IDEAS home Printed from https://ideas.repec.org/a/spr/nathaz/v75y2015i1p909-934.html
   My bibliography  Save this article

Comparison of methodologies for flood rainfall thresholds estimation

Author

Listed:
  • V. Montesarchio
  • F. Napolitano
  • M. Rianna
  • E. Ridolfi
  • F. Russo
  • S. Sebastianelli

Abstract

A flood warning system based on rainfall thresholds makes it possible to issue alarms via an off-line approach. This technique is useful for mitigating the effects of flooding in small-to-medium-sized basins characterized by an extremely rapid response to rainfall. Rainfall threshold values specify the amount of precipitation that occurs over a given period of time and are dependent on both the amount of soil moisture and the spatiotemporal distribution of the rainfall. The precipitation generates a critical discharge in a particular river cross section. Exceeding these values can produce a critical situation in river sites that make them susceptible to flooding. In this work, we present a comparison of methodologies for estimating rainfall thresholds. Critical precipitation amounts are evaluated using empirical data, hydrological simulations and probabilistic methods. The study focuses on three small-to-medium-sized basins located in central Italy. For each catchment, historical data are first used to theoretically evaluate the empirical rainfall thresholds. Next, we calibrate a semi-distributed hydrological model that is validated using rain gauge and weather radar data. Critical rainfall depths over 30 min and 1, 3, 6, 12 and 24 h durations are then evaluated using the hydrological simulation. In the probabilistic approach, rainfall threshold values result from a minimization of two different functions, one following the Bayesian decision theory and the other following the informative entropy concept. In order to implement both functions, it is necessary to evaluate the joint probability function. The joint probability function is built up as a bivariate distribution of rainfall depth for a given duration with the corresponding flow peak value. Finally, in order to assess the performance of each methodology, we construct contingency tables to highlight the system performance. Copyright Springer Science+Business Media Dordrecht 2015

