Abstract
The standard approach to flood frequency analysis (FFA) fits mathematical functions to sequences of historic flood data and extrapolates the tails of the distribution to estimate the magnitude and likelihood of extreme floods. Here, we identify the most exceptional floods in the United States as compared against other major floods at the same location, and evaluate how the flood-of-record (Qmax) influences FFA estimates. On average, floods-of-record are 20% larger by discharge than their second-place counterparts (Q2), and 212 gages (7.3%) have Qmax:Q2 ratios greater than two. There is no clear correspondence between the Qmax:Q2 ratio and median instantaneous discharge, and exceptional floods do not become less likely with time. Excluding Qmax from the FFA causes the median 100-year flood to decline by −10.5%, the 200-year flood by −11.8%, and the 500-year flood by −13.4%. Even when floods are modelled using a heavy tail distribution, the removal of Qmax yields significantly “lighter” tails and underestimates the risk of large floods. Despite the temporal extension of systematic hydrological observations in the United States, FFA is still sensitive to the presence of extreme events within the sample used to calculate the frequency curve.
Original language | English (US) |
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Article number | e12512 |
Journal | Journal of Flood Risk Management |
Volume | 12 |
Issue number | S1 |
DOIs | |
State | Published - Oct 1 2019 |
Bibliographical note
Funding Information:information Alexander von Humboldt FoundationThis work was conducted during a Humboldt Research Fellowship for Experienced Researchers awarded to S.St.G., and is the product of a collaboration fostered by the PAGES Floods Working Group. Additional support was provided by the Goethe-Institut. We thank Victor Baker, Lin Ji, Tao Liu, and an anonymous reviewer for comments on a prior version of the manuscript that improved the final product substantially.
Publisher Copyright:
© 2018 The Chartered Institution of Water and Environmental Management (CIWEM) and John Wiley & Sons Ltd
Keywords
- United States
- flood frequency analysis
- floods
- heavy tail analysis
- record floods