3d Contours

Generation of 3d contours within Environmental Insite is an internal three-step process. The data are queried to select the set of measurements for which the contours will be constructed. Then the measured data is interpolated on the corners of a 3-dimensional mesh. Lastly surfaces are generated representing the selected contour intervals.

The 3d mesh is rectangular, with its lateral extent, vertical extent and horizontal and vertical discretization selected by the user. A finer mesh will create a smoother surface, but may be time consuming to create. There are no absolute constraints as to the number of grid points other than the physical memory in the computer. In most practical cases, the time to plot and the physical memory will not be significant constraints.

Query

Intervals

Contour Setup Dialog

Format

Options

3d Contour Option

In contouring on a x-section or in 3d contouring, multiple measurement points are assigned along the length of the specified measurement interval. The first value in the Points per Sample Interval is the minimum number of points that are assigned to a sample interval. Then the interval height per measurement point is calculated. If this exceeds the entered Max. Interval Height per Point, then the number of points to achieve that value is calculated and that number of points distributed along the interval horizon.

3d Contour Volume Calculation

For 3d contouring, EnviroInsite can estimate the volume occupied by each contour interval and the average value within that interval. The calculations are performed by interpolation to randomly sampled points within the contour grid and estimation of the average interpolated value within each contour interval. The occupied volume is estimated as the grid volume and the fraction of the sample points with values within a given contour interval relative to the total number of points. Results for each iteration are reported to a file called calcvol.txt and printed to a dialog. It is the user's responsibility to check to be sure that the estimated values have satisfactorily converged at the desired level of accuracy.

Estimate Volume - toggle on or off to execute the calculate the volume within each contour interval (only for 3d contouring)

Number of Iterations - number of iterations to be used in calculation of volume within each contour interval (only for 3d contouring)

Initial Number of Sample Points - number of points at which field value is calculated for estimation of volume within each contour interval (only for 3d contouring)

Click here to view a recorded webinar on using 3d contours to calculate contaminant volume and mass

Grid

This tab allows the user to define the grid on which the measured values will be interpolated prior to contouring. Increasing the number of cells may improve the faithfulness of the contoured result to the interpolated field, but increases the time to generate the contours.

Interpolation

This tab allows the user to select the interpolation scheme and the parameters of the interpolation method. The correct selection of interpolation parameters is critical for generation of contours that accurately reflect the field data and our expectations of how the values vary between the measured data points. The default parameters are frequently adequate, although some improvement can be anticipated through trial and error.

Kriging Parameter

The kriging routines are derived from the kt3d routine of the Geostatistical Software Library (GSLIB) authored by Clayton Deutsch and Andre Journel (www.gslib.com).

The reference, GSLIB: Geostatistical Software Library and Users' Guide is highly recommended. Here are the spherical semivariogram models used by EnviroInsite for an isotropic system, where h is the lag, c is the sill, and a is the (practical) range. This is from this link to an introductory text on kriging: Click here for an introductory text on the variogram models

For anisotropic systems h/a in the previous is calculated as

Virtual Points

Virtual points are used to control the generation of contours with sparse data. In those cases or in cases of water bodies that are hydraulically continuous with groundwater, it may be advantageous to create virtual measurement points that will control the resulting contours.