Determining areas most likely to flood amid changing land use, rainfall and weather patterns is expensive and complicated.
New research from the University of Georgia (UGA) outlines a simplified, cost-effective method for developing flood maps that reflect the uncertainty in flood predictions
Engineering professor Brian Bledsoe, director of UGA’s Institute for Resilient Infrastructure Systems (IRIS), and alumnus Tim Stephens use confidence intervals and standard of deviation around a specific flood prediction.
Published in the journal Water, the study offers “a practical, simplified approach for quantifying uncertainty in flood hazard estimates” by modeling flooding in two urban watersheds: Proctor Creek in Atlanta, Georgia and Bronx Wash in Tucson, Arizona.
Bledsoe said, “Conventional flood hazard mapping tends to draw a single line showing the flood zone, which is often interpreted by the public as, ‘You’re not going to get flooded if you’re outside the line.’ In reality, that line can be very uncertain and fuzzy, and a large proportion of flood damages occur outside of it.”
Flooding in U.S. urban areas cost more than $106 billion between 1960 and 2016, disrupting life, damaging property and harming people.
The simplified statistical approach is expected to better protect people and property – enabling most municipalities, especially communities with limited resources, to access results that are “very similar and acceptable” compared to outputs from traditional time-intensive and complex hydraulic modeling.
The authors added that the “method should result in improved maps that are more frequently updated.”
“It can be implemented with a small increase in the level of effort for traditional regulatory flood hazard studies, making the incorporation of uncertainty much more approachable, viable, and cost effective,” said Stephens.
Researchers have begun coordinating with the U.S. Army Corps of Engineers, the Federal Emergency Management Agency (FEMA), the Georgia Emergency Management Agency, floodplain management associations, and various municipalities.