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Use of L-Moments Approach for Regional Flood Frequency Analysis in Sicily, Italy

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  • Leonardo Noto
  • Goffredo La Loggia

Abstract

Extremely great floods are among environmental events with the most disastrous consequences for the entire world. Estimates of their return periods and design values are of great importance in hydrologic modeling, engineering practice for water resources and reservoirs design and management, planning for weather-related emergencies, etc. Regional flood frequency analysis resolves the problem of estimating the extreme flood events for catchments having short data records or ungauged catchments. This paper analyzes annual maximum peak flood discharge data recorded from more than 50 stream flow gauging sites in Sicily, Italy, in order to derive regional flood frequency curves. First these data are analyzed to point out some problems concerning the homogeneity of the single time series. On the basis of the L-moments and using cluster analysis techniques, the entire region is subdivided in five subregions whose homogeneity is tested using the L-moments based heterogeneity measure. Comparative regional flood frequency analysis studies are carried out employing the L-moments based commonly used frequency distributions. Based on the L-moment ratio diagram and other statistic criteria, generalized extreme value (GEV) distribution is identified as the robust distribution for the study area. Regional flood frequency relationships are developed to estimate floods at various return periods for gauged and ungauged catchments in different subregions of the Sicily. These relationships have been implemented using the L-moment based GEV distribution and a regional relation between mean annual peak flood and some geomorphologic and climatic parameters of catchments. Copyright Springer Science+Business Media B.V. 2009

Suggested Citation

  • Leonardo Noto & Goffredo La Loggia, 2009. "Use of L-Moments Approach for Regional Flood Frequency Analysis in Sicily, Italy," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 23(11), pages 2207-2229, September.
    • Handle: RePEc:spr:waterr:v:23:y:2009:i:11:p:2207-2229
    DOI: 10.1007/s11269-008-9378-x
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    References listed on IDEAS

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    1. Rakesh Kumar & C. Chatterjee & Sanjay Kumar & A. Lohani & R. Singh, 2003. "Development of Regional Flood Frequency Relationships Using L-moments for Middle Ganga Plains Subzone 1(f) of India," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 17(4), pages 243-257, August.
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    Cited by:

    1. Brunella Bonaccorso & Giuseppe T. Aronica, 2016. "Estimating Temporal Changes in Extreme Rainfall in Sicily Region (Italy)," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(15), pages 5651-5670, December.
    2. Felício Cassalho & Samuel Beskow & Carlos Rogério Mello & Maíra Martim Moura & Laura Kerstner & Leo Fernandes Ávila, 2018. "At-Site Flood Frequency Analysis Coupled with Multiparameter Probability Distributions," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(1), pages 285-300, January.
    3. Rakesh Kumar & Narendra Goel & Chandranath Chatterjee & Purna Nayak, 2015. "Regional Flood Frequency Analysis using Soft Computing Techniques," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(6), pages 1965-1978, April.
    4. Giuseppe Cipolla & Antonio Francipane & Leonardo Valerio Noto, 2020. "Classification of Extreme Rainfall for a Mediterranean Region by Means of Atmospheric Circulation Patterns and Reanalysis Data," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(10), pages 3219-3235, August.
    5. S. Baidya & Ajay Singh & Sudhindra N. Panda, 2020. "Flood frequency analysis," 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. 100(3), pages 1137-1158, February.
    6. Neslihan Seckin & Murat Cobaner & Recep Yurtal & Tefaruk Haktanir, 2013. "Comparison of Artificial Neural Network Methods with L-moments for Estimating Flood Flow at Ungauged Sites: the Case of East Mediterranean River Basin, Turkey," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(7), pages 2103-2124, May.
    7. Nurulkamal Masseran & Muhammad Aslam Mohd Safari, 2022. "Statistical Modeling on the Severity of Unhealthy Air Pollution Events in Malaysia," Mathematics, MDPI, vol. 10(16), pages 1-15, August.
    8. Andrea Gioia & Maria Francesca Bruno & Vincenzo Totaro & Vito Iacobellis, 2020. "Parametric Assessment of Trend Test Power in a Changing Environment," Sustainability, MDPI, vol. 12(9), pages 1-18, May.
    9. T. K. Drissia & V. Jothiprakash & A. B. Anitha, 2019. "Flood Frequency Analysis Using L Moments: a Comparison between At-Site and Regional Approach," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(3), pages 1013-1037, February.
    10. Pezhman Allahbakhshian-Farsani & Mehdi Vafakhah & Hadi Khosravi-Farsani & Elke Hertig, 2020. "Regional Flood Frequency Analysis Through Some Machine Learning Models in Semi-arid Regions," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(9), pages 2887-2909, July.
    11. Chang-Shian Chen & Frederick Chou & Boris Chen, 2010. "Spatial Information-Based Back-Propagation Neural Network Modeling for Outflow Estimation of Ungauged Catchment," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 24(14), pages 4175-4197, November.

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