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Reliable estimates of the magnitude and frequency of floods are essential for such things as the design of transportation and water-conveyance structures, flood insurance studies, and flood-plain management. Flood-frequency estimates are particularly important in densely populated urban areas. The U.S. Geological Survey (USGS) is using a multistate approach to update methods for determining the magnitude and frequency of floods in urban and small, rural streams that are not substantially affected by regulation or tidal fluctuations in Georgia (GA), South Carolina (SC), and North Carolina (NC). The multistate approach has the advantage over a single state approach of increasing the number of streamflow-gaging stations (streamgages) available for analysis, expanding the geographical coverage that would allow for application of regional regression equations across state boundaries, and building on a previous flood-frequency investigation of rural streamgages in the Southeastern United States.
Building on the success of a multistate approach for developing regional flood-frequency equations to estimate the magnitude and frequency of floods at ungaged locations in Southeastern rural streams (Gotvald and others, 2009; Weaver and others, 2009; and Feaster and others, 2009), a similar approach is being applied to urban and small, rural streams. For this investigation, “Southeast” refers specifically to GA, SC, and NC. The analytical techniques used incorporate urban and rural streamgages and therefore in addition to urban basins, also can be applied to small, rural streams. The lower limit of drainage area for basins included in the Southeast rural flood-frequency study was 1 square mile (mi2). The lower limit of drainage area for rural basins included in this investigation is 0.1 mi2. Consequently, in this study, small, rural streams refer to those with drainage areas less than 1 mi2. Some of the benefits of including both urban and rural streamgages in the regression analysis are (1) smoother transition between urban and rural flood-frequency estimates, (2) larger database than would be available with just urban streamgages alone, and (3) larger geographical coverage in the hydrologic regions, which will represent a broader range of hydrologic conditions likely to occur at ungaged locations.
The focus of the investigation is on three hydrologic regions (HR) in the Southeast (fig. 1): HR1, Piedmont-Ridge and Valley; HR3, Sand Hills; and HR4, Coastal Plain. The Blue Ridge (HR2) was not included due to the lack of urban streamgages having sufficient record lengths to include in a regional regression analysis. Regression equations for HR5, which is contained solely in southwest GA, were previously developed and published by Gotvald and Knaak (2011).
The objectives for the investigation will be to:
100-Year-Flood-It's All About Chance (2 Mb PDF)
The regression analysis will include flood-frequency estimates generated for 488 USGS streamgages: 341 rural; 32 small, rural; and 115 urban. The flood-frequency data for the rural streamgages will be taken from the previously published Southeastern rural study (Feaster and others, 2009). The flood-frequency estimates for the remaining streamgages will be completed by using a modified version of the methods described in Bulletin 17B of the Hydrology Subcommittee of the Interagency Advisory Committee on Water Data (1982) by including the expected moments algorithm, which allows for a more generalized approach to representing observed annual peak-flow information by using an interval range as compared to the conventional method of using point data, and a generalized Grubbs-Becks test, which allows for the detection of multiple potentially influential low outliers. The regional-regression analysis will provide predictive equations that can be used to estimate the 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent annual exceedance probability (AEP) flows at urban and small, rural ungaged locations in the Southeast..
Prior to the development of regression equations, basin characteristics for the urban station watersheds will be updated using GIS methods. Afterwards, statistical techniques will be used to develop regression equations that can be used to estimate peak flows at ungaged urban sites. Similar to the rural flood-frequency investigation (Feaster and others, 2009), a combination of ordinary least squares (OLS) and generalized least squares (GLS) regression techniques will be used to develop the equations. The OLS techniques will be used to select the explanatory variables to be used in the final equations and to determine the regionalization scheme for the states. The GLS techniques will be used to compute the final coefficients and to measure the accuracy of the regression equations. Generalized least squares regression equations have been determined to be more accurate than OLS regression equations when streamflow data at gaging stations are of different and widely varying lengths (Stedinger and Tasker, 1985).
Below are partners associated with this project.