Application of a coupled mechanistic and data-driven model for water level prediction considering the temporal and spatial effects of runoff evolution in cascade hydropower stations

Key Points

• The outcome of water level predictions reveals the influence of runoff evolution over time and space.
• Key evidence shows improved accuracy in predictions when using a combined mechanistic and data-driven approach.
• Observational analysis focuses on different spatial and temporal effects on water levels in hydropower stations.
• This might enable better management practices to optimize the operations of cascade hydropower systems.