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Streamflow is a very important component of the hydrological cycle, and variation in the streamflow can be an indication of hydrological disaster. Thus, the accurate quantification of streamflow variation is a core concern in water resources engineering. In this study, we evaluated the factors influencing streamflow and decomposed their effects in three large rivers: the Buk Han River (BHR), the Nam Han River (NHR), and the Lower Han River (LHB). The Pettit test was used to investigate breakpoints in conjunction with the climate elasticity approach and decomposition framework to quantify and decompose the effects of climate variability and anthropogenic activity. The abrupt breakpoints in the streamflow and precipitation data were detected in 1997 and 1995. Considering these breakpoints, we divided the time series into two periods: the baseline period and the post-baseline period. Climate elasticity approaches were used to quantify the effects of climate variability and anthropogenic activity during the baseline period, post-baseline period, and future periods (2031–2060 and 2071–2100) under the Representative Concentration Pathways’ 4.5 and 8.5 scenarios. The results revealed that climate variability was the leading cause of alteration in the streamflow in the BHR and NHR, accounting for 76.52% to 80.51% of the total change, respectively. Meanwhile, the LHR remained more sensitive to anthropogenic activity, which accounted for 56.42% of the total variation in streamflow. Future climate change also showed an increase in precipitation and temperature in both scenarios, especially during the far-future period (2071–2100). This variation in the climatic factor was shown to affect the future streamflow by 22.14% to 27.32%. These findings can play a very important role in future planning for large river basins, considering the impacts of increasing anthropogenic activity and climate change to reduce the risks of hydrological hazards.

Investigation of the Effects of Climate Variability, Anthropogenic Activities, and Climate Change on Streamflow Using Multi-Model Ensembles