EGU26-389, updated on 13 Mar 2026
https://doi.org/10.5194/egusphere-egu26-389
EGU General Assembly 2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
Poster | Thursday, 07 May, 16:15–18:00 (CEST), Display time Thursday, 07 May, 14:00–18:00
 
Hall A, A.26
Spatiotemporal attribution of runoff changes in the upper Yangtze River Basin using the SWAT+ model
Yu Han1, Ping-an Zhong1, Yujie Wang2, Xinyuan Qian1, Mengxue Ben1, and Zixin Song1
Yu Han et al.
  • 1College of Hydrology and Water Resources, Hohai University, Nanjing, China
  • 2Xinjiang Uygur Autonomous Region Rivers and Lakes Protection Center, Urumqi, China

Runoff in the UYRB has changed due to the combined effects of climate change and human activities. However, comprehensive spatiotemporal attribution studies are still lacking. This study analyzes and attributes runoff changes across different temporal scales (annual, drawdown, and refill periods) and spatial scales (entire basin and five zones). The effects of climate change and land use/land cover change (LUCC) on runoff are quantified using the SWAT+ model. The main driving factors are identified by comparing their contributions with observed runoff changes.

From the baseline period (1961-2000) to the impact period (2001-2023), annual runoff in the UYRB decreased by 34.60 billion m³/yr, while runoff increased by 21.53 billion m³/yr during the drawdown period and decreased by 40.29 billion m³/yr during the refill period. These trends were generally consistent across all zones. Climate change was the dominant factor driving annual runoff changes (77.69%), followed by increased water consumption (13.41%) and LUCC (5.85%). Climate change reduced annual runoff in most zones due to the combined effect of reduced precipitation and increased potential evapotranspiration. However, during the drawdown and refill periods, reservoir operation emerged as another significant driving factor influencing runoff changes. This study provides valuable insights into water resource management in a changing environment.

How to cite: Han, Y., Zhong, P., Wang, Y., Qian, X., Ben, M., and Song, Z.: Spatiotemporal attribution of runoff changes in the upper Yangtze River Basin using the SWAT+ model, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-389, https://doi.org/10.5194/egusphere-egu26-389, 2026.