When science colors outside the lines: Incorporating uncertain future extreme precipitation projections into conventional engineering for high-hazard infrastructure (Invited)

The potential effects of climate change are not generally reflected in the estimates of probable maximum precipitation (PMP) and other metrics of extreme precipitation currently applied to the design and regulation of dams and other high-hazard infrastructure in the U.S. With robust evidence that climate change will increasingly affect extreme rainfall in the future, dam owners and operators, regulatory agencies, and professional engineering associations have been reconsidering practices for PMP estimation and application in risk assessment.

A relatively recent study focusing on Colorado and New Mexico examined a number of different pathways for including climate projection information in PMP applications. The analysis considered a spectrum of model downscaling methods as well as qualitative approaches that leaned more on risk-informed decision-making conceptual choices than specific dataset recommendations. Though multiple quantitative, climate model-driven paths were presented, the state ultimately recommended that the implementation of climate change be accounted for in a uniform 7% increase in PMP estimates, representing the higher-confidence, robust and fundamental Clausius-Clapeyron relationship that exists between the thermodynamically-driven increase in precipitable water and precipitation.

This approach was implemented into new Colorado state dam safety rules, making Colorado the first state in the nation to incorporate climate change information into its dam safety rules. Always looking forward, however, the climate science community continues to produce cutting-edge climate science and increasingly sophisticated and higher-resolution models which offer evermore potential for more refined climate science-informed solutions. The catch is that, of course, cutting edge comes with a cost: new data and methods that incur new learning curves, potential inconsistencies, and new uncertainties that must be characterized and understood before being “user-ready.” Building on lessons learned in Colorado, a national approach is now being undertaken to identify the best cross-section of publicly-available climate projection data and user needs and capabilities; the current status and planned next steps for this effort will be described.