This web page addresses a way to quantitatively express the amount of confidence which may be placed upon anomalies on contour maps. The importance of understanding uncertainty in contour mapping in geology results from the necessity of making decisions related to anomalies based on inaccurate data. For example, a contour map of the elevation of the top of bedrock beneath a cover of glacial drift might be based on data furnished by water well drillers or seismic shot-hole drillers. These data may be known to contain considerable error which is evidenced by discrepancies in data from holes drilled at nearly the same place. Nevertheless, this could be the only data available, and certain anomalies on the map may be interesting because they suggest the presence of buried bedrock valleys which might contain sand and gravel aquifers. Aquifer exploration is not the only application of contour maps affected by uncertainty. Many tasks in oil and gas exploration also involve contour maps, and costly decisions must be made based on the maps.
The scientific paper attached to this page via the link below describes one approach to this problem of quantitatively comparing anomalies which result from mechanical (as opposed to interpretational) contouring. This approach determines minimum values for the probabilities that individual anomalies actually exist and are not merely the result of measurement errors or differences in geologic interpretation. Such measurement errors are especially important in subsurface geologic data because of the difficulty of interpreting subsurface information. Indeed, two geologists independently studying cuttings and other data from the same bore-hole may produce significantly different logs of the depths and classification of materials encountered in drilling the hole.
The method of calculating the probabilities of anomalies is described in the paper accessed by the following link: The Probability of Anomalies on Contour Maps.
Addendum
Another page on this web site that is related to the application of statistics to aquifer exploration is Aquifer Exploration Probability.
Revised: August 14, 2019