IDEAS home Printed from https://ideas.repec.org/a/spr/waterr/v35y2021i5d10.1007_s11269-021-02798-3.html
   My bibliography  Save this article

Dam Hydrological Risk and the Design Flood Under Non-stationary Conditions

Author

Listed:
  • Leandro José Isensee

    (Fundação Universidade Regional de Blumenau)

  • Adilson Pinheiro

    (Fundação Universidade Regional de Blumenau)

  • Daniel Henrique Marco Detzel

    (Federal University of Paraná)

Abstract

Increasing global trends in time series of annual maximum daily streamflow (AMX) raise the concern that the safety of dams and other sensitive structures is compromised. There is no defined methodology to estimate the design flood (DF) under non-stationarity; thus, the objective of this work is to evaluate the behavior of the hydrological risk of Brazilian dams due to the non-stationary nature of the AMX time series and the implications of the non-stationary nature of the AMX time series in the design of new dams. For this, the hydrological risk of 108 AMX time series was evaluated, comparing the time intervals between 1954–1984 and 1954–2014. A case study was also executed, where the DF was estimated in a non-stationary time series. The generalized distribution of extreme values (GEV) was applied in the time series analyses. The results indicate that the hydrological risk of Brazilian dams increased, and safety may have been reduced. Regarding the ranking of models, the use of physical covariates in the estimate of the DF makes the estimates more reliable. Finally, although significant trends are good indicators, they alone do not guarantee a reduction or increase in risk. It was also observed that using non-stationary models is less important than updating the estimates with newly observed data.

Suggested Citation

  • 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.
    • Handle: RePEc:spr:waterr:v:35:y:2021:i:5:d:10.1007_s11269-021-02798-3
    DOI: 10.1007/s11269-021-02798-3
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11269-021-02798-3
    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/s11269-021-02798-3?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. Linyin Cheng & Amir AghaKouchak & Eric Gilleland & Richard Katz, 2014. "Non-stationary extreme value analysis in a changing climate," Climatic Change, Springer, vol. 127(2), pages 353-369, November.
    2. 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.
    3. 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.
    4. Sang Ug Kim & Cheol-Eung Lee, 2021. "Incorporation of Cost-Benefit Analysis Considering Epistemic Uncertainty for Calculating the Optimal Design Flood," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(2), pages 757-774, January.
    5. Yiming Hu & Zhongmin Liang & Vijay P. Singh & Xuebin Zhang & Jun Wang & Binquan Li & Huimin Wang, 2018. "Concept of Equivalent Reliability for Estimating 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. 32(3), pages 997-1011, February.
    6. Ali Razmi & Saeed Golian & Zahra Zahmatkesh, 2017. "Non-Stationary Frequency Analysis of Extreme Water Level: Application of Annual Maximum Series and Peak-over Threshold Approaches," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(7), pages 2065-2083, May.
    7. Christian L. E. Franzke & Marcin Czupryna, 2020. "Probabilistic assessment and projections of US weather and climate risks and economic damages," Climatic Change, Springer, vol. 158(3), pages 503-515, February.
    Full references (including those not matched with items on IDEAS)

    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. 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.
    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. Hongxiang Yan & Hamid Moradkhani, 2016. "Toward more robust extreme flood prediction by Bayesian hierarchical and multimodeling," 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. 81(1), pages 203-225, March.
    4. Robert L. Ceres & Chris E. Forest & Klaus Keller, 2017. "Understanding the detectability of potential changes to the 100-year peak storm surge," Climatic Change, Springer, vol. 145(1), pages 221-235, November.
    5. 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.
    6. Mojtaba Sadegh & Amir AghaKouchak & Alejandro Flores & Iman Mallakpour & Mohammad Reza Nikoo, 2019. "A Multi-Model Nonstationary Rainfall-Runoff Modeling Framework: Analysis and Toolbox," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(9), pages 3011-3024, July.
    7. Jittima Singvejsakul & Chukiat Chaiboonsri & Songsak Sriboonchitta, 2021. "The Optimization of Bayesian Extreme Value: Empirical Evidence for the Agricultural Commodities in the US," Economies, MDPI, vol. 9(1), pages 1-10, March.
    8. Mahkameh Zarekarizi & Vivek Srikrishnan & Klaus Keller, 2020. "Neglecting Uncertainties Biases House-Elevation Decisions to Manage Riverine Flood Risks," Papers 2001.06457, arXiv.org, revised Sep 2020.
    9. Uddameri, Venkatesh & Ghaseminejad, Ali & Hernandez, E. Annette, 2020. "A tiered stochastic framework for assessing crop yield loss risks due to water scarcity under different uncertainty levels," Agricultural Water Management, Elsevier, vol. 238(C).
    10. 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.
    11. Franzke, Christian L.E., 2021. "Towards the development of economic damage functions for weather and climate extremes," Ecological Economics, Elsevier, vol. 189(C).
    12. Christian L. E. Franzke & Marcin Czupryna, 2020. "Probabilistic assessment and projections of US weather and climate risks and economic damages," Climatic Change, Springer, vol. 158(3), pages 503-515, February.
    13. M. Karamouz & F. Fooladi Mahani, 2021. "DEM Uncertainty Based Coastal Flood Inundation Modeling Considering Water Quality Impacts," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(10), pages 3083-3103, August.
    14. Hongxiang Yan & Hamid Moradkhani, 2016. "Toward more robust extreme flood prediction by Bayesian hierarchical and multimodeling," 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. 81(1), pages 203-225, March.
    15. Goyal, Manish Kumar & Gupta, Anil Kumar & Jha, Srinidhi & Rakkasagi, Shivukumar & Jain, Vijay, 2022. "Climate change impact on precipitation extremes over Indian cities: Non-stationary analysis," Technological Forecasting and Social Change, Elsevier, vol. 180(C).
    16. Mohammad Karamouz & Helia Farzaneh & Mehri Dolatshahi, 2020. "Margin of Safety Based Flood Reliability Evaluation of Wastewater Treatment Plants: Part 1 – Basic Concepts and Statistical Settings," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(2), pages 579-594, January.
    17. Chen, Haoling & Zhao, Tongtiegang, 2020. "Modeling power loss during blackouts in China using non-stationary generalized extreme value distribution," Energy, Elsevier, vol. 195(C).
    18. Saeed Alimohammadi & Masoume Behrouz, 2021. "Stochastic Design of Flood Control Systems; Uncertainty Propagation and Results Representation," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(13), pages 4457-4476, October.
    19. Omid Bozorg-Haddad & Mohammad Solgi & Hugo A. Loáiciga, 2017. "Investigation of Climatic Variability with Hybrid Statistical Analysis," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(1), pages 341-353, January.
    20. Hefei Huang & Huijuan Cui & Quansheng Ge, 2021. "Assessment of potential risks induced by increasing extreme precipitation under climate 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. 108(2), pages 2059-2079, September.

    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:waterr:v:35:y:2021:i:5:d:10.1007_s11269-021-02798-3. 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.