Peak-flow frequency relations and evaluation of the peak-flow gaging network in Nebraska

Estimates of peak-flow magnitude and frequency are required for the efficient design of structures that convey flood flows or occupy floodways, such as bridges, culverts, and roads. The U.S. Geological Survey, in cooperation with the Nebraska Department of Roads, conducted a study to update peak-flow frequency analyses for selected streamflow-gaging stations, develop a new set of peak-flow frequency relations for ungaged streams, and evaluate the peak-flow gaging-station network for Nebraska. Data from stations located in or within about 50 miles of Nebraska were analyzed using guidelines of the Interagency Advisory Committee on Water Data in Bulletin 17B. New generalized skew relations were developed for use in frequency analyses of unregulated streams. Thirty-three drainage-basin characteristics related to morphology, soils, and precipitation were quantified using a geographic information system, related computer programs, and digital spatial data.For unregulated streams, eight sets of regional regression equations relating drainage-basin to peak-flow characteristics were developed for seven regions of the state using a generalized least squares procedure. Two sets of regional peak-flow frequency equations were developed for basins with average soil permeability greater than 4 inches per hour, and six sets of equations were developed for specific geographic areas, usually based on drainage-basin boundaries. Standard errors of estimate for the 100-year frequency equations (1percent probability) ranged from 12.1 to 63.8 percent. For regulated reaches of nine streams, graphs of peak flow for standard frequencies and distance upstream of the mouth were estimated.The regional networks of streamflow-gaging stations on unregulated streams were analyzed to evaluate how additional data might affect the average sampling errors of the newly developed peak-flow equations for the 100-year frequency occurrence. Results indicated that data from new stations, rather than more data from existing stations, probably would produce the greatest reduction in average sampling errors of the equations.