Natural disasters are a fact of life. It’s not a matter of if, but rather of when and where, they will strike. But how do you prepare for an event that may occur only once in a thousand years?
Politicians proposing counterflood measures, city planners evaluating land, emergency services planning for disasters, and insurance firms hedging against loss all need to be able to evaluate the risks of extreme floods. Traditional models assume that the impact is the same in the entire area affected by a flood, but flooding can be more severe in some areas than in others, even during the same flood event. When these models expand to national scales, they break down even further.
Here Quinn et al. present a method to assess the loss exceedance curve, or the probability that total losses will be above a particular dollar amount, across the entire continental United States. This probability-based analysis is an improvement over traditional models, which can estimate only average loss. In previous models, loss from any extreme event is watered down and distributed across all the years in an analysis; in this model, potential loss is calculated each year as a probability.
The scientists expanded an existing model to cover this large and varied area and applied it to 40 years of U.S. Geological Survey data to simulate a thousand years of potential flood events. They calculated the economic loss of tens of thousands of simulated events to generate a loss exceedance curve.
The researchers confirmed that a flood event’s impact can vary even in adjacent areas, and often, the more extreme the event is, the more localized the greatest destruction is. They found that once in a hundred years, U.S. annual total flood losses would exceed US$78 billion. Once in a thousand years, annual losses would exceed US$136 billion. In other words, each year has a 0.1% chance of flood events that cause more damage than Hurricane Katrina, the costliest natural disaster in U.S. history.
According to the study, the largest contributors to national average annual loss are from heavily populated areas such as New Orleans, despite the presence of flood defenses, because of the catastrophic damages that can occur when a defense-exceeding magnitude event takes place.
The method proposed here provides the first spatially realistic, national-scale assessment of flood risk. With this new method, emergency responders in San Francisco or insurance providers in West Virginia will be able to predict what resources they will need in the case of a rare flood.