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Attribution of Streamflow Changes Considering Spatial Contributions and Driver Interactions Based on Hydrological Modeling

Author

Listed:
  • Yinshan Xu

    (Bureau of Hydrology, Changjiang Water Resources Commission)

  • Yubin Chen

    (Bureau of Hydrology, Changjiang Water Resources Commission)

  • Yufeng Ren

    (China Yangtze Power Co., Ltd)

  • Zhengyang Tang

    (China Yangtze Power Co., Ltd)

  • Xu Yang

    (China Yangtze Power Co., Ltd)

  • Yu Zhang

    (Nanjing Hydraulic Research Institute)

Abstract

Streamflow is one of the most important elements of a water resources system and is key to understanding the conditions of water resources at different scales. Therefore, clarifying streamflow changes and the causes is important for water resources management under changing environments. The variability of streamflow and drivers is very complex in the spatial dimension, which is particularly evident in large scale regions. This study aims to develop a new attribution analysis method based on hydrological modeling that considers spatial contributions and driver interactions. A large-scale Soil and Water Assessment Tool (SWAT) model is established. The calibrated SWAT model provides detailed, high-resolution descriptions of small-scale processes that are numerically integrated to larger scales. Based on the distributed simulation under different scenarios, attribution analysis can be conducted at scales as small as the sub-basins can be divided. Results reveal that: (1) Streamflow of the entire Upper Yangtze River Basin was significantly reduced by -8.9 km3 per ten years during the study period. Streamflow changes exhibited different characteristics in space. This emphasizes the necessity of introducing spatial contributions into attribution analysis. (2) At the basin scale, the decrease in precipitation and wind speed, the increase in maximum temperature, and land use/ cover change (LUCC) all contribute to the decrease in streamflow. While the increase in minimum temperature and decrease in relative humidity have the effect of increasing streamflow. At the basin scale or smaller sub-basin scale, there are significant differences in the contributions of driving factors to streamflow changes. This has practical implications for water resources management in terms of refining attribution analysis and adopting targeted countermeasures. Key Points • Develops a new multi-routes-based attribution analysis method using large-scale hydrological modeling. • Introduces spatial contributions into attribution analysis. • Conducts a case study based on the proposed method using real-world data.

Suggested Citation

  • Yinshan Xu & Yubin Chen & Yufeng Ren & Zhengyang Tang & Xu Yang & Yu Zhang, 2023. "Attribution of Streamflow Changes Considering Spatial Contributions and Driver Interactions Based on Hydrological Modeling," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(5), pages 1859-1877, March.
    • Handle: RePEc:spr:waterr:v:37:y:2023:i:5:d:10.1007_s11269-023-03459-3
    DOI: 10.1007/s11269-023-03459-3
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    References listed on IDEAS

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    1. Gajanan Ramteke & R. Singh & C. Chatterjee, 2020. "Assessing Impacts of Conservation Measures on Watershed Hydrology Using MIKE SHE Model in the Face of Climate Change," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(13), pages 4233-4252, October.
    2. Xinyu Wan & Lijuan Hua & Shutan Yang & Hoshin V. Gupta & Ping’an Zhong, 2018. "Evaluating the Impacts of a Large-Scale Multi-Reservoir System on Flooding: Case of the Huai River in China," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(3), pages 1013-1033, February.
    3. Vahid Moosavi & Ayoob Karami & Negin Behnia & Ronny Berndtsson & Christian Massari, 2022. "Linking Hydro-Physical Variables and Landscape Metrics using Advanced Data Mining for Stream-Flow Prediction," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(11), pages 4255-4273, September.
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    1. Erfan Mahmoodi & Mahmood Azari & Mohammad Taghi Dastorani & Aryan Salvati, 2024. "Comparison of Hydrological Modeling, Artificial Neural Networks and Multi-Criteria Decision Making Approaches for Determining Flood Source Areas," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 38(13), pages 5343-5363, October.

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