Climate Scenario Generator for Water Network Stress Testing

Climate Scenario Generators for Water Network Stress Testing translate coarse global or regional climate model (GCM/RCM) outputs into high-resolution, physically consistent, and statistically robust boundary conditions tailored to urban water systems. They incorporate downscaling techniques (e.g., bias-corrected quantile mapping, weather generators, or stochastic rainfall-runoff emulators) to produce time series of demand drivers (e.g., temperature-dependent water consumption), supply stressors (e.g., reduced reservoir inflows, drought-induced source limitations), and system hazards (e.g., intense rainfall causing infiltration/inflow or pipe corrosion acceleration). The generator must account for non-stationarity—i.e., shifting statistical properties of climate variables—and interdependencies among stressors (e.g., heatwaves increasing both peak demand and pipe material degradation). Integration with hydraulic simulation engines (e.g., EPANET, InfoWater, or custom agent-based models) enables dynamic stress testing across multiple scenarios—including Representative Concentration Pathways (RCPs) or Shared Socioeconomic Pathways (SSPs)—to quantify failure probabilities, pressure deficits, water age exceedances, or energy use escalation. Crucially, the generator supports scenario discovery methods (e.g., factorial experiments or sensitivity-informed sampling) to identify critical stressor combinations rather than relying solely on 'plausible but extreme' cases.