Evidence-based policy gaps in water resources - Thinking fast and slow on floods and flow

Water resources and municipal engineering practices have matured in Canada over decades. Each year, refined analytical tools are developed and applied in urban flood management. We are now at a crossroads where practitioners hold many tools for ‘doing the project right’, and should be asking if we are ‘doing the right project’ within broader decision-making frameworks addressing the true risk of problems being analyzed and the lifecycle economics of prescribed solutions. Otherwise, evidence-based policy gaps emerging on the prioritization of flood risk factors and flood damages will widen and will misdirect the appropriate type and level of mitigation efforts. For example, despite statistically significant historical decreases in regional short–duration rainfall intensities in southern Ontario, extensive resources are devoted to projecting IDF curves under climate change. “Thinking Fast” by listing recent extreme events to declare ‘new weather reality’ risks, simply based on heuristic availability biases, has replaced data-driven policy decisions and the statistical rigour of evidenced-based “Thinking Slow” problem-solving defined by Kahneman.  Under this skewed risk perspective, a high profile Ontario commuter train flood was mischaracterized as an unprecedented event despite a less than a 5-year return period and a greater flood just weeks before – key operational risks were ignored. Recent Ontario urban flood incidents have been attributed to unprecedented weather despite GIS analysis showing hydrologic drivers two orders of magnitude greater in some watersheds. As analytical tools have matured, constraints for effective water management are less likely to be technical but rather scientific (inadequate representation of urban groundwater systems where simulated baseflows do not match observations), institutional (arbitrary scale-based boundaries between municipality vs. watershed agency overland flow management), economic (unaffordable green infrastructure solutions based on cost/benefit and ‘flat’ normalized loss trends), or operational. Evidence-based policies and water management solutions are needed from a broad risk and economic framework recognizing these barriers and uncertainties in the application of analytical tools.