Abstract

Groundwater resources are limited and difficult to predict in crystalline bedrock due to heterogeneity and anisotropy in rock fracture systems. Municipal-level governments often lack the resources for traditional hydrogeological tests when planning for sustainable use of water resources. A new methodology for assessing groundwater resources potential (GRP) based on geological and topographical factors using principal component analysis (PCA) and analysis of variance (ANOVA) was developed and tested. ANOVA results demonstrated statistically significant differences in classed variable groups as well as in classed GRP scores with regard to hydrogeological indicators, such as specific capacity (SC) and transmissivity. Results of PCA were used to govern the weight of the variables used in the prediction maps. GRP scores were able to identify 79% of wells in a verification dataset, which had SC values less than the total dataset median. GRP values showed statistically significant correlations using both parametric (using transformed datasets) and non-parametric methods. The method shows promise for municipal or regional level planning in crystalline terrains with high levels of heterogeneity and anisotropy as a hydrogeologically and statistically based tool to assist in assessing groundwater resources. The methodology is executed in a geographic information systems environment, and uses often readily available data, such as geological maps, feature maps and topography, and thus does not require expensive and time-consuming aquifer tests.

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