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Attribution Analysis of Runoff Variation in Kuye River Basin Based on Three Budyko Methods

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  • Jiahao Zheng

    (Shaanxi Key Laboratory of Earth Surface System and Environmental Carrying Capacity, College of Urban and Environmental Science, Northwest University, Xi’an 710127, China
    Environmental Engineering, College of Urban and Environmental Science, Northwest University, Xi’an 710127, China)

  • Yi He

    (Environmental Engineering, College of Urban and Environmental Science, Northwest University, Xi’an 710127, China)

  • Xiaohui Jiang

    (Shaanxi Key Laboratory of Earth Surface System and Environmental Carrying Capacity, College of Urban and Environmental Science, Northwest University, Xi’an 710127, China
    Environmental Engineering, College of Urban and Environmental Science, Northwest University, Xi’an 710127, China)

  • Tong Nie

    (Shaanxi Key Laboratory of Earth Surface System and Environmental Carrying Capacity, College of Urban and Environmental Science, Northwest University, Xi’an 710127, China
    Environmental Engineering, College of Urban and Environmental Science, Northwest University, Xi’an 710127, China)

  • Yuxin Lei

    (Environmental Engineering, College of Urban and Environmental Science, Northwest University, Xi’an 710127, China)

Abstract

The Loess Plateau is the main soil erosion area within the Yellow River Basin. Quantifying the contribution rate of climate change and human activities to runoff change can provide support for water resources management in the Yellow River Basin. Kuye River Basin is located in the Loess Plateau. As a first-class tributary of the Yellow River, it was selected as the study area. Runoff from the Kuye River Basin has decreased significantly since the 1990s owing to climate change and anthropogenic coal mining. The main objective of this study was to quantify the contribution and sensitivity of climate change and anthropogenic activities to runoff changes using three popular Budyko and elasticity coefficient methods, as well as to compare the similarities and differences among the three methods. The results show that: (1) Through four mutation point test methods, the change point of runoff in the study period of Kuye River Basin is 1997. (2) The elasticity coefficients calculated by the three Budyko methods showed that during the study period, the runoff was more sensitive to changes in precipitation, followed by the catchment surface characteristic parameters and the potential evapotranspiration. (3) All three Budyko methods can yield reasonable contributions of climate change and human activity to runoff changes. The three methods together indicate that the influence of the catchment surface characteristic parameters is the most important factor for the runoff variation in the Kuye River.

Suggested Citation

  • Jiahao Zheng & Yi He & Xiaohui Jiang & Tong Nie & Yuxin Lei, 2021. "Attribution Analysis of Runoff Variation in Kuye River Basin Based on Three Budyko Methods," Land, MDPI, vol. 10(10), pages 1-18, October.
    • Handle: RePEc:gam:jlands:v:10:y:2021:i:10:p:1061-:d:652134
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    References listed on IDEAS

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    1. Guangxing Ji & Huiyun Song & Hejie Wei & Leying Wu, 2021. "Attribution Analysis of Climate and Anthropic Factors on Runoff and Vegetation Changes in the Source Area of the Yangtze River from 1982 to 2016," Land, MDPI, vol. 10(6), pages 1-13, June.
    2. A. N. Pettitt, 1979. "A Non‐Parametric Approach to the Change‐Point Problem," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 28(2), pages 126-135, June.
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    Cited by:

    1. Wenqing Li & Guohua He & Yong Zhao & Zhao Liu & Fan He & Haibin Wang, 2023. "An Analysis of Runoff Variation in a Small Basin in the Loess Plateau: Identifying the Variation Causes and Implications for Sustainable Water Management," Sustainability, MDPI, vol. 15(12), pages 1-22, June.
    2. Mengru Wei & Zhe Yuan & Jijun Xu & Mengqi Shi & Xin Wen, 2022. "Attribution Assessment and Prediction of Runoff Change in the Han River Basin, China," IJERPH, MDPI, vol. 19(4), pages 1-22, February.

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