IDEAS home Printed from https://ideas.repec.org/a/spr/waterr/v37y2023i15d10.1007_s11269-023-03649-z.html
   My bibliography  Save this article

Flood Attenuation Potential of Italian Dams: Sensitivity on Geomorphic and Climatological Factors

Author

Listed:
  • Giulia Evangelista

    (Politecnico di Torino, Department of Environment, Land and Infrastructure Engineering)

  • Daniele Ganora

    (Politecnico di Torino, Department of Environment, Land and Infrastructure Engineering)

  • Paola Mazzoglio

    (Politecnico di Torino, Department of Environment, Land and Infrastructure Engineering)

  • Francesca Pianigiani

    (General Department of Dams and Hydro-Electrical Infrastructures)

  • Pierluigi Claps

    (Politecnico di Torino, Department of Environment, Land and Infrastructure Engineering)

Abstract

In this work the attenuation potential of flood peaks of 265 large reservoirs all over Italy is analysed, considering a flood management that excludes gates opening and then configures strictly unsupervised attenuation effects. Key factors of dams and related basins are considered to develop a ranking method that can emphasize the interplay between dam geometry and the hydrological processes acting in the upstream watershed. To maintain a homogeneous approach in such a wide geographic area, the attenuation index is computed applying the numerical solution of the differential equation of lakes and only two different standardized hydrograph shapes have been used. An index design flood from the rational method is used as the incoming peak value for each dam, enhancing the use of the results of a recent analysis of all Italian rainfall extremes. Even with a very simple approach, twenty-four different design incoming floods are derived, by varying the shape of the incoming hydrograph and the parameters of the rational method. Exploring the ranking results in all the alternatives, the attenuation potential obtained for all dams demonstrates to be strongly sensitive to the assumptions on the time of concentration and to some rainfall features. On the other hand, the hydrograph shape seems to exert much less influence on the ranking outcome. Results obtained can be useful to studies of wide-area flood frequency analyses, as we highlighted the sensitivity of the rank of attenuation efficiency to hydrologic parameters widely used in the assessment of the design flood peaks in ungauged basins.

