The Soil and Water Assessment Tool (SWAT) model has been widely applied for simulating the water cycle and quantifying the influence of climate change and anthropogenic activities on hydrological processes. A major uncertainty of SWAT stems from poor representation of vegetation dynamics due to the use of a simplistic vegetation growth and development module. Using long-term remote sensing-based phenological data, we improved the SWAT model’s vegetation module by adding a dynamic growth start date and the dynamic heat requirement for vegetation growth rather than using constant values. We verified the new SWAT model in the Han River basin, China, and found its performance was much improved in comparison with that of the original SWAT model. Specifically, the accuracy of the leaf area index (LAI) simulation improved notably (coefficient of determination (R2) increased by 0.193, Nash–Sutcliffe Efficiency (NSE) increased by 0.846, and percent bias decreased by 42.18%), and that of runoff simulation improved modestly (R2 increased by 0.05 and NSE was similar). Additionally, we found that the original SWAT model substantially underestimated evapotranspiration (Penman–Monteith method) in comparison with the new SWAT model (65.09 mm (or 22.17%) for forests, 92.27 mm (or 32%) for orchards, and 96.16 mm (or 36.4 %) for farmland), primarily due to the inaccurate representation of LAI dynamics. Our results suggest that accurate representation of phenological dates in the vegetation growth module is important for improving the SWAT model performance in terms of estimating terrestrial water and energy balance.

As regional heterogeneity on the Qinghai Tibetan Plateau (QTP), the “greening rate” between alpine steppe in the west and alpine meadow ecosystems in the east is difference during the past several decades. To investigate the difference, the net photosynthetic rate (An) and the supply (mesophyll conductance ( g m), stomatal conductance ( g s)) and demand (the maximum rates of Rubisco carboxylase activity ( V cmax) and photosynthetic electron transport ( J max)) for CO 2 of three plants functional types (PFTs) were measured. Other functional traits and influencing factors were compared among ecosystems along the altitudinal gradients of QTP. The An of the PFTs was simulated under potential future conditions. At high altitudes, grass was found to maintain a relatively stable An by decreasing V cmax, J max, and g s, while slightly increasing g m, compared with that at a low altitude. The An of sedge and shrubs increased with rising V cmax, J max and g s and g m values, resulting in a large increment in the An at low altitudes. Grass seemed to be less sensitive to the environment by reducing the supply of and holding onto CO 2, while sedge and shrub increased both. Grass and sedge should be divided into two PFTs rather than remaining as one based on their opposite physiological and morphological functions in response to climate change. The ecosystem at 3600 m was transitional. C a was likely to be a more dominant factor than T a in affecting the An of grass. The order of rising An in PFTs was shrub > sedge > grass and the An of alpine meadow was found to increase more under the two future climate scenarios.