Reliable estimates of the magnitude and frequency

of floods are essential for the design of transportation and

water-conveyance structures, flood-insurance studies, and

flood-plain management. Such estimates are particularly

important in densely populated urban areas. In order

to increase the number of streamflow-gaging stations

(streamgages) available for analysis, expand the geographical

coverage that would allow for application of regional

regression equations across State boundaries, and build

on a previous flood-frequency investigation of rural U.S.

Geological Survey streamgages in the Southeast United

States, a multistate approach was used 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, South Carolina,

and North Carolina. The at-site flood-frequency analysis

of annual peak-flow data for urban and small, rural

streams (through September 30, 2011) included 116 urban

streamgages and 32 small, rural streamgages, defined in

this report as basins draining less than 1 square mile. The

regional regression analysis included annual peak-flow

data from an additional 338 rural streamgages previously

included in U.S. Geological Survey flood-frequency reports

and 2 additional rural streamgages in North Carolina that

were not included in the previous Southeast rural floodfrequency

investigation for a total of 488 streamgages

included in the urban and small, rural regression analysis.

The at-site flood-frequency analyses for the urban and small,

rural streamgages included the expected moments algorithm,

which is a modification of the Bulletin 17B log-Pearson

type III method for fitting the statistical distribution to the

logarithms of the annual peak flows. Where applicable,

the flood-frequency analysis also included low-outlier and

historic information. Additionally, the application of a

generalized Grubbs-Becks test allowed for the detection of

multiple potentially influential low outliers.

Streamgage basin characteristics were determined

using geographical information system techniques. Initial ordinary least squares regression simulations reduced the

number of basin characteristics on the basis of such factors

as statistical significance, coefficient of determination,

Mallow’s Cp statistic, and ease of measurement of the

explanatory variable. Application of generalized least

squares regression techniques produced final predictive

(regression) equations for estimating the 50-, 20-, 10-, 4-,

2-, 1-, 0.5-, and 0.2-percent annual exceedance probability

flows for urban and small, rural ungaged basins for three

hydrologic regions (HR1, Piedmont–Ridge and Valley; HR3,

Sand Hills; and HR4, Coastal Plain), which previously had

been defined from exploratory regression analysis in the

Southeast rural flood-frequency investigation. Because of the

limited availability of urban streamgages in the Coastal Plain

of Georgia, South Carolina, and North Carolina, additional

urban streamgages in Florida and New Jersey were used in

the regression analysis for this region. Including the urban

streamgages in New Jersey allowed for the expansion of the

applicability of the predictive equations in the Coastal Plain

from 3.5 to 53.5 square miles. Average standard error of

prediction for the predictive equations, which is a measure

of the average accuracy of the regression equations when

predicting flood estimates for ungaged sites, range from

25.0 percent for the 10-percent annual exceedance probability

regression equation for the Piedmont–Ridge and Valley

region to 73.3 percent for the 0.2-percent annual exceedance

probability regression equation for the Sand Hills region.