IDEAS home Printed from https://ideas.repec.org/a/spr/nathaz/v113y2022i3d10.1007_s11069-022-05370-3.html
   My bibliography  Save this article

Impacts of climate and reservoirs on the downstream design flood hydrograph: a case study of Yichang Station

Author

Listed:
  • Rongrong Li

    (Wuhan University)

  • Lihua Xiong

    (Wuhan University)

  • Xini Zha

    (Wuhan University)

  • Bin Xiong

    (Nanchang University)

  • Han Liu

    (Wuhan University)

  • Jie Chen

    (Wuhan University)

  • Ling Zeng

    (Changjiang Water Resources Commission)

  • Wenbin Li

    (Wuhan University)

Abstract

The Upper Yangtze River (above Yichang) in China has constructed the world's largest reservoir group with the Three Gorges Reservoir (TGR) as the core, the operation of these reservoirs and future climate change will no doubt alter the downstream hydrological processes and pose a challenge to the downstream flood design. As Yichang Hydrologic Station is 44 km downstream of TGR, how the design flood at Yichang Station would be impacted in the future by climate and upstream reservoirs has rarely been investigated. In this study, the climate and upstream reservoirs effects on design flood at Yichang Station are evaluated under six future climate and reservoir scenarios (S1, S2, S3, S4, S5 and S6) with different combinations of summer precipitation anomaly (SPA) and reservoir index (RI), in which SPA is obtained from global climate models under the three emission scenarios (SSP1-2.6, SSP2-4.5 and SSP5-8.5) of CMIP6 and RI is calculated under the two reservoir conditions (RI at current level and RI at planning level). The SPA and RI of S1, S2, S3, S4, S5 and S6 are, respectively, substituted into the optimal nonstationary GEV probability model, and the corresponding 1000-year design floods are estimated by using average annual reliability method. Under the same future reservoir condition, the flood peak discharge, 3-day, 7-day, 15-day and 30-day flood volume (denoted as Qm, W3, W7, W15 and W30, respectively) under SSP2-4.5 and SSP5-8.5 are 0.2% ~ 2.5% larger than those under SSP1-2.6. The change rates of Qm, W3, W7, W15 and W30 under six scenarios relative to the stationary design flood values calculated by Changjiang Water Resources Commission range from −11.4% to −23.9%, and the reduction amount of Qm is more than 16,000 m3/s even under SSP5-8.5. Therefore, reservoirs impact on the design flood of Yichang Station is quite prominent.

