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The Development of a Nonstationary Standardised Streamflow Index Using Climate and Reservoir Indices as Covariates

Author

Listed:
  • Menghao Wang

    (Hohai University
    Hohai University)

  • Shanhu Jiang

    (Hohai University
    Hohai University)

  • Liliang Ren

    (Hohai University
    Hohai University)

  • Chong-Yu Xu

    (University of Oslo)

  • Linyong Wei

    (Hohai University)

  • Hao Cui

    (Hohai University)

  • Fei Yuan

    (Hohai University)

  • Yi Liu

    (Hohai University)

  • Xiaoli Yang

    (Hohai University)

Abstract

Under current global change, the driving force of evolution of drought has gradually transitioned from a single natural factor to a combination of natural and anthropogenic factors. Therefore, widely used standardised drought indices based on assumption of stationarity are challenged and may not accurately assess characteristics of drought processes. In this study, a nonstationary standardised streamflow index (NSSI) that incorporates climate and reservoir indices as external covariates was developed to access nonstationary hydrological drought. The first step of the proposed approach is to apply methods of trend and change point analysis to assess the nonstationarity of streamflow series to determine type of streamflow regime, that is, the natural and altered regime. Then, different nonstationary models were constructed to calculate the NSSI by selecting climate indices as covariates for streamflow series with natural regime, and climate and reservoir indices as covariate for streamflow series with altered regime. Four stations in the upper reaches of the Huaihe River basin, China, were selected to examine the performance of the proposed NSSI. The results indicated that Dapoling (DPL), Changtaiguan (CTG), and Xixian (XX) stations had natural streamflow regimes, while the Nanwan (NW) station had an altered regime. The global deviances of the optimal nonstationary models were 17 (2.2%), 18 (2.9%), 26 (4.0%), and 22 (3.5%) less than those of stationary models for DPL, CTG, NW, and XX stations, respectively. Especially, for the NW station influenced by reservoir regulations, the frequency of slight drought and moderate drought of NSSI was 12.8% lower than and 13.1% greater than those of SSI, respectively. Overall, the NSSI that incorporates the influence of climate variability and reservoir regulations provided more reliable assessment of hydrological drought than the traditional SSI.

Suggested Citation

  • Menghao Wang & Shanhu Jiang & Liliang Ren & Chong-Yu Xu & Linyong Wei & Hao Cui & Fei Yuan & Yi Liu & Xiaoli Yang, 2022. "The Development of a Nonstationary Standardised Streamflow Index Using Climate and Reservoir Indices as Covariates," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(4), pages 1377-1392, March.
  • Handle: RePEc:spr:waterr:v:36:y:2022:i:4:d:10.1007_s11269-022-03088-2
    DOI: 10.1007/s11269-022-03088-2
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    References listed on IDEAS

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    1. Shahab Araghinejad, 2011. "An Approach for Probabilistic Hydrological Drought Forecasting," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 25(1), pages 191-200, January.
    2. Peng Shi & Chao Chen & Ragahavan Srinivasan & Xuesong Zhang & Tao Cai & Xiuqin Fang & Simin Qu & Xi Chen & Qiongfang Li, 2011. "Evaluating the SWAT Model for Hydrological Modeling in the Xixian Watershed and a Comparison with the XAJ Model," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 25(10), pages 2595-2612, August.
    3. Lei Zou & Jun Xia & Dunxian She, 2018. "Analysis of Impacts of Climate Change and Human Activities on Hydrological Drought: a Case Study 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. 32(4), pages 1421-1438, March.
    4. R. A. Rigby & D. M. Stasinopoulos, 2005. "Generalized additive models for location, scale and shape," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 54(3), pages 507-554, June.
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