A Reservoir Group Flood Control Operation Decision-Making Risk Analysis Model Considering Indicator and Weight Uncertainties

Reservoir group flood control scheduling decision-making faces multiple uncertainties, such as dynamic fluctuations of evaluation indicators and conflicts in weight assignment. This study proposes a risk analysis model for the decision-making process: capturing the temporal uncertainties of flood control indicators (such as reservoir maximum water level and downstream control section flow) through the Long Short-Term Memory (LSTM) network, constructing a feasible weight space including four scenarios (unique fixed value, uniform distribution, etc.), resolving conflicts among the weight results from four methods (Analytic Hierarchy Process (AHP), Entropy Weight, Criteria Importance Through Intercriteria Correlation (CRITIC), Principal Component Analysis (PCA)) using game theory, defining decision-making risk as the probability that the actual safety level fails to reach the evaluation threshold, and quantifying risks based on the First-Order Second-Moment (FOSM) method. Case verification in the cascade reservoirs of the Qiantang River Basin of China shows that the model provides a risk assessment framework integrating multi-source uncertainties for flood control scheduling decisions through probabilistic description of indicator uncertainties (e.g., Zmax1 with μ = 65.3 and σ = 8.5) and definition of weight feasible regions (99% weight distribution covered by the 3σ criterion), filling the methodological gap in risk quantification during the decision-making process in existing research.