A StreamStats migration on February 10, 2023 updated regression equations for Wisconsin StreamStats.
StreamStats regression equation updates for Wisconsin
Flood discharges for the 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2- percent annual exceedance probability were computed at 299 unregulated streams in Wisconsin using the Expected Moments Algorithm (EMA) method with the Multiple Grubbs-Beck test for potentially influential low floods (PILFs), as recommended in Bulletin 17C (England and others, 2019). Regression equations relating flood discharges to basin characteristics were developed and can be used to estimate flood discharges at ungaged locations in Wisconsin. Generalized least squares regression was used to fit flood frequency regression equations using the WREG package in R (Farmer, 2017; R Core Team, 2021). Basin characteristics included in the final regression equations include drainage area, saturated hydraulic conductivity, percent forest, percent herbaceous upland, percent open water, and the maximum 24-hour precipitation with a 10-year recurrence interval. The standard error of prediction for regression equations ranges between 40 and 71 percent, and the pseudo coefficient of determination ranges between 0.8 and 0.95.
- England, J.F., Jr., Cohn, T.A., Faber, B.A., Stedinger, J.R., Thomas, W.O., Jr., Veilleux, A.G., Kiang, J.E., and Mason, R.R., Jr., 2019, Guidelines for determining flood flow frequency—Bulletin 17C (ver. 1.1, May 2019): U.S. Geological Survey Techniques and Methods, book 4, chap. B5, 148 p., https://doi.org/10.3133/tm4B5.
- Farmer, W.H., 2021, WREG: Weighted Least Squares Regression for Streamflow Frequency Statistics: U.S. Geological Survey software release, R package, Reston, Va., https://doi.org/10.5066/P9ZCGLI1.
- R Core Team, 2021, R: A language and environment for statistical computing: R Foundation for Statistical Computing, Vienna, Austria, accessed September 1, 2021, at https://www.R-project.org/