Study region: This study focuses on Upper Yellow River Basin (UYRB), located at the junction of the Qinghai Tibet Plateau and the Loess Plateau in China.
Study focus: This study developed the MEP-PML evapotranspiration model and a water vapor transport-box model, both grounded in calculus-based formulations. These models were then integrated into a comprehensive atmospheric water cycle model. We analyzed spatiotemporal changes in the atmospheric water cycle over the Upper Yellow River Basin (UYRB) under the combined effects of climate change and human activities. Subsequently, a detrending analysis approach was applied to simulate the atmospheric water cycle under a counterfactual scenario excluding the temperature component of climate change. To isolate anthropogenic influences, we further simulated the atmospheric water cycle in the absence of human activities by explicitly incorporating vegetation change, as a proxy for land surface dynamics, into the model. By comparing observational data against these scenario-based simulations, we quantified the spatiotemporal evolution of the atmospheric water cycle.
New hydrological insight for the region: The simulation results indicate that the temperature component of climate change has induced a continuous decline in evapotranspiration (8.57 f 7.14 mm), precipitation (5.24 f 3.26 mm), and atmospheric water vapor outflow (0.15 f 0.09 x 106 kg s-1) across the UYRB over the period 1982-2021. In contrast, vegetation changes driven by human activities have led to an increase in evapotranspiration (0.37 f 0.33 mm), precipitation (0.23 f 0.20 mm), and atmospheric water vapor outflow (near zero). The influence of temperature component of climate change on the atmospheric water cycle remained consistent over the period 1982-2021, whereas vegetation changes driven by human activities displayed pronounced spatiotemporal heterogeneity. This study advances our understanding of quantifying the impacts of climate change and human activities on the hydrological cycle, thereby supporting scientifically informed decision-making for future water resource management.