Flood risk assessment under different multi-purpose reservoir allocation strategies: an operational driven copula approach

Multi-purpose reservoirs in Alpine regions must balance competing demands for flood protection, hydropower generation, and water supply. This requires robust flood risk assessment frameworks to support decision-making under uncertainty. To this end, the aim of this work is to develop an innovative copula-based approach to evaluate flood risk mitigation strategies for Alpine reservoirs by simulating compound events of flood peaks and volumes through Monte Carlo generation.

Bivariate copulas are fitted to observed flood peak discharges and corresponding event volumes extracted from streamflow data, and subsequently employed to generate Monte Carlo synthetic flood events for risk assessment. This enables estimation of conditional probabilities of flood volumes given fixed peak discharges, the key variable controlling available storage capacity and thus the reservoir's ability to mitigate subsequent flood events. The simulated scenarios allow systematic exploration of reservoir responses across diverse flood conditions, evaluating how different initial water levels and water release patterns affect downstream flood risk.

A key innovation of our framework is the operation-based definition of flood events rather than statistical percentiles: we use the maximum turbine discharge capacity as the minimum peak threshold, which varies across reservoirs based on their operational characteristics. This directly links the statistical analysis to management constraints. A minimum inter-event duration, determined through sensitivity analysis, distinguishes between multi-peaked events (where volume accumulates from successive peaks) and truly independent flood occurrences.

The framework provides a quantitative basis for optimizing risk-based trade-offs among multiple water uses, explicitly accounting for how stored volumes affect both flood protection and competing demands, enabling reservoir operators and local authorities to quantify flood risk under alternative water allocation scenarios.