Addressing Critical Gaps in Flood Risk Assessment
There is a hidden crisis in the field of flood risk management. The science is simply not mature enough for us to accurately understand flood risk. Corporate data-vendors are selling flood risk estimates while refusing to disclose their uncertainty. Other actors are selling data to states and municipalities for planning purposes generated in ways that are simply mathematically incorrect. Well-intentioned analysts are structurally pushed towards releasing modeling results that they know are inadequate; mostly their jobs are to bill hours and re-do their last analysis in a new location. It is currently nobody's job to make sure that the models being used actually work.
It is widely known that FEMA floodmaps are outdated both in content and methodology (through no fault of FEMA staff themselves – they have neither the funding nor the congressional mandate to properly characterize flood risk across the United States). Corporate data-vendors claim to provide a solution, but refuse to disclose uncertainty information—violating established standards of practice in applied statistics—and hide from scientific scrutiny with closed-source modeling practices. From the information they do disclose, it is clear that they systematically ignore critical flood drivers from consideration, and assume that flood outcomes are uniquely determined by a single variable measuring rainfall or streamflow severity. The truth is that storms which cause flooding are more than a single number—for a given storm, rainfall varies in time and space and streamflow rises to a peak before declining. Models typically assume an average soil moisture condition, when oftentimes the worst floods occur when the soil has already been saturated by a recent storm. Modeling flood risk with a single scalar variable and treating everything else as constant systematically underestimates the variability of flooding and therefore underestimates the severity of the worst and most impactful floods.
Naturally, these univariate models can't resolve flood risk from river flows and rainfall at the same time (flood risk from multiple flood hazards is called "compound flood risk"). That's a problem, because a lot of places have both rivers and rain. Scientists and engineers are aware of this problem, but have not managed to fully resolve it. Current methods in compound flood risk analysis are not mature enough for safety-critical applications in flood resilience planning or infrastructure design. While recent work has mostly figured out how to handle compound flood risk from hurricanes (with major caveats). But as far as we can tell, for compound flood risk which isn't related to hurricanes, nobody has come up with a method that works (although some might disingenuously claim otherwise).
Some methods seeing active use in flood risk analysis are so deeply problematic and unrigorous that their ongoing use in safety-critical applications reflects a lack of scientific integrity. Other major concerns in the state of practice of flood risk analysis do not reflect an integrity issue but nonetheless require significant research to resolve core methodological gaps in order to effectively quantify flood risk and enable effective risk mitigation planning.
Integrity Issues
- Addressing Corporate Vendors and Univariate Flood Hazard
- Addressing Bivariate Design Storms – They Don't Work
- Inappropriate Rainfall Modeling for Tropical Storms