Floods are among some of the most dangerous phenomena people are faced with each year. The current practice of flood forecasting relies on modeling the complex hydrological processes that control the flow of freshwater through a watershed. Past literature has shown however, that these complex processes can be simplified using rainfall-runoff models. These models estimate the relationship between precipitation and runoff generation. Some models emphasize the land-surface interactions, while others focus on the estimation of soil moisture in determining how precipitation flows through a watershed. The soil composition and land cover are not mutually exclusive of each other, and varying combinations of both across different watersheds are linked to the differences in the antecedent conditions necessary to produce floods. The first part of this study focuses on quantifying soil composition and land cover differences in watersheds of the Southeast U.S. region. A principal component analysis (PCA) of watershed attributes from the GAGES-II dataset was used to spread 78 sample watersheds into a 2-D phase space. Ten sample watersheds were chosen to represent the phase space in the second part of this study which was to determine the role of antecedent precipitation in 5-year flow events. Eighty-eight 5-year flow events were identified and the cumulative antecedent precipitation (AP) prior to these events were analyzed using three parameters: storm precipitation (0-3 Day AP), intermediate (4-14 Day AP), and long-term (4-30 Day AP). A principal component regression analysis (PCR) of the 88 events was used to determine the role of antecedent precipitation in the 5-year flow events. Two PCR models consisting of four parameters each were used to analyze differences between the effects of intermediate and long-term precipitation on the magnitude of the 5-year flow events. The parameters used in the PCR were the storm precipitation, antecedent precipitation, and each sample watershed’s position in principal components one (PC1) and two (PC2). The results of the PCR determined that the cumulative antecedent precipitation prior to an event has little effect on the magnitude of these flows. It was determined that the attributes comprising PC1 and PC2, along with the storm precipitation had a stronger effect on the flow magnitude of the events. The hydrological processes associated with the attributes of PC1 and PC2 were used to describe the differences between the watersheds, proving that a PCA can be used to quantitatively differentiate watersheds in the Southeast U.S.