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Identification of the Non-stationarity of Floods: Changing Patterns, Causes, and Implications

Author

Listed:
  • Saiyan Liu

    (Xi’an University of Technology)

  • Shengzhi Huang

    (Xi’an University of Technology)

  • Yangyang Xie

    (Research Institute of Modern Rural Water Conservancy)

  • Hao Wang

    (China Institute of Water Resources and Hydropower Research)

  • Guoyong Leng

    (University of Oxford)

  • Qiang Huang

    (Xi’an University of Technology)

  • Xiaoting Wei

    (Xi’an University of Technology)

  • Lu Wang

    (Xi’an University of Technology)

Abstract

The assumption of stationarity in the flood time series is the basis for flood design and forecasting. Therefore, identification of the non-stationarity of flood series and the underlying causes is necessary for flood risk and water resources management. The Wei River Basin (WRB) of China was selected as the case study. Nonstationary flood behavior was examined comprehensively in terms of trends and the mean and variance change point. Then, the implications of the nonstationary flood series were explored. Furthermore, the impacts of antecedent precipitation, El Niño Southern Oscillation/Pacific Decadal Oscillation and vegetation coverage on floods were investigated. The results indicated following: (1) There is a non-significant delay in the timing of the annual maximum flood peak and seasonal floods across the basin; (2) the assumption of stationarity in the flood series is invalid, with significant downward trends and change points identified; (3) bias arising from the variance change point is much more significant than that of the mean change point in estimating floods; and (4) changing climate and human activities are jointly responsible for nonstationary floods in the WRB. These findings provide new insights into nonstationary flood behavior by emphasizing the importance of identifying the potential variance change points in the flood series, which is important for flood mitigation and water resources management.

Suggested Citation

  • Saiyan Liu & Shengzhi Huang & Yangyang Xie & Hao Wang & Guoyong Leng & Qiang Huang & Xiaoting Wei & Lu Wang, 2019. "Identification of the Non-stationarity of Floods: Changing Patterns, Causes, and Implications," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(3), pages 939-953, February.
    • Handle: RePEc:spr:waterr:v:33:y:2019:i:3:d:10.1007_s11269-018-2150-y
    DOI: 10.1007/s11269-018-2150-y
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    References listed on IDEAS

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    1. Konrad Nosek, 2010. "Schwarz information criterion based tests for a change-point in regression models," Statistical Papers, Springer, vol. 51(4), pages 915-929, December.
    2. Shengzhi Huang & Jianxia Chang & Qiang Huang & Yutong Chen, 2014. "Spatio-temporal Changes and Frequency Analysis of Drought in the Wei River Basin, China," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(10), pages 3095-3110, August.
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    Cited by:

    1. Leandro José Isensee & Adilson Pinheiro & Daniel Henrique Marco Detzel, 2021. "Dam Hydrological Risk and the Design Flood Under Non-stationary Conditions," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(5), pages 1499-1512, March.
    2. Chi Zhang & Xuezhi Gu & Lei Ye & Qian Xin & Xiaoyang Li & Hairong Zhang, 2023. "Climate Informed Non-stationary Modeling of Extreme Precipitation in China," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(9), pages 3319-3341, July.
    3. Ming, Bo & Liu, Pan & Guo, Shenglian & Cheng, Lei & Zhang, Jingwen, 2019. "Hydropower reservoir reoperation to adapt to large-scale photovoltaic power generation," Energy, Elsevier, vol. 179(C), pages 268-279.
    4. Huang, Shengzhi & Wang, Lu & Wang, Hao & Huang, Qiang & Leng, Guoyong & Fang, Wei & Zhang, Ying, 2019. "Spatio-temporal characteristics of drought structure across China using an integrated drought index," Agricultural Water Management, Elsevier, vol. 218(C), pages 182-192.

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