This paper illustrates the application of TOPNET, a distributed physically based hydrologic model in different watersheds across US to determine streamflow regime variables which are a significant influencing factor for both in and out –of stream environments. The models are being established so as to be able to predict and examined changes in flow regimes due to climate change. This paper discusses the model parameterization and calibration parts of the work. A 30 m DEM obtained from National elevation dataset was used to delineate streams and sub watersheds. TauDEM (Tarboton 2002) software was used for delineating stream networks and obtaining slope and catchment area. For this application, the TOPNET model used daily precipitation and temperature data from Daymet, which has fine spatial (1km x1km) and temporal resolution (daily). Initial model parameters for each subbasin were estimated from SSURGO soil and National Land Cover (NLCD) data. USGS streamflow data was used as observed for model calibration. The calibration used a multiplier for each parameter which was estimated using a controlled elitist multi objective genetic algorithm. Automation of all input data preparation workflows and calibration of the model make implementation of TOPNET over those watersheds efficient. Visual comparison of time series plots and statistical measures namely, Nash-Sutcliffe efficiency (NS), percent bias (PBIAS) and root mean square error (RMSE) were used to evaluate the model performance. For most of the watersheds, the model performed relatively well and gave a good representation of the flow hydrographs of the watersheds. Stream flow regime variables derived from calibrated flow were nicely comparable to those from observed flow. The promising simulation results obtained in this study reveal the usefulness of the TOPNET model for estimating streamflow regime variables