IDEAS home Printed from https://ideas.repec.org/a/spr/nathaz/v98y2019i2d10.1007_s11069-019-03724-y.html
   My bibliography  Save this article

Flood scaling under nonstationarity in Daqinghe River basin, China

Author

Listed:
  • Jianzhu Li

    (Tianjin University)

  • Qiushuang Ma

    (Tianjin University)

  • Yu Tian

    (China Institute of Water Resources and Hydropower Research)

  • Yuming Lei

    (China Water Northeastern Investigation, Design and Research Co., Ltd.)

  • Ting Zhang

    (Tianjin University)

  • Ping Feng

    (Tianjin University)

Abstract

Flood scaling issue is usually studied under stationary conditions. However, in recent decades, climate change and anthropogenic activities have changed hydrological processes, and stationary assumption has been questioned. To test the flood scaling invariance (simple scaling or multiscaling) and analyze the influence of environmental change on flood scaling parameter, in this study, eight mesoscale sub-watersheds in Daqinghe River basin were selected as the study area, and the trend and change point of annual maximum flood peak (AMFP) series were detected, respectively. All the AMFP series had downward trend, and the change point was around 1979. Therefore, the AMFP series are nonstationary. To analyze the flood scaling issue in the Daqinghe River basin, the AMFP series were reconstructed under the environmental conditions before and after the change point, respectively. Then, flood quantiles were calculated using the reconstructed stationary series. We also used GAMLSS (Generalized Additive Model in Location, Scale and Shape) to calculate flood quantiles based on the observed nonstationary AMFP series. According to the flood quantiles calculated by the above methods, the relationship of the drainage areas of the sub-watersheds and the flood quantiles was fitted with power function. Flood quantiles of the reconstructed stationary and observed nonstationary series showed obvious flood multiscaling. The increase in rainfall depth causes the increase in flood scaling exponents with the increase in return period, and different change ratios of land use before and after change point resulted in the flood scaling exponents of reconstructed series before 1979 were smaller than those after the change point at same return period.

Suggested Citation

  • Jianzhu Li & Qiushuang Ma & Yu Tian & Yuming Lei & Ting Zhang & Ping Feng, 2019. "Flood scaling under nonstationarity in Daqinghe River basin, 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. 98(2), pages 675-696, September.
    • Handle: RePEc:spr:nathaz:v:98:y:2019:i:2:d:10.1007_s11069-019-03724-y
    DOI: 10.1007/s11069-019-03724-y
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11069-019-03724-y
    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/s11069-019-03724-y?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. Hang Zeng & Ping Feng & Xin Li, 2014. "Reservoir Flood Routing Considering the Non-Stationarity of Flood Series in North China," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(12), pages 4273-4287, September.
    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.
    3. Xiyuan Deng & Weinan Ren & Ping Feng, 2016. "Design flood recalculation under land surface change," 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. 80(2), pages 1153-1169, January.
    4. 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.
    5. Elias Ishak & Khaled Haddad & Mohammad Zaman & Ataur Rahman, 2011. "Scaling property of regional floods in New South Wales Australia," 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. 58(3), pages 1155-1167, September.
    6. Xiyuan Deng & Weinan Ren & Ping Feng, 2016. "Design flood recalculation under land surface change," 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. 80(2), pages 1153-1169, January.
    7. 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. Yanchen Zheng & Jianzhu Li & Ting Zhang & Youtong Rong & Ping Feng, 2023. "Considering flood scaling property in multi-objective calibration of the SWAT model: a case study in Zijinguan watershed, Northern 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. 117(1), pages 267-292, May.

    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. Tranmer, Andrew W. & Marti, Clelia L. & Tonina, Daniele & Benjankar, Rohan & Weigel, Dana & Vilhena, Leticia & McGrath, Claire & Goodwin, Peter & Tiedemann, Matthew & Mckean, Jim & Imberger, Jörg, 2018. "A hierarchical modelling framework for assessing physical and biochemical characteristics of a regulated river," Ecological Modelling, Elsevier, vol. 368(C), pages 78-93.
    5. 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.
    6. Yuming Huang & Yanjie Li & Min Liu & Liang Xiao & Fuwan Gan & Jian Jiao, 2022. "Uncertainty Analysis of Flood Control Design Under Multiple Floods," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(4), pages 1175-1189, March.
    7. 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.
    8. 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.
    9. 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.
    10. Gauss Cordeiro & Josemar Rodrigues & Mário Castro, 2012. "The exponential COM-Poisson distribution," Statistical Papers, Springer, vol. 53(3), pages 653-664, August.
    11. Christian Kleiber & Achim Zeileis, 2016. "Visualizing Count Data Regressions Using Rootograms," The American Statistician, Taylor & Francis Journals, vol. 70(3), pages 296-303, July.
    12. 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.
    13. 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.
    14. 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.
    15. Kazi Ali Tamaddun & Ajay Kalra & Sajjad Ahmad, 2019. "Spatiotemporal Variation in the Continental US Streamflow in Association with Large-Scale Climate Signals Across Multiple Spectral Bands," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(6), pages 1947-1968, April.
    16. Alina Bărbulescu & Cristian Ștefan Dumitriu, 2021. "On the Connection between the GEP Performances and the Time Series Properties," Mathematics, MDPI, vol. 9(16), pages 1-19, August.
    17. 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.
    18. Alfredas Račkauskas & Martin Wendler, 2020. "Convergence of U-processes in Hölder spaces with application to robust detection of a changed segment," Statistical Papers, Springer, vol. 61(4), pages 1409-1435, August.
    19. Catherine Araujo Bonjean & Alioune N’diaye & Olivier Santoni, 2019. "Who benefits from the return of the rains? The case of the Ferlo breeders in Senegal [A qui profite le retour des pluies ? Le cas des éleveurs du Ferlo]," CERDI Working papers halshs-02419601, HAL.
    20. 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.

    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:98:y:2019:i:2:d:10.1007_s11069-019-03724-y. 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.