Regional prediction of groundwater potential mapping in a multifaceted geology terrain using GIS-based Dempster–Shafer model

Abstract

A prediction at a regional scale of groundwater productivity potential mapping in an area is subjected to uncertainties that must be efficiently managed for enhancing decision making. This study explored the potential of a GIS-based Dempster–Shafer theory (DST) model as a spatial prediction model to offer solution to this problem. Seven criteria/factors regarded as positive indicators to the existence of promising groundwater reservoir in a given study area were selected and weighted in a probability-based DST approach to compute degrees of belief functions component indexes. The results of the computed belief function indexes values were processed in GIS environment to generate belief functions maps among which the uncertainty index map established uncertainty result of relatively low range of <1 to 9 % prediction in the area. The belief index map which provides concrete support for the existence of promising aquifers in the area was modeled to produce the groundwater potential zones prediction (GPZP) map. A developed mathematical model based on the relationship between the estimated Belief index values and borehole yield data established the influences of diverse rock type’s properties on the aquifer productivity in the area. The effect of coherence of criteria on the efficiency of DST model as a prediction model was also examined. The GPZP map produced was found to be 85.71 % accurate. The results of the examination of the effect of coherence of the criteria revealed that the ability of the DST model to produce accurate prediction is dependent on the exhaustiveness of the set of criteria used. The obtained results illustrate the usefulness of knowledge-driven DST model in GIS-based predictive mapping of groundwater potential zones. The results also show the capability of DST model in managing uncertainty associated with the predictive potential zones in the study area.