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Analysis of Rainfall Severity and Duration in Victoria, Australia using Non-parametric Copulas and Marginal Distributions

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  • Ummul Abdul Rauf
  • Panlop Zeephongsekul

Abstract

The analysis of joint probability distributions of rainfall characteristics such as severity and duration is important in water resources management. Deriving their distributions using standard statistical techniques are often problematical due to its complexity. Standard methods usually assume that the rainfall characteristics are independent or that their marginal distributions belong to the same family of distributions. The use of copulas based methodologies can circumvent these restrictions and are therefore increasingly popular. However, the copulas and marginal distributions that are commonly used belong to specific parametric families and their adoption could lead to spurious inferences if the underlying assumptions are violated. For this reason, we recommend a nonparametric or semiparametric approach to estimate the joint distribution of rainfall characteristics. In this paper, we introduce and compare several copula–based approaches, each involving a combination of parametric or nonparametric marginal distributions conjoined by a parametric or nonparametric copula. An empirical illustration of the different approaches using rainfall data collected from six stations in the state of Victoria, Australia, demonstrated that a nonparametric approach can often give better results than a purely parametric approach. Copyright Springer Science+Business Media Dordrecht 2014

Suggested Citation

  • Ummul Abdul Rauf & Panlop Zeephongsekul, 2014. "Analysis of Rainfall Severity and Duration in Victoria, Australia using Non-parametric Copulas and Marginal Distributions," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(13), pages 4835-4856, October.
    • Handle: RePEc:spr:waterr:v:28:y:2014:i:13:p:4835-4856
    DOI: 10.1007/s11269-014-0779-8
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    1. Sajjad Abdollahi & Ali Mohammad Akhoond-Ali & Rasoul Mirabbasi & Jan Franklin Adamowski, 2019. "Probabilistic Event Based Rainfall-Runoff Modeling Using Copula Functions," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(11), pages 3799-3814, September.
    2. Nguyen-Huy, Thong & Deo, Ravinesh C. & An-Vo, Duc-Anh & Mushtaq, Shahbaz & Khan, Shahjahan, 2017. "Copula-statistical precipitation forecasting model in Australia’s agro-ecological zones," Agricultural Water Management, Elsevier, vol. 191(C), pages 153-172.
    3. Shahid Latif & Slobodan P. Simonovic, 2022. "Nonparametric Approach to Copula Estimation in Compounding The Joint Impact of Storm Surge and Rainfall Events in Coastal Flood Analysis," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(14), pages 5599-5632, November.
    4. Ravinesh Deo & Hi-Ryong Byun & Jan Adamowski & Do-Woo Kim, 2015. "A Real-time Flood Monitoring Index Based on Daily Effective Precipitation and its Application to Brisbane and Lockyer Valley Flood Events," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(11), pages 4075-4093, September.
    5. Shahid Latif & Slobodan P. Simonovic, 2023. "Trivariate Probabilistic Assessments of the Compound Flooding Events Using the 3-D Fully Nested Archimedean (FNA) Copula in the Semiparametric Distribution Setting," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(4), pages 1641-1693, March.
    6. Hongshi Xu & Kui Xu & Tianye Wang & Wanjie Xue, 2022. "Investigating Flood Risks of Rainfall and Storm Tides Affected by the Parameter Estimation Coupling Bