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Flood estimates often assume that the statistical behaviour of annual peak streamflow remains constant. Sara B. Levin investigates an alternative for locations where records show trends or shifts, using regression to adjust flood-frequency estimates for changing conditions.
The study covers streamgages in nine north-central states and compares models using time with models using a climate predictor. It explains the assumptions behind the analyses, the screening of candidate sites, and estimates of the flood associated with a one-percent annual exceedance probability. Results show where time-adjusted and climate-adjusted approaches can be applied, while the discussion addresses their limitations and the interpretation of estimates.
First published in 2025, the report contains the full statistical methods, original maps and graphs, findings, and references. It offers a detailed example of how hydrologists approach risk estimates when a long record cannot be treated as a sample from one unchanging distribution.
Sara B. Levin. Nonstationary Flood Frequency Analysis Using Regression in the North-Central United States. U.S. Geological Survey, 2025. https://doi.org/10.3133/sir20255034. Public domain U.S. Government publication. Original agency, author and photograph credits retained.