Peak-flow and low-flow magnitude estimates at defined frequencies and durations for nontidal streams in Delaware

John C. Hammond; Edward J. Doheny; Jonathan J.A. Dillow; Mark R. Nardi; Peter A. Steeves; Daniel L. Warner

doi:10.3133/sir20225005

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Peak-flow and low-flow magnitude estimates at defined frequencies and durations for nontidal streams in Delaware

John C. Hammond·Edward J. Doheny·Jonathan J.A. Dillow·Mark R. Nardi·Peter A. Steeves·Daniel L. Warner

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Abstract

Reliable estimates of the magnitude of peak flows in streams are required for the economical and safe design of transportation and water conveyance structures. In addition, reliable estimates of the magnitude of low flows at defined frequencies and durations are needed for meeting regulatory requirements, quantifying base flows in streams and rivers, and evaluating time of travel and dilution of toxic spills. This report, in cooperation with the Delaware Department of Transportation and the Delaware Geological Survey, presents methods for estimating the magnitude of peak flows and low flows at defined frequencies and durations on nontidal streams in Delaware, at locations both monitored by streamflow-gage sites and ungaged. Methods are presented for estimating (1) the magnitude of peak flows for return periods ranging from 2 to 500 years (50-percent to 0.2-percent annual-exceedance probability), and (2) the magnitude of low flows as applied to 7-, 14-, and 30-consecutive day low-flow periods with recurrence intervals of 2, 10, and 20 years (50-, 10-, and 5-percent annual non-exceedance probabilities). These methods are applicable to watersheds that exhibit a full range of development conditions in Delaware. The report also describes StreamStats, a web application that allows users to easily obtain peak-flow and low-flow magnitude estimates for user-selected locations in Delaware. Peak-flow and low-flow magnitude estimates for ungaged sites are obtained using statistical regression analysis through a process known as regionalization, where information from a group of streamflow-gage sites within a region forms the basis for estimates for ungaged sites within the same region. Ninety-four streamflow-gage sites in and near Delaware with at least 10 years of nonregulated annual peak-flow data were used for the peak-flow regression analysis, a subset of the 121 sites for which peak-flow estimates were computed. These sites included both continuous-record streamflow-gage sites as well as partial record sites. Forty-five streamflow-gage sites with at least 10 years of nonregulated low-flow data available were used for the low-flow regression analyses, a subset of the 68 sites for which low-flow estimates were computed. Estimates for gaged sites are obtained by combining (1) the station peak-flow statistics (mean, standard deviation, and skew) and peak-flow estimates using the recent Bulletin 17C guidelines that incorporate the Expected Moments Algorithm with (2) regional estimates of peak-flow magnitude derived from regional regression equations and regional skew derived from sites with records greater than or equal to 35 years. Example peak-flow estimate calculations using the methods presented in the report are given for (1) ungaged sites, (2) gaged sites, (3) sites upstream or downstream from a gaged location, and (4) sites between gaged locations. Estimates for low-flow gaged sites are obtained by combining (1) the station low-flow statistics (mean, standard deviation, and skew) and low-flow estimates with (2) regional estimates of low-flow magnitude derived from regional regression equations. Example low-flow estimate calculations using the methods presented in the report are given for (1) ungaged sites, (2) gaged sites, (3) sites upstream or downstream from a gaged location, and (4) sites between gaged locations. A total of 54 sites in the Coastal Plain region were used to develop peak-flow regressions for the region and 40 sites were used for the Piedmont region. Similarly, 24 sites were used for low-flow regression equation development in the Coastal Plain, with 21 in the Piedmont. Peak and low-flow site inclusion in the Coastal Plain tended to be more restricted with tidal influence and ranges of basin characteristics, including drainage area, limiting regression equation development and application. Regional regression equations for peak flows and low flows, as applicable to ungaged sites in the Piedmont and Coastal Plain Physiographic Provinces in Delaware, are presented. Peak-flow regression equations used variables that quantified drainage area, basin slope, percent area with well-drained soils, percent area with poorly drained soils, impervious area, and percent area of surface water storage in estimating peak-flow estimates, whereas low-flow regression equations used only drainage area and percent poorly drained soils in the estimation of low flows. Average standard errors for peak-flow regressions tended to be lower than those for low- flow regressions, with lower errors in the Piedmont region for both peak- and low-flow regressions. For peak-flow estimates, a sensitivity analysis of Piedmont regression equation estimates to changes in impervious area is also presented. Additional topics associated with the analyses performed during the study are discussed, including (1) the availability and description of 32 basin and climatic characteristics considered during the development of the regional regression equations; (2) the treatment of increasing trends in the annual peak-flow series identified at 18 gaged sites and inclusion in or exclusion from the regional analysis; (3) regional skew analysis and determination of regression regions; (4) sample adjustments and removal of sites owing to regulation and redundancy; and (5) a brief comparison of peak- and low-flow estimates at gages used in previous studies.

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John C. Hammond, Edward J. Doheny, Jonathan J.A. Dillow, Mark R. Nardi, Peter A. Steeves, Daniel L. Warner. 2022-02-18. Peak-flow and low-flow magnitude estimates at defined frequencies and durations for nontidal streams in Delaware. https://doi.org/10.3133/sir20225005

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