A(QUA)LITY: Water Quality Prediction for Indian States with Varied Parameters Using Ensemble Machine Learning Models

Water quality is a critical concern for sustainable development and public health. This study focuses on the prediction of water quality for different Indian states, considering a variety of parameters. The objective is to develop an accurate prediction model that can assist in effective water management strategies and decision-making processes. To achieve this, an ensemble of machine learning models is employed, leveraging the strengths of multiple algorithms. The dataset consists of water quality measurements and associated parameters collected from various monitoring stations across different states in India. The ensemble model is trained and evaluated using these datasets, and its performance is compared against individual ML models. The results demonstrate that the ensemble approach outperforms individual models, yielding more accurate water quality predictions. The findings of this research can contribute to the development of proactive measures for ensuring water quality, aiding policymakers, environmentalists, and water resource managers in their efforts to protect and sustain this vital resource.