Abstract:
Groundwater potential prediction here refers to the total amount of permanent storage water
that exists in the aquifers. Groundwater potential is the function of the porosities of the rocks
and amount of open space in rocks that could store water. Most of Ethiopia population lives in
rural area have not got sufficient water for drinking, irrigation and livestock raring. Lack of
pure water in the rural area and town is the major problem for industrial development and
economically. Using ground water is the solution for the problem of lack addressing sufficient
water for people in Ethiopia. The aim of this study was developing knowledge base system for
groundwater potential prediction. To do so, a design science research methodology was used.
Development of KBS for GWPP to improve the quality of decision making for fresh
hydrologist and geologist to predict groundwater potential effective and efficiently in the
shortage of domain expert. To achieve this objective knowledge was acquired by using sample
size from Jimma University Institute of Technology, Faculty of Civil and Environmental
Engineering, Jimma Zone and Jimma Town water and Energy organizations. Purposive
sampling techniques used to selected domain expert and secondary was collected from
difference of journal article, groundwater directive, manuals, books and different website
working on assessment of groundwater potential.KBS is developed by using conceptual model
and representation which is supported by decision tree easily to understand and interpret the
steps of groundwater potential prediction. Prototype is developed based on the conceptual
model using WINprolog version 6.4.0. production rule if then rules,and forward chaining
reasoning mechanism to inference engine rule and appropriate decision making. Performance
of the prototype KBS have got excellent acceptance by system evaluator and 85.7% users
satisfied by the performance of the prototype developed. Finding of this research was
performance of system evaluated by using confusion matrix predict validation techniques by
using twenty two parameters of predicting groundwater potential then result of validation
parameters of prototype is 84.33% accurate to predict GWPP. Future work proposed by
researcher predicting spring water potential continuity by using knowledge based system
