AI ENABLED WATER WELL PREDICTION

Abstract

Water scarcity and groundwater depletion have become major concerns due to rapid urbanization, climate change, and excessive groundwater extraction. Traditional borewell drilling methods are costly and often unsuccessful because they rely heavily on manual geological surveys and expert analysis. This research paper presents an AI Enabled Water Well Prediction System that uses Machine Learning techniques to predict the probability of successful borewell drilling at a selected geographic location. The system integrates environmental parameters such as rainfall, soil type, humidity, temperature, elevation, and geological conditions to generate accurate predictions. The proposed system is developed as a web application using Python Flask, Scikit-learn, SQLite, HTML, CSS, JavaScript, and OpenStreetMap APIs. The machine learning model uses the Random Forest Classifier algorithm to improve prediction accuracy. Experimental results demonstrate an accuracy of approximately 87%, making the system effective for groundwater prediction