Suggested Citation

  • V. Montesarchio & F. Napolitano & M. Rianna & E. Ridolfi & F. Russo & S. Sebastianelli, 2015. "Comparison of methodologies for flood rainfall thresholds estimation," 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. 75(1), pages 909-934, January.
    • Handle: RePEc:spr:nathaz:v:75:y:2015:i:1:p:909-934
    DOI: 10.1007/s11069-014-1357-3
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s11069-014-1357-3
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s11069-014-1357-3?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. Saeed Golian & Bahram Saghafian & Reza Maknoon, 2010. "Derivation of Probabilistic Thresholds of Spatially Distributed Rainfall for Flood Forecasting," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 24(13), pages 3547-3559, October.
    2. Michalis Diakakis, 2012. "Rainfall thresholds for flood triggering. The case of Marathonas in Greece," 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. 60(3), pages 789-800, February.
    3. Yang, Jiping & Qiu, Wanhua, 2005. "A measure of risk and a decision-making model based on expected utility and entropy," European Journal of Operational Research, Elsevier, vol. 164(3), pages 792-799, August.
    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. Wenlin Yuan & Meiqi Liu & Fang Wan, 2019. "Calculation of Critical Rainfall for Small-Watershed Flash Floods Based on the HEC-HMS Hydrological Model," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(7), pages 2555-2575, 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. Shiang-Jen Wu & Chih-Tsung Hsu & Ho-Cheng Lien & Che-Hao Chang, 2015. "Modeling the effect of uncertainties in rainfall characteristics on flash flood warning based on rainfall thresholds," 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. 75(2), pages 1677-1711, January.
    2. Naser Dehghanian & S. Saeid Mousavi Nadoushani & Bahram Saghafian & Ruhangiz Akhtari, 2019. "Performance Evaluation of a Fuzzy Hybrid Clustering Technique to Identify Flood Source Areas," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(13), pages 4621-4636, October.
    3. R. Luce & C. Ng & A. Marley & János Aczél, 2008. "Utility of gambling II: risk, paradoxes, and data," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 36(2), pages 165-187, August.
    4. Nikola Gradojevic & Marko Caric, 2017. "Predicting Systemic Risk with Entropic Indicators," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 36(1), pages 16-25, January.
    5. Changjun Liu & Liang Guo & Lei Ye & Shunfu Zhang & Yanzeng Zhao & Tianyu Song, 2018. "A review of advances in China’s flash flood early-warning system," 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. 92(2), pages 619-634, June.
    6. Fischer, Kathrin & Kleine, Andreas, 2007. "Remarks on "A measure of risk and a decision-making model based on expected utility and entropy" by Jiping Yang and Wanhua Qiu (EJOR 164 (2005), 792-799)," European Journal of Operational Research, Elsevier, vol. 182(1), pages 469-474, October.
    7. Yogita Singh & Mohd. Adil & S. M. Imamul Haque, 2023. "Personality traits and behaviour biases: the moderating role of risk-tolerance," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(4), pages 3549-3573, August.
    8. Nathan Lassance & Frédéric Vrins, 2021. "Minimum Rényi entropy portfolios," Annals of Operations Research, Springer, vol. 299(1), pages 23-46, April.
    9. Alaa Ahmed & Guna Hewa & Abdullah Alrajhi, 2021. "Flood susceptibility mapping using a geomorphometric approach in South Australian basins," 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. 106(1), pages 629-653, March.
    10. Daniel Chiew & Judy Qiu & Sirimon Treepongkaruna & Jiping Yang & Chenxiao Shi, 2019. "The predictive ability of the expected utility-entropy based fund rating approach: A comparison investigation with Morningstar ratings in US," PLOS ONE, Public Library of Science, vol. 14(4), pages 1-22, April.
    11. He, Ying & Huang, Rui-Hua, 2008. "Risk attributes theory: Decision making under risk," European Journal of Operational Research, Elsevier, vol. 186(1), pages 243-260, April.
    12. R. Luce & C. Ng & A. Marley & János Aczél, 2008. "Utility of gambling I: entropy modified linear weighted utility," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 36(1), pages 1-33, July.
    13. Fränz Zeimetz & Bettina Schaefli & Guillaume Artigue & Javier García Hernández & Anton J. Schleiss, 2018. "Swiss Rainfall Mass Curves and their Influence on Extreme Flood Simulation," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(8), pages 2625-2638, June.
    14. Brice Corgnet & Roberto Hernán González, 2023. "On The Appeal Of Complexity," Working Papers 2312, Groupe d'Analyse et de Théorie Economique Lyon St-Étienne (GATE Lyon St-Étienne), Université de Lyon.
    15. Fawad Ahmad, 2020. "Personality traits as predictor of cognitive biases: moderating role of risk-attitude," Qualitative Research in Financial Markets, Emerald Group Publishing Limited, vol. 12(4), pages 465-484, June.
    16. Wei Li & Jianzhong Zhou & Huaiwei Sun & Kuaile Feng & Hairong Zhang & Muhammad Tayyab, 2017. "Impact of Distribution Type in Bayes Probability Flood Forecasting," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(3), pages 961-977, February.
    17. Birnbaum, Michael H., 2007. "Tests of branch splitting and branch-splitting independence in Allais paradoxes with positive and mixed consequences," Organizational Behavior and Human Decision Processes, Elsevier, vol. 102(2), pages 154-173, March.
    18. Zhou, Wei & Zhang, Cheng & Wang, Qiangqiang, 2018. "Concealment measurement and flow distribution of military supply transportation: A double-entropy model," European Journal of Operational Research, Elsevier, vol. 264(2), pages 570-581.
    19. Michalis Diakakis, 2012. "Rainfall thresholds for flood triggering. The case of Marathonas in Greece," 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. 60(3), pages 789-800, February.
    20. A. O. Matin & F. Misagh, 2019. "A Modified Mcdm Algorithm With Cumulative Entropy Weights For Selecting The Winner Of The Tender," Strategic decisions and risk management, Real Economy Publishing House, vol. 10(1).

    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:75:y:2015:i:1:p:909-934. 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.