Suggested Citation

  • Giulia Evangelista & Daniele Ganora & Paola Mazzoglio & Francesca Pianigiani & Pierluigi Claps, 2023. "Flood Attenuation Potential of Italian Dams: Sensitivity on Geomorphic and Climatological Factors," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(15), pages 6165-6181, December.
  • Handle: RePEc:spr:waterr:v:37:y:2023:i:15:d:10.1007_s11269-023-03649-z
    DOI: 10.1007/s11269-023-03649-z
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11269-023-03649-z
    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/s11269-023-03649-z?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. Leila Shakarami & Parisa-Sadat Ashofteh & Vijay P. Singh, 2022. "Disaggregating the Effects of Climatic Variability and Dam Construction on River Flow Regime," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(10), pages 3813-3838, August.
    2. Parisa Noorbeh & Abbas Roozbahani & Hamid Kardan Moghaddam, 2020. "Annual and Monthly Dam Inflow Prediction Using Bayesian Networks," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(9), pages 2933-2951, July.
    3. Julien Boulange & Naota Hanasaki & Dai Yamazaki & Yadu Pokhrel, 2021. "Role of dams in reducing global flood exposure under climate change," Nature Communications, Nature, vol. 12(1), pages 1-7, December.
    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. Prabal Das & D. A. Sachindra & Kironmala Chanda, 2022. "Machine Learning-Based Rainfall Forecasting with Multiple Non-Linear Feature Selection Algorithms," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(15), pages 6043-6071, December.
    2. Julien Boulange & Yukiko Hirabayashi & Masahiro Tanoue & Toshinori Yamada, 2023. "Quantitative evaluation of flood damage methodologies under a portfolio of adaptation scenarios," 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. 118(3), pages 1855-1879, September.
    3. Hamid Kardan Moghaddam & Mohammad Ebrahim Banihabib & Saman Javadi & Timothy O. Randhir, 2021. "A framework for the assessment of qualitative and quantitative sustainable development of groundwater system," Sustainable Development, John Wiley & Sons, Ltd., vol. 29(6), pages 1096-1110, November.
    4. Schmitt, Rafael Jan Pablo & Rosa, Lorenzo, 2024. "Dams for hydropower and irrigation: Trends, challenges, and alternatives," Renewable and Sustainable Energy Reviews, Elsevier, vol. 199(C).
    5. Chen, Zhonglu & Zhang, Li & Weng, Chen, 2023. "Does climate policy uncertainty affect Chinese stock market volatility?," International Review of Economics & Finance, Elsevier, vol. 84(C), pages 369-381.
    6. Bao-Jian Li & Guo-Liang Sun & Yan Liu & Wen-Chuan Wang & Xu-Dong Huang, 2022. "Monthly Runoff Forecasting Using Variational Mode Decomposition Coupled with Gray Wolf Optimizer-Based Long Short-term Memory Neural Networks," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(6), pages 2095-2115, April.
    7. Lili Wang & Zexia Li & Fuqiang Ye & Tongyang Liu, 2023. "A Probability Model for Short-Term Streamflow Prediction Based on Multi-Resolution Data," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(14), pages 5601-5618, November.
    8. Mohamad Basel Sawaf & Kiyosi Kawanisi & Cong Xiao & Gillang Noor Nugrahaning Gusti & Faruq Khadami, 2022. "Monitoring Inflow Dynamics in a Multipurpose Dam Based on Travel-time Principle," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(8), pages 2589-2610, June.
    9. Zhao, Huirong & Luo, Na, 2024. "Climate uncertainty and green index volatility: Empirical insights from Chinese financial markets," Finance Research Letters, Elsevier, vol. 60(C).
    10. Atiyeh Bozorgi & Abbas Roozbahani & Seied Mehdy Hashemy Shahdany & Rouzbeh Abbassi, 2021. "Development of Multi-Hazard Risk Assessment Model for Agricultural Water Supply and Distribution Systems Using Bayesian Network," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(10), pages 3139-3159, August.
    11. Sarmad Dashti Latif & Ali Najah Ahmed & Edlic Sathiamurthy & Yuk Feng Huang & Ahmed El-Shafie, 2021. "Evaluation of deep learning algorithm for inflow forecasting: a case study of Durian Tunggal Reservoir, Peninsular Malaysia," 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. 109(1), pages 351-369, October.
    12. Jiang, Qi & Fan, Yawen, 2024. "Hedging downside risk in agricultural commodities: A novel nonparametric kernel method," Finance Research Letters, Elsevier, vol. 70(C).
    13. Dinesh Roulo & Subbarao Pichuka, 2024. "Assessing the effects of extreme rainfall patterns and their impact on dam safety: a case study on Indian dam failures," 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. 120(14), pages 12967-12987, November.
    14. Pengcheng Qin & Hongmei Xu & Min Liu & Lüliu Liu & Chan Xiao & Iman Mallakpour & Matin Rahnamay Naeini & Kuolin Hsu & Soroosh Sorooshian, 2022. "Projected impacts of climate change on major dams in the Upper Yangtze River Basin," Climatic Change, Springer, vol. 170(1), pages 1-24, January.
    15. Xu, Xin & An, Haizhong & Huang, Shupei & Jia, Nanfei & Qi, Yajie, 2024. "Measurement of daily climate physical risks and climate transition risks faced by China's energy sector stocks," International Review of Economics & Finance, Elsevier, vol. 93(PB), pages 625-640.
    16. Xu, Xin & Huang, Shupei & Lucey, Brian M. & An, Haizhong, 2023. "The impacts of climate policy uncertainty on stock markets: Comparison between China and the US," International Review of Financial Analysis, Elsevier, vol. 88(C).
    17. Zhang, Li & Liang, Chao & Huynh, Luu Duc Toan & Wang, Lu & Damette, Olivier, 2024. "Measuring the impact of climate risk on renewable energy stock volatility: A case study of G20 economies," Journal of Economic Behavior & Organization, Elsevier, vol. 223(C), pages 168-184.
    18. Javad Shafiee Neyestanak & Abbas Roozbahani, 2021. "Comprehensive Risk Assessment of Urban Wastewater Reuse in Water Supply Alternatives Using Hybrid Bayesian Network Model," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(14), pages 5049-5072, November.
    19. Hossien Riahi-Madvar & Majid Dehghani & Rasoul Memarzadeh & Bahram Gharabaghi, 2021. "Short to Long-Term Forecasting of River Flows by Heuristic Optimization Algorithms Hybridized with ANFIS," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(4), pages 1149-1166, March.
    20. M. Rajesh & Sachdeva Anishka & Pansari Satyam Viksit & Srivastav Arohi & S. Rehana, 2023. "Improving Short-range Reservoir Inflow Forecasts with Machine Learning Model Combination," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(1), pages 75-90, January.

    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:37:y:2023:i:15:d:10.1007_s11269-023-03649-z. 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.