Estimating Flood Discharges at Selected Annual Exceedance Probabilities for Unregulated, Rural Streams in Vermont, 2023

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Abstract

This report provides estimates of flood discharge at selected annual exceedance probabilities (AEPs) for streamgages in and adjacent to Vermont and equations for estimating flood discharges at AEPs of 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent (recurrence intervals of 2-, 5-, 10-, 25-, 50-, 100-, and 500-years, respectively) for ungaged, unregulated, rural streams in Vermont with drainage areas between 0.47 and 851 square miles. The equations were developed using generalized least-squares regression and flood-frequency and drainage-basin characteristics from 156 streamgages. Flood-frequency analyses were completed using data through the 2023 water year. The drainage-basin characteristics used as explanatory variables in the regression equations are drainage area, percentage of wetland area, and basin-wide mean of the average annual precipitation. The average standard errors of prediction used to estimate flood discharges at the 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent AEP with these equations are 34.9, 37.1, 38.2, 41.6, 43.8, 46.0, 49.1, and 53.2 percent, respectively. Flood discharges at selected AEPs for streamgages were computed using the Expected Moments Algorithm. Techniques used to adjust an AEP discharge computed from a streamgage record with results from the regression equations and to estimate flood discharge at a selected AEP for an ungaged site upstream or downstream from a streamgage using a drainage-area adjustment are both described. The final regression equations and the flood-discharge frequency data used in this study will be available in StreamStats. StreamStats is an internet-based application that provides automated regression-equation solutions for user-selected sites on streams.

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APA

Olson, S. A. (2025). Estimating Flood Discharges at Selected Annual Exceedance Probabilities for Unregulated, Rural Streams in Vermont, 2023. USGS Scientific Investigations Report, 2025. https://doi.org/10.3133/sir20255088

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