A multistate approach was used to update methods for estimating the magnitude and frequency of floods in rural, ungaged basins in Georgia, South Carolina, and North Carolina that are not substantially affected by regulation, tidal fluctuations, or urban development. Annual peak-flow data through September 2006 were analyzed for 943 streamgaging stations having 10 or more years of data on rural streams in Georgia, South Carolina, North Carolina, and adjacent parts of Alabama, Florida, Tennessee, and Virginia. Flood-frequency estimates were computed for the 943 stations by fitting the logarithms of annual peak flows for each station to a Pearson Type III distribution. As part of the computation of flood-frequency estimates for these streamgaging stations, a new value for the generalized-skew coefficient was developed by using a Bayesian generalized least-squares regression model. Additionally, basin characteristics for the streamgaging stations were computed by using a geographical information system and automated computer algorithms.
Regional regression analysis, using generalized least-squares regression, was used to develop a set of predictive equations for estimating the 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent chance exceedance flows for rural ungaged basins in Georgia, South Carolina, and North Carolina. Flood-frequency estimates and basin characteristics for 828 stream-gaging stations were combined to form the final database used in the regional regression analysis. Five hydrologic regions were developed for Georgia, South Carolina, and North Carolina. The final predictive equations are all functions of drainage area and percentage of the drainage basin within each hydrologic region. Average standard errors of prediction for these regression equations range from 34.5 to 47.7 percent.