Flooding is a major natural hazard that has significant societal, economic, hydrological, and ecological consequences. Prediction of floods is necessary for flood mitigation. To improve flood frequency estimation, this study provides insights on the connections between flood frequency and the annual water balance. Researchers, led by DOE scientists at Pacific Northwest National Laboratory, performed a comparative study using data from several hundred catchments across the continental United States. The research expressed mean annual water balance in terms of two similarity measures: (i) the climatic aridity index, AI, which is a measure of the competition between energy and water availability and (ii) the base flow index, BFI, which is a measure of total runoff partitioning into surface and subsurface components at the annual time scale. Their results showed that the aridity index, AI, has a first-order control on the shape of the flood frequency curve in terms of the mean and coefficient of variation (Cv) of the annual maximum floods. While the mean annual (specific) flood discharge decreases with increasing aridity, Cv increases with increasing aridity. On the other hand, the BFI was found to exert a second-order control on the flood frequency curve. Higher BFI, meaning higher contributions of subsurface flow to total streamflow, leads to a decrease of the mean annual (specific) flood discharge, and vice versa. By attributing regional variations of the flood frequency curve to AI and BFI, this study provided the basis to delineate hydrologically homogeneous regions using the two indices for flood frequency regionalization, which may help improve flood estimation and prediction.