Balancing aquaculture and estuarine ecosystems: machine learning-based water quality indices for effective management.

This study delves into the environmental impact of inland aquaculture on estuarine ecosystems by examining the water quality of four estuarine streams within the key inland aquaculture zone of South India. In this region, extensive and intensive aquaculture practices are common, posing potential challenges to estuarine health. The research explores the predictive capabilities of the Gaussian elimination method (GEM) and machine learning techniques, specifically multi-linear regression (MLR) and support vector regressor (SVR), in forecasting the water quality index of these streams.