Water Systems Control: from Ensemble Forecasts to Network Topology Optimization

April 17, 2025 | 11:45 a.m.
Conference Room Emilio Gatti
Building 20

Abstract

Climate change intensifies extreme weather events, stressing water resources and demanding optimal reservoir management for competing needs.

Exploring advanced forecast-based control strategies, Lake Como serves as a multi-objective case study.

First, this seminar details a novel algorithm using probabilistic ensemble forecasts to improve decision-making, validated by blocked k-fold cross-validation.

Second, it couples neuro-evolution deep reinforcement learning with time-varying sensitivity analysis to optimize network topologies and evaluate the importance of each forecast across the year and across different compromise solutions.

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