Water Quality Monitoring of River Ganga Using Non-Linear Data Analytics

Abstract

The Ganga River is one of India's biggest and most significant rivers, and the health and welfare of millions of people depend on the purity of its water. The traditional linear models that have been used extensively to assess water quality have limitations in their ability to capture the intricate non-linear interactions between the water quality factors. On the other hand, non-linear data analytics are able to identify these linkages and can offer more precise and trustworthy estimates of water quality. In order to monitor the River Ganga's water quality, this study suggests a non-linear data analytics approach that entails gathering and studying a significant amount of water quality data. The results show that the proposed approach outperforms traditional linear models and can provide valuable insights into the water quality of the River Ganga.