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An Investigation of Strategies to Predict Flood-Peak Discharges on Variously-Sized Watersheds in Ohio

Published by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan

Citation:  Paper number  701P0904,  . (doi: 10.13031/2013.17426)
Authors:   Jessica L. D’Ambrosio, Andy Ward, Lance Williams

This study (1) evaluated how flood-peak discharges are associated with several common approaches for determining the recurrence interval (return period) and annual frequency of storm events, and (2) analyzed and tested the United States Geologic Survey (USGS) rural and urban flood-peak discharge regression equations for Ohio to determine if they can provide effective estimations of peak discharges at lower recurrence intervals (less than 2 years) and using simple, practical data collection methods. The USGS equations were tested on 79 watersheds in Ohio with various drainage sizes. An analysis of measured discharge used annual series streamflow data from USGS gaging stations and related it to recurrence interval using the Weibull method. An analysis of predicted discharge involved solving the USGS equations and comparing the results to measured discharge values. This relationship was evaluated based on y = (1)x. Slope and intercept terms were evaluated for significance (alpha = 0.05) for each trend line equation. In general, on smaller watersheds (less than 35 mi2) the USGS rural and urban equations provided reasonably good estimates of measured discharge. On watersheds greater than 100 mi2, the USGS urban equation provided good estimates of measured discharge. Different methods of collecting data for the rural equation variables included the use of USGS 7.5-minute topographic quadrangle maps and Geographic Information Systems (GIS) technology. Comparing the two methods showed that for the watersheds used in this study, simple practical methods of data collection provided similar estimations of peak discharge to data gathered using GIS. Manipulating the coefficients in the urban equation through regression analysis provided even better estimates indicating that some modification to the current urban equation may be useful. The basin development factor (BDF) variable was not significant (alpha = 0.05) in the urban equation across all watersheds sizes and recurrence intervals suggesting that the watersheds used in the study may not be urbanized enough for it to be important in the equation. However, this variable is needed because it is the only indicator of urban development in the USGS equations.

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