Spatial variability is of particular concern in performing seepage modeling because there is often uncertainty regarding the ability to measure the hydraulic conductivity (both saturated and unsaturated) of the material at the site. It is possible that laboratory measurements of saturated hydraulic conductivity could be in error by up to two orders of magnitude. If samples are taken around a site, even in the same layer, the amount of variance in saturated hydraulic conductivity can be significant.
The current methods for dealing with this type of uncertainty are often associated with Monte Carlo type techniques, which will vary the material properties through a normal distribution and perform hundreds or thousands of numerical model runs. The draw-back for this method is that, in each trial run, the material properties for the target region are assumed to be homogeneous.
In the field there is often preferential flow noted and such preferential flow can not be accounted for in standard numerical models. Spatial variability allows the user to enter a mean and standard deviation for parameters such as saturated hydraulic conductivity. These parameters can then vary spatially to account for reasonable variation. The potential impact on flow paths can then be examined in detail. This application of technology has significant potential influence on calculations of flow regimes through earth dams, calculation of heap leach drain down times, as well as potential impacts in almost every area of seepage modeling.