River Digital Twin for Water Quality Prediction

River is complex system of system, whose dynamics are influenced by multiple factors such as river characteristics (e.g., gradient and terrain), environmental factors (e.g., rainfall and temperature), and human interventions like building dams, and discharging wastewater. To understand and improve river water quality, a river digital twin is created using a combination of agent-based and physics-based models. Agent-based modeling captures behavioral relationships for ease in modeling complex systems and physics-based models simulate transport and reaction behavior. This integrated approach constructs a digital twin capable of simulating quality parameters under various scenarios, like rainfall, effluent discharge, changing demographics, and climate. The study enhances understanding of river ecosystems and provides a tool for managing their ecological health. The river digital twin is developed considering river and its ecosystem with different inflows and outflows and is applied successfully using a 480 km stretch of an India's largest river, the Ganga.