Reservoir Risk Operation of 'Domestic-Production-Ecology' Water Supply Based on Runoff Forecast Uncertainty

Water supply operation of a reservoir group is a critical strategy for mitigating conflicts between water resource supply and demand in a basin. However, the uncertainty of runoff forecast presents significant challenges to this operation. To explore the risk laws of the complex water supply process, this study focuses on analyzing the three primary source streams and the main stream of the Tarim River, the largest inland river in China. Initially, a runoff forecast model is developed utilizing Long Short-Term Memory Artificial Neural Networks (LSTM-ANN) to generate runoff datasets. Subsequently, a theoretically optimal operation process for the reservoir group is derived through a long-series deterministic multi-objective operation, which establishes boundary constraints for water supply risk operation. Finally, the runoff forecast results are integrated into an uncertainty water supply risk operation model to assess the associated water supply risk. The results indicate that: 1) Due to varying guarantee rates and water supply priorities among different sectors, the risk of ecological water supply is the highest, followed by agriculture and then domestic-production. 2) Within an effective forecast range of 0% to 20%, the most significant increase occurs when the error ranges between 5 to 10%. 3) As the reservoir regulation capacity in mountainous areas increases, the average water supply risk value for agriculture decreases from 0.086 to 0.040, representing a 53.1% risk reduction. The research results are of great significance to the reservoir group risk operation and the water supply safety in the basin.