Wu et al. (2026) A two-level attribution method for water resource changes based on water budget balance and distributed simulation

Identification

• Journal: Journal of Hydrology
• Year: 2026
• Date: 2026-03-05
• Authors: Qingsong Wu, Hao Wei, Xing Yuan, Lu Lu, Shengqi Jian, Jiawei Li
• DOI: 10.1016/j.jhydrol.2026.135238

Research Groups

• School of Water Conservancy and Transportation, Zhengzhou University, Zhengzhou 450001, China
• Yellow River Water Resources Protection Institute, Yellow River Conservancy Commission, Zhengzhou 450004, China
• Yellow River Institute of Hydrology and Water Resources, Bureau of Hydrology, Yellow River Conservancy Commission, Zhengzhou 450004, China
• School of Civil Engineering, Zhengzhou University, Zhengzhou 450001, China
• Yellow River Institute of Hydraulic Research, Yellow River Conservancy Commission, Zhengzhou 450003, China
• Henan Key Laboratory of YB Ecological Protection and Restoration, Yellow River Institute of Hydraulic Research, YRCC, Zhengzhou 450003, China

Short Summary

This study develops and applies a novel two-level attribution method for water resource changes, integrating water balance principles and a distributed human-water relationship model. The method effectively clarifies the driving mechanisms of water resource changes across scales, revealing that climatic factors dominated runoff changes in the Qin River Basin (2001–2022), while human activities had complex effects on natural and actual runoff.

Objective

• To develop and apply a two-level attribution method for water resource changes, integrating water balance principles and a distributed human-water relationship model, to quantify the driving contributions of climate change and human activities to natural runoff, and various hydrological components to actual runoff.

Study Configuration

• Spatial Scale: Qin River Basin in China (entire basin and basin divisions).
• Temporal Scale: Multi-year average, annual, and monthly scales, covering the period 2001–2022, with specific comparisons between 2001–2010 and 2011–2020.

Methodology and Data

• Models used:
  • Constructed water budget balance equation.
  • Constructed distributed human-water relationship model covering the entire “input-transformation-consumption-output” chain.
  • Two-level attribution system established by coupling the balance equation, distributed model, control variable method, and contribution rate quantification.
• Data sources: Multi-source information (specific types not detailed in the provided text).

Main Results

• The developed two-level attribution method effectively integrates multi-source information, clarifying the driving mechanisms of water resource changes with strong effectiveness and applicability across scales.
• Runoff changes in the Qin River Basin during 2001–2022 were primarily dominated by climatic factors.
• Human activities promoted an increase in natural runoff but led to a reduction in actual runoff.
• Comparing the periods 2001–2010 and 2011–2020, the basin's natural runoff decreased by 0.982 × 10^8 m^3, with climate change contributing -118.0% and human activities contributing 18.0%.
• Actual runoff decreased by 0.508 × 10^8 m^3 due to the combined effects of:
  • Reduced precipitation: -47.3%
  • Decreased natural evapotranspiration: 276.4%
  • Increased human water consumption: -173.5%
  • Increased external transferred water: -1.1%
  • Increased water storage: -154.5%

Contributions

• The primary novelty lies in establishing a hierarchical framework that distinctly attributes drivers to both natural and actual runoff, offering a finer attribution resolution compared to conventional methods.

Funding

• Not specified in the provided text.

Citation

@article{Wu2026twolevel,
  author = {Wu, Qingsong and Wei, Hao and Yuan, Xing and Lu, Lu and Jian, Shengqi and Li, Jiawei},
  title = {A two-level attribution method for water resource changes based on water budget balance and distributed simulation},
  journal = {Journal of Hydrology},
  year = {2026},
  doi = {10.1016/j.jhydrol.2026.135238},
  url = {https://doi.org/10.1016/j.jhydrol.2026.135238}
}