Groundwater Quality Assessment of Raipur City Using Machine Learning Models

Groundwater has been a vital source of water consumption across India. Raipur, the capital city of Chhattisgarh, has been utilizing this resource for water consumption and utilization for Irrigation. While water is a necessity for survival, it is also important that water which we uptake is fit for consumption. Groundwater often gets contaminated by the fertilizers and pesticides by affecting the concentration of the major ions and other parameters present in the water. Groundwater Quality Index is a measure to determine the quality of water, which is calculated based on some physicochemical parameters and ions that water contains. The Water Quality Index (WQI) is a really useful measure for assessing the overall water quality. It simplifies the interpretation of information by lowering a huge number of data points to a single value. The WQI is used to assess whether or not groundwater is suitable for drinking. In this paper, the Water Quality Index was calculated based on pH, TA, TH, Chloride, Nitrate, Fluoride, and Calcium. Further, the quality of groundwater was assessed using various Machine Learning Models, namely, Logistic Regression, Decision Tree Classifier, Gaussian NB, Random Forest Classifier, Linear SVC, and XGB Classifier. The best classification was shown by Random Forest Classifier with an outstanding of 100 percent accuracy.