Integrating dynamic vegetation phenology into SWAT improves watershed nitrogen and phosphorus simulations

The Soil and Water Assessment Tool (SWAT) is widely applied in non-point source pollution research, yet its reliance on static parameters to characterize vegetation phenology hinders the capture of dynamic phenological changes, thereby introducing biases into nitrogen and phosphorus (N-P) transport and cycling simulations. To address this gap, this study integrated observed dynamic phenology data into the SWAT model and explored the impact of vegetation dynamics on hydrological and N-P cycling simulations in a typical sub-basin of the Yangtze River. Results show that the modified SWAT outperforms the original model, demonstrating a notable enhancement in simulating the leaf area index (LAI) (NSE >0.66). While runoff simulation accuracy showed a marginal improvement (NSE increased by 0.03), total nitrogen (TN) and total phosphorus (TP) simulation accuracies demonstrated measurable improvements (NSE increased by 0.13 for TN and 0.04 for TP, respectively; PBIAS decreased by 14.4% and 3.33%, respectively). Specifically, the improvement in TN arose from correcting the temporal mismatch between vegetation nitrogen demand and soil availability, thereby reducing overestimation during early and late growth stages. For TP, the refined phenology captured the critical canopy coverage threshold during the wet season, which helped regulate sediment-bound phosphorus transport via enhanced erosion control. Furthermore, the N-P simulation improvements were more pronounced in natural vegetation-dominated areas than at the mixed-use basin outlet (NSE increased by 0.16 for TN and 0.14 for TP). This study underscores that the dynamic representation of phenological information influences N and P transport and cycling processes, demonstrating that this natural regulation is prominent in pristine headwaters but largely masked by intensive downstream human activities.