Using integrated modelling to understand seasonal vegetation dynamics and its relationship to runoff generation

Vegetation dynamics and hydrological processes are major components of terrestrial ecosystems, and they interact strongly with each other. Studies of hydrological responses to vegetation dynamics are usually conducted on a long-term scale, whereas the hydrological responses within a single year have rarely been studied. In the present study, Poyang Lake runoff (PYL-R) model, a new hydrological model coupled with leaf area index (LAI) remote sensing products, was established and applied to simulate the runoff process in the Poyang Lake Watershed. The simulation results obtained in three sub-watersheds of the Poyang Lake Watershed (Ganjiang Watershed, Xinjiang Watershed, and Fuhe Watershed) agreed well with the observations (Nash efficiency coefficient values and R values exceeded 0.6 and 0.9, respectively). The PYL-R experiment (PYL-R-E) model was designed as a contrast model without considering the impact of LAI. The simulated monthly runoff results obtained using the PYL-R and PYL-R-E models were compared, and the within-year changes in the differences between the two results were analysed to evaluate and quantify the impact of vegetation dynamic on runoff. From January to July, when LAI values increased by around 2.6 m² m⁻², monthly runoff depth differences between PYL-R and PYL-R-E results increased by 35.25, 27.98, and 29.14 mm in the Ganjiang, Xinjiang, and Fuhe watersheds, respectively. Dense vegetation caused high interception and evapotranspiration during summer, which largely reduced runoff. By contrast, during winter, the effect of vegetation was weaker on runoff process whereas the impacts of other factors (e.g., precipitation) were higher. The sensitivity of monthly runoff to vegetation dynamics varied greatly throughout the whole year. In particular, during August and September, the LAI-caused runoff changes were very high, accounting for 28–42% of monthly runoff in the sub-watersheds. Our findings clarify the effects of changes in vegetation on hydrological processes over short time scales, thereby providing insights into the effects of scale on eco-hydrological processes.