A fundamental tradeoff exists in watershed modeling between a model's flexibility for representing watersheds with different characteristics versus its potential for overparameterization. This study uses global sensitivity analysis to investigate how a commonly used intermediate-complexity model, the Sacramento Soil Moisture Accounting Model (SAC-SMA), represents a wide range of watersheds with diverse physical and hydroclimatic characteristics. The analysis aims to establish a detailed understanding of model behavior across watersheds and time periods with the ultimate objective to guide model calibration and evaluation studies. Sobol's sensitivity analysis is used to evaluate the SAC-SMA in 12 Model Parameter Estimation Experiment (MOPEX) watersheds in the US. The watersheds span a wide hydroclimatic gradient from arid to humid systems. Four evaluation metrics reflecting base flows, midrange flows, peak flows, and long-term water balance were used to comprehensively characterize trends in sensitivity and model behavior. Results show significant variation in parameter sensitivities that are correlated with the hydroclimatic characteristics of the watersheds and time periods analyzed. The sensitivity patterns are consistent with the expected dominant processes and demonstrate the need for moderate model complexity to represent different hydroclimatic regimes. The analysis reveals that the primary model controls for some aspects of the simulated hydrograph are different from those typically assumed for the SAC-SMA. Results also show that between 6 and 10 parameters are regularly identifiable from daily hydrologic data, which is about twice the range that is often assumed (i. e., 3 to 5). Synthesized results provide comprehensive SAC-SMA calibration guidance, demonstrate the flexibility of the model for representing multiple hydroclimatic regimes, and highlight the great difficulty in generalizing model behavior across watersheds.