Three recording rain gages in a 9.7‐square‐mile basin in southern California were used with a deterministic rainfall‐runoff model to simulate flood hydrographs and peaks and to assess the effects of data errors on simulation results. Bias in the estimation of effective basin rainfall seemed to result in curve fitting parameter adjustments which compensated for the bias. The combined effects for a storm of both difference in the time distribution of rainfall at different points and spatial variability of rainfall volume over the basin limit the possible accuracy of simulation results. The use of a single rain gage on a basin with this hydrology can at best be expected to predict peak discharge with a standard error of estimate on the order of 20%.

A parametric rainfall~runoff simulation model is used with dat~ from a point rainfall gage and data on daily potential evapotranspiration to predict flood volume and peak rates of runoff for small drainage areas. The model is based on bulkparameter approximations to the physical laws governing infiltration, soil-moisture accretion and depletion, and surface streamflow. Three case studies are presented in which an objective fitting method is used for determining optimal best-fit sets of parameter values for the data available for use in predicting flood peaks. Errors of prediction result both from errors in rainfall input and from lack of model equivalence to the physical prototype. These two sources of error seem to be of the same order of magnitude for a model of the level of simplicity of that present~d. Major gains in accuracy of simulation will require improvements in both data and model. The limit of accuracy of prediction of flood peaks by simulation with a bulk-parameter model using data obtained from a single rain gage seems to be on the order of 25 percent.