Simulating streamflow in ungauged catchments remains a challenging task in hydrology and increases the demand for regionalization studies worldwide. Here, we investigate the effect of three modes of parameter transfer, including temporal (transferring across different periods), spatial (transferring between same calibration periods but different sites), and spatiotemporal (transferring across both different periods and sites) on simulating streamflow using HBV conceptual rainfall-runoff model at 576 unregulated catchments throughout Iran (407,000 Km2). Our main conclusions are: (1) temporal mode shows the best performance, with the lowest decline in performance (median decline of 5.8%) as measured using the NSE efficiency metric, (2) difference between spatial and spatiotemporal options was negligible (median decline of 13.7% and 15.1% respectively), (3) all parameters are associated with some uncertainties and those related to runoff and snow components of the model are associated with the highest and lowest uncertainties, respectively, (4) overall, the model performance in arid regions is not as good as humid regions which confirmed that elevation and climate play a major role in parameter estimation in these areas, and (5) aridity and catchment elevation are two major controls on model transferability at regional (climate classes) and local (the whole country) scales. We also show that the superiority of the temporal mode is maintained with: (i) increasing spatial distance between gauged (donor) and ungauged (target) catchments, (ii) increasing time lag (10 years) between calibration and validation, and (iii) gradually increased time lags between calibration and validation. Our study suggest that spatiotemporal parameter transfer can be a reliable option for PUB studies and climate change-related studies, at least in wetter catchments. However, further research is needed to explore the complicated relationship between temporal and spatial aspects of hydrological variability.