| Summary: | Optimal design of culverts for fish passage for each stream crossing requires the magnitude, duration, frequency and seasonal relationship of the flow and the timing of fish movement. Although previous studies have measured fish swimming abilities and culvert water velocity profiles, there are limited studies in northern regions of the hydrologic relationship among magnitude, duration, frequency and season of discharge for the design of culverts for fish passage. We analyzed streamflow records from 33 gaging stations in southcentral, western, interior, and arctic Alaska (from watersheds with a drainage area less than 100 sq. miles each) to determine the highest consecutive mean discharge with one-, three-, seven and fifteen-day durations, and the lowest consecutive mean discharge with three-, seven-, fourteen- and thirty-day durations. Streamflow during three seasons were analyzed: spring, April 1 to June 30; summer, July 1 to August 31; and fall, Septermber 1 to November 30. The lognormal distribution, using the Blom plotting position formula, was used to estimate flows at recurrence intervals of 1.25, 2, 5, 10 and 20 years. Multiple linear regression equations were developed to predict flows from ungaged watersheds. Significant basin and climatic characteristics for high flows were drainage area, mean annual precipitation and percent of the drainage basin with forest cover. Significant characteristics at low flows were drainage area, mean minimum January temperature, mean annual precipitation and percent of drainage basin covered by forests. This report provides the culvert designer with equations to predict flows, other than the instantaneous peak flow, for use in designing culverts for fish passage. Two example problems are given to show the application of these equations. List of Figures - v List of Tables - vi Acknowledgements - viii 1.0 Introduction - 1 1.1 Description of Problem - 1 1.2 Objective of Study - 2 2.0 Literature Review - 2 2.1 Summary of Fish Passage Culvert Design Methods - 2 2.2 Selection ...
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