer.

2. Stochastic generation of spatially correlated data

Spatially correlated data are generated using a “turningband” algorithm (exponential approach). The interpolation accounts for the similarity of data as a function of their proximity and spatial correlation lengths may vary in three dimensions.

Interpolation of attributes

Following the mesh generation, geological, hydraulic and hydrologic data, which are in the best case only known locally or for limited areas, are entered. Flexible and customisable geostatistical, global and local interpolation functions interpolate attributes to nodes or elements of the model mesh beyond the known and defined areas.

A wizard allows parameterisation using adjustable geostatistical global and local interpolation functions.

Gaußs interpolation

Inverse distance weighting (IDW)

Kriging

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