Artificial Intelligence Tools and Techniques for Water-Resources Assessment in Africa

Abstract

This paper presents the development of a hydrogeological expert system able to handle the drilling location problem within the scope of village water-supply programs. This work is based on the experience the authors gained from thousands of drillings carried out in fifteen African countries. The cognitive model comes from the practical know-how acquired from real-world programs, from original statistics and probabilistics analyses showing connections between data collected during the drilling-site selection and hydrodynamic parameters registered in the borings and from the research the authors carried out in the artificial intelligence field to propose a comprehensive knowledge modeling framework. The paper includes a description of the specific knowledge involved in the drilling location process. Relevant hydrogeological parameters recognition and examples of advanced computer knowledge modeling methods are presented. First the rules of thumb and the interpretative frames retained for the cognitive model are described, then the characteristics of the HYDROLAB expert system devoted both to computer-aided decision and to computer-assisted learning support.