The use of continuous fuzzy and traditional classification models for groundwater potentiality mapping in areas underlain by granitic hard-rock aquifers

Abstract

Delineating groundwater potential (GWP) zones is very important for the sustainable planning, development and management of the groundwater resources in hard-rock terrains. This is usually undertaken using multi-criteria evaluation methods based on using a data- or knowledge-driven combination of factors that are assumed to control the distribution of groundwater in hard-rock terrains. In the current study, this method was applied on a GIS platform to model GWP zones of a granitic hard-rock terrain in an arid region of central Iran. The groundwater occurrence indicators such as lineaments, drainage density, rainfall, lithology, topographic slope and vegetation cover were firstly prepared in the form of thematic maps and then combined using the traditional classification and continuous fuzzification methods to integrate these layers to produce GWP maps. Zones with high GWP values were identified in valley floors where granite was assumed to be overlain by a thick weathered profile and in highland areas where fracture zones were identified and annual rainfall is higher than at lower elevations. The modeled potentiality maps were validated by a comparison of the distribution of high GWP values and the spatial distribution of existing springs, qanats and wells in the region. Comparing the results of the two applied integration methods highlights the ability of the continuous fuzzy model based on data-driven logistic-based weighting of the thematic maps in delineating the GWP zones. The model will help to reduce the problem of exploration bias and uncertainties resulting from discretization of spatial values into arbitrary classes and defining weights based on the expert judgment in knowledge-driven method of traditional classification. It is recommended for modeling GWP zones and then proper management of the hard-rock aquifers in other regions.