Abstract:
A number of geological, hydrological, and hydrogeological features related to the aquifers in the Oak Ridges Moraine area extracted from the MOEE water well data, digital...Show MoreMetadata
Abstract:
A number of geological, hydrological, and hydrogeological features related to the aquifers in the Oak Ridges Moraine area extracted from the MOEE water well data, digital geological map, remote sensed Landsat TM images were mapped and analyzed using statistical approaches and GIS. Using the flowing wells as training points, the weights of evidence model was applied to describe the spatial pattern of the high yield confined aquifers, and to measure the correlation between the flowing wells and the regional hydrogeological features. This has led to the identification of binary evidential features to predicting the potential distributions of confined aquifers. These binary patterns correlated to the locations of flowing wells were integrated using multivariate logistic regression model and a predictive map was created to illustrate the potential distributions of confined aquifers in the ORM area. It has been demonstrated that the weights of evidence and logistic regression models implemented in GIS can be used as effective analytical tools to predict the potential of high yield confined aquifers in the study area. The predictive result can be used to interpret the potentia interactions between ground water and surface water system such as river baseflow, ponds and lakes.
Date of Conference: 24-28 June 2002
Date Added to IEEE Xplore: 07 November 2002
Print ISBN:0-7803-7536-X