Next Stages in Aquifer Vulnerability Studies by Integrating Risk Indexing with Understanding Uncertainties by using Generalised Likelihood Uncertainty Estimation

Abstract

A strategy is presented in this paper on the DRASTIC framework to integrate: (i) reducing subjectivities; (ii) transforming vulnerability indexing to risk indexing; and (iii) understanding inherent uncertainties. Notably, indexing refers to relative values for spatial comparisons within an aquifer using a set of incorporated data layers. The strategy also pools together catastrophe theory, fuzzy membership function and Generalised Likelihood Uncertainty Estimation (GLUE), for which data layers are transformed into a limited number of parameters. The strategy produces some anecdotal evidence from a study area, despite the sparse data availability that (i) treating subjectivities by a fuzzy-catastrophe scheme enhances accuracy and (ii) GLUE provides an insight, such that hotspots of high vulnerability have lower uncertainty, whereas low-vulnerable areas are associated with higher uncertainty. Also, risk indexing reveals that the study area suffers from inappropriate planning practices both in agricultural activities and in groundwater abstraction.