Technical Abstract: Water quality regulation and litigation have elevated the awareness and need for quantifying water quality and source contributions in watersheds across the US. In the present study, the regression method, which is typically applied to perennial rivers to estimate constituent loads, was evaluated on three small watersheds in Texas. Specifically, regression methodology was used with four low-frequency sampling strategies - random, rise and fall, peak, and single stage - to estimate nutrient and sediment loads. Estimated loads were compared to measured loads determined in 2001-2004 with an autosampler and high-frequency sampling strategies. Although annual rainfall and runoff volumes were relatively consistent within watersheds during the study period, annual nutrient and sediment concentrations and loads varied considerably for the cultivated and mixed watersheds but not for the pasture watershed. Correlations between constituent concentrations and mean daily flow rate were poor and not significant for all watersheds, which is different than typically observed in large rivers. The regression method was quite variable in its ability to accurately estimate annual nutrient loads from the study watersheds; however, constituent load estimates were much more accurate for the combined 3-yr period. Thus for small watersheds, regression-based annual load esimates should be used with caution, whereas long-term estimates can be much more accurate when multiple years of concentration data are available. The predictive ability of the regression method was similar for all of the low-frequency sampling strategies studied; therefore, single stage or random strategies are recommended for low-frequency storm sampling on small watersheds because of their simplicity.