Integration of the vegetation phenology module improves ecohydrological simulation by the SWAT-Carbon model

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

doi:https://doi.org/10.5194/hess-29-2081-2025

Articles | Volume 29, issue 8

https://doi.org/10.5194/hess-29-2081-2025

© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/hess-29-2081-2025

© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 29, issue 8

Research article

|

25 Apr 2025

Research article |

| 25 Apr 2025

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

Supplement

https://doi.org/10.5194/hess-29-2081-2025-supplement

Data sets

Geospatial Data Cloud site, Computer Network Information Center SRTMDEM 90M https://www.gscloud.cn/sources/details/305?pid=302

China Multiperiod Land Use Remote Sensing Monitoring Dataset (CNLUCC) X. Xu et al. https://doi.org/10.12078/2018070201

Global agro-ecological zones assessment for agriculture (GAEZ 2008) G. Fischer et al. https://www.fao.org/soils-portal/soil-survey/soil-maps-and-databases/harmonized-world-soil-database-v12/en/

China meteorological forcing dataset (1979-2018) K. Yang et al. https://doi.org/10.11888/AtmosphericPhysics.tpe.249369.file

Spatiotemporally consistent global dataset of the GIMMS Normalized Difference Vegetation Index (PKU GIMMS NDVI) from 1982 to 2022 (V1.2) M. Li et al. https://doi.org/10.5281/zenodo.8253971

Global Land Surface Satellite leaf area index GLASS LAI https://www.glass.hku.hk/archive/LAI/AVHRR/

Short summary

Climate-driven shifts in vegetation phenology have a significant impact on hydrological processes. In this study, we integrated a process-based phenology module into the SWAT-Carbon model, which led to a substantial improvement in the simulation of vegetation dynamics and hydrological processes in the Jinsha River watershed. Our findings highlight the critical need to incorporate vegetation phenology into hydrological models to achieve a more accurate representation of ecohydrological processes.