Spatially Quantifying the Uncertainty of Salinity Risk Assessments
Abstract
Salinity management relies heavily upon the mapping of the watertable to predict regions at risk of salinity. Current mapping techniques often ignore the influence of topography and interpolate using only the reduced water level (RWL) at each bore. The result, frequently, is an exaggerated area of shallow
watertable and area apparently at risk of salinity [Peterson et al 2003].
Sequential Gaussian simulation (SGS), a stochastic geostatistical technique, was used with kriging with external drift (KED) to quantify and map the risk and probability of shallow water tables through central Victoria. This paper reviews the SGS method for mapping uncertainty to that from KED. While KED produces significantly improved water table maps it’s map of uncertainty was found to be valid only in regions of very high bore density. In regions of lesser bore density KED, and presumably even simpler methods such as bore density maps, frequently over estimated the uncertainty and had no correlation to the more rigorous SGS map. A water level monitoring network designed on the basis of KED uncertainty maps or bore density maps alone is likely to be non-optimal in terms of the number of bores and their location.
Authors
T. Peterson & B. Barnett