Suggested Citation

  • Rongrong Li & Lihua Xiong & Xini Zha & Bin Xiong & Han Liu & Jie Chen & Ling Zeng & Wenbin Li, 2022. "Impacts of climate and reservoirs on the downstream design flood hydrograph: a case study of Yichang Station," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 113(3), pages 1803-1831, September.
    • Handle: RePEc:spr:nathaz:v:113:y:2022:i:3:d:10.1007_s11069-022-05370-3
    DOI: 10.1007/s11069-022-05370-3
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11069-022-05370-3
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s11069-022-05370-3?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. J. Rolf Olsen & James H. Lambert & Yacov Y. Haimes, 1998. "Risk of Extreme Events Under Nonstationary Conditions," Risk Analysis, John Wiley & Sons, vol. 18(4), pages 497-510, August.
    2. Yi-han Tang & Jie-feng Wu & Pei-yi Li & Li-juan Zhang & Xiao-hong Chen & Kai-rong Lin, 2019. "Quantifying Flood Frequency Modification Caused by Multi-Reservoir Regulation," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(13), pages 4451-4470, October.
    3. 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.
    4. P. C. D. Milly & R. T. Wetherald & K. A. Dunne & T. L. Delworth, 2002. "Increasing risk of great floods in a changing climate," Nature, Nature, vol. 415(6871), pages 514-517, January.
    5. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Atsuya Ikemoto & So Kazama & Takeo Yoshida & Hayata Yanagihara, 2023. "Evaluation of an Adaptation Strategy for Flood Damage Mitigation Under Climate Change Through the Use of Irrigation Reservoirs in Japan," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(10), pages 4159-4175, August.
    2. Rongrong Li & Lihua Xiong & Cong Jiang & Wenbin Li & Chengkai Liu, 2023. "Quantifying multivariate flood risk under nonstationary condition," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 116(1), pages 1161-1187, March.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Jianzhu Li & Yuming Lei & Senming Tan & Colin D. Bell & Bernard A. Engel & Yixuan Wang, 2018. "Nonstationary Flood Frequency Analysis for Annual Flood Peak and Volume Series in Both Univariate and Bivariate Domain," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(13), pages 4239-4252, October.
    2. Jianzhu Li & Senming Tan, 2015. "Nonstationary Flood Frequency Analysis for Annual Flood Peak Series, Adopting Climate Indices and Check Dam Index as Covariates," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(15), pages 5533-5550, December.
    3. Lei Yan & Lihua Xiong & Qinghua Luan & Cong Jiang & Kunxia Yu & Chong-Yu Xu, 2020. "On the Applicability of the Expected Waiting Time Method in Nonstationary Flood Design," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(8), pages 2585-2601, June.
    4. Dong-dong Zhang & Deng-hua Yan & Yi-Cheng Wang & Fan Lu & Shao-hua Liu, 2015. "GAMLSS-based nonstationary modeling of extreme precipitation in Beijing–Tianjin–Hebei region of China," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 77(2), pages 1037-1053, June.
    5. Yixuan Wang & Jianzhu Li & Ping Feng & Rong Hu, 2015. "A Time-Dependent Drought Index for Non-Stationary Precipitation Series," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(15), pages 5631-5647, December.
    6. Nathaniel Geiger & Bryan McLaughlin & John Velez, 2021. "Not all boomers: temporal orientation explains inter- and intra-cultural variability in the link between age and climate engagement," Climatic Change, Springer, vol. 166(1), pages 1-20, May.
    7. Panayi, Efstathios & Peters, Gareth W. & Danielsson, Jon & Zigrand, Jean-Pierre, 2018. "Designating market maker behaviour in limit order book markets," Econometrics and Statistics, Elsevier, vol. 5(C), pages 20-44.
    8. Gauss Cordeiro & Josemar Rodrigues & Mário Castro, 2012. "The exponential COM-Poisson distribution," Statistical Papers, Springer, vol. 53(3), pages 653-664, August.
    9. Christian Kleiber & Achim Zeileis, 2016. "Visualizing Count Data Regressions Using Rootograms," The American Statistician, Taylor & Francis Journals, vol. 70(3), pages 296-303, July.
    10. P. V. Timbadiya & K. M. Krishnamraju, 2023. "A 2D hydrodynamic model for river flood prediction in a coastal floodplain," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 115(2), pages 1143-1165, January.
    11. Chen, Shu & Shao, Dongguo & Tan, Xuezhi & Gu, Wenquan & Lei, Caixiu, 2017. "An interval multistage classified model for regional inter- and intra-seasonal water management under uncertain and nonstationary condition," Agricultural Water Management, Elsevier, vol. 191(C), pages 98-112.
    12. Riccardo De Bin & Vegard Grødem Stikbakke, 2023. "A boosting first-hitting-time model for survival analysis in high-dimensional settings," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 29(2), pages 420-440, April.
    13. Matteo Malavasi & Gareth W. Peters & Pavel V. Shevchenko & Stefan Truck & Jiwook Jang & Georgy Sofronov, 2021. "Cyber Risk Frequency, Severity and Insurance Viability," Papers 2111.03366, arXiv.org, revised Mar 2022.
    14. Tong, Edward N.C. & Mues, Christophe & Thomas, Lyn, 2013. "A zero-adjusted gamma model for mortgage loan loss given default," International Journal of Forecasting, Elsevier, vol. 29(4), pages 548-562.
    15. 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.
    16. Ding, Hui & Zhang, Jian & Zhang, Riquan, 2022. "Nonparametric variable screening for multivariate additive models," Journal of Multivariate Analysis, Elsevier, vol. 192(C).
    17. Giampiero Marra & Matteo Fasiolo & Rosalba Radice & Rainer Winkelmann, 2023. "A flexible copula regression model with Bernoulli and Tweedie margins for estimating the effect of spending on mental health," Health Economics, John Wiley & Sons, Ltd., vol. 32(6), pages 1305-1322, June.
    18. Berlemann, Michael, 2015. "Hurricane Risk, Happiness and Life Satisfaction. Some Empirical Evidence on the Indirect Effects of Natural Disasters," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 113073, Verein für Socialpolitik / German Economic Association.
    19. Álvarez, Xana & Gómez-Rúa, María & Vidal-Puga, Juan, 2019. "Risk prevention of land flood: A cooperative game theory approach," MPRA Paper 91515, University Library of Munich, Germany.
    20. D. Chiru Naik & Sagar Rohidas Chavan & P. Sonali, 2023. "Incorporating the climate oscillations in the computation of meteorological drought over India," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 117(3), pages 2617-2646, July.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:nathaz:v:113:y:2022:i:3:d:10.1007_s11069-022-05370-3. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.