|Wanted: Evidence-Based, Data-Driven Water Resources|
Engineering Policy .. Braaaaaaaaains !
Evidence-based policy gaps in water resources - Thinking Fast and Slow on Floods and Flow
One might expect that the "dumbing-down" of media and our communications surrounding topics of great importance to society would not affect the engineering profession, and the important things that we do to serve the public and protect the environment. But you'd be wrong.
I first explored the how discussions and reporting on extreme weather and flooding in water resources engineering have fallen prey to the knee-jerk-reaction, quick-fix crowd back in late 2015 in this post called "Thinking Fast and Slow About Extreme Weather and Climate Change":
My first inclination that facts were falling by the wayside came earlier in 2015 when I found that the Insurance Bureau of Canada and Institute for Catastrophic Loss Reduction's Telling the Weather Story cited arbitrary weather frequency shifts as real Environment and Climate Change Canada IDF data - that was laid out in this presentation.
Now my examination of how we frame and solve problems in the realm of flood risk management - including the identification and prioritization of causes of flooding - has been published in the Journal of Water Management Modeling. Its called Evidence Based Policy Gaps in Water Resources: Thinking Fast and Slow on Floods and Flow :
What's it all about? Well here's the paper's abstract:
"Water resources management and municipal engineering practices have matured in Canada over recent decades. Each year, more refined analytical tools are developed and used in urban flood management. We are now at a state where practitioners must use these tools within broad decision making frameworks to address system risks and the life cycle economics of prescribed solutions. Otherwise, evidence based policy gaps in the prioritization of risk factors and damages will widen and lead to misdirected mitigation efforts. For example, despite statistically significant decreases in regional short duration rainfall intensities in Southern Ontario, extensive resources are devoted to projecting IDF curves under climate change. Thinking fast, as defined by Daniel Kahneman, through listing recent extreme events to declare new weather reality risks based on heuristic availability biases, has replaced data driven policy and the statistical rigour of thinking slow problem solving. Under this skewed risk perspective, a high profile Ontario commuter train flood was mischaracterized as an unprecedented event despite a <5 y return period and a greater flood weeks before. Recent Ontario urban flood incidents have been attributed to unprecedented weather despite GIS analysis showing more critical hydrologic drivers. Constraints on effective water management are now less likely to be technical but rather scientific (inadequate representation of urban groundwater systems), institutional (arbitrary boundaries between city and watershed agency jurisdictions), economic (unaffordable green infrastructure solutions based on cost–benefit analysis and flat normalized loss trends), or operational. Evidence based policies and water management solutions are needed from a broad risk and economic framework that recognizes these barriers and uncertainties in the application of analytic tools."
If you've read the www.cityfloodmap.com blog you've seen these themes before. But nonetheless please give it a read and pass on your comments! Thanks so much.
Robert J. Muir, M.A.Sc., P.Eng.