Flood frequency analysis is a method used to evaluate flood risk, thereby offering statistics like the “100-year flood” or “500-year flood” that are crucial to dam safety analysis, infrastructure design, and flood mapping in flood-prone regions.
The Truckee River in Reno, Nev. during high flow conditions after a storm in late January, 2016. Image Credit: Kelsey Fitzgerald/Desert Research Institute.
However, the technique utilized to assess such flood frequencies is due for an update, as per a new study by researchers from DRI, the University of Wisconsin-Madison, and Colorado State University.
The floods, even in a single watershed, are considered to be caused by a range of sources, such as snowmelt, rainfall, or “rain-on-snow” events in which rain falls on the present snowpack. But flood frequencies have conventionally been evaluated under the assumption such flood “drivers,” or root causes, are insignificant.
In a new open-access study reported in the journal Geophysical Research Letters, a team headed by Guo Yu, Ph.D,. of DRI analyzed the major common drivers (snowmelt, rainfall, and rain-on-snow events) of historic floods for 308 watersheds present in the Western US, and examined the effect of various flood types on the consequent flood frequencies.
Their study outcomes displayed that most (64%) watersheds experienced two or three flood types frequently across the study period and that rainfall-driven floods, such as rain-on-snow, were considerably bigger compared to snowmelt floods throughout watershed sizes.
Additional analysis performed has displayed that ignoring the special roles of every flood type and traditional methods for producing flood frequency estimates leads to under-estimation of flood frequency at over half of sites, particularly at the 100-year flood and beyond.
In practice, the role of different mechanisms has often been ignored in deriving the flood frequencies. This is partly due to the lack of a physics-based understanding of historic floods. In this study, we showed that neglecting such information can result in uncertainties in estimated flood frequencies which are critical for infrastructure.
Guo Yu, Maki Postdoctoral Research Associate, Desert Research Institute
The study outcomes possess significant impacts for evaluating flood frequencies into the future, as climate change forces conditions in snowmelt-dominated watersheds toward high rainfall.
How the 100-year flood will evolve in the future due to climate change is one of the most important unanswered questions in water resources management. To answer it, we need to focus on the fundamental science of how the water cycle, including extreme rainstorms and snow dynamics, are and will continue to change in a warming climate.
Daniel Wright, Associate Professor, Civil and Environmental Engineering, University of Wisconsin-Madison
The study team believes that this study can turn out to be beneficial to engineers, who depend on precise estimates of flood frequencies while bridges and other infrastructure have been constructed.
Even though several engineers identify that there is an issue with the traditional approach to evaluating flood frequencies, this study offers new insights into the level of error that has been caused.
This study shows that taking into account different physical processes can improve flood risk assessment. Importantly, this result suggests both a need and opportunity to develop new methods of flood frequency assessment that will more accurately reflect flood risk in a warming climate.
Frances Davenport PhD, Postdoctoral Research Fellow, Colorado State University
This study was financially supported by the DRI’s Maki Postdoctoral fellowship, US National Science Foundation Hydrologic Sciences Program (award number EAR-1749638), and Stanford University.
The authors of the study included Guo Yu (DRI/University of Wisconsin-Madison), Daniel Wright (University of Wisconsin-Madison), and Frances Davenport (Stanford University and Colorado State University).
Journal Reference:
Yu, G., et al. (2022) Diverse Physical Processes Drive Upper-Tail Flood Quantiles in the US Mountain West. Geophysical Research Letters. doi.org/10.1029/2022GL098855.