Preprints
https://doi.org/10.5194/hess-2024-75
https://doi.org/10.5194/hess-2024-75
13 May 2024
 | 13 May 2024
Status: a revised version of this preprint was accepted for the journal HESS and is expected to appear here in due course.

Integration of the Vegetation Phenology Module Improves Ecohydrological Simulation by the SWAT-Carbon Model

Mingwei Li, Shouzhi Chen, Fanghua Hao, Nan Wang, Zhaofei Wu, Yue Xu, Jing Zhang, Yongqiang Zhang, and Yongshuo H. Fu

Abstract. Vegetation phenology and hydrological cycles are closely interacted from leaf and species levels to watershed and global scales. As one of the most sensitive biological indicators of climate change, plant phenology is essential to be simulated accurately in hydrological models. Despite the Soil and Water Assessment Tool (SWAT) has been widely used for estimating hydrological cycles, its lack of integration with the phenology module has led to substantial uncertainties. In this study, we developed a process-based vegetation phenology module and coupled it with the SWAT-Carbon model to investigate the effects of vegetation dynamics on runoff in the upper reaches of Jinsha River watershed in China. The modified SWAT-Carbon model showed reasonable performance in phenology simulation, with root mean square error (RMSE) of 9.89 days for the start-of-season (SOS) and 7.51 days for the end-of-season (EOS). Simulations of both vegetation dynamics and runoff were also substantially improved compared to the original model. Specifically, the simulation of leaf area index significantly improved with the coefficient of determination (R2) increased by 0.62, the Nash–Sutcliffe efficiency (NSE) increased by 2.45, and the absolute percent bias (PBIAS) decreased by 69.0 % on average. Additionally, daily runoff simulation also showed notably improvement, particularly noticeable in June and October, with R2 rising by 0.22 and NSE rising by 0.43 on average. Our findings highlight the importance of integrating vegetation phenology into hydrological models to enhance modeling performance.

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The shifts in vegetation phenology under climate change have significantly influenced...
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