China leads the world in vegetation greening and accounts for one-fourth of the global net increase in leaf area over the past two decades. However, it remains elusive on the relative importance of vegetation greening and climate change on China’s hydrological cycle due to the lack of observational-based constraints on notorious model uncertainties. Here, we developed a process-based distributed hydrological model that couples a nonlinear runoff generation mechanism with a remotely-sensed evapotranspiration (ET) module. This model could well capture the spatiotemporal patterns of the main hydrological components (runoff, ET, and soil moisture) at grid scale and streamflow at watershed scale during 1982–2012 over the mainland China. We show that the changes in climatic factors (precipitation and potential ET) dominated hydrologic change at the national scale, with climate induced runoff decrease by 7.6 mm year−1 compared to 0.6 mm year−1 caused by vegetation change. Vegetation effect was primarily notable in water-limited regions as a higher correlation between vegetation contribution to runoff change and absolute leaf area index (LAI) trend in water-limited regions (r = 0.52, p < 0.01) than energy-limited regions (r = 0.19, p < 0.01). Our results highlight the significance of region-dependent differential measures for sustainable water resources management and climate change adaptation under a changing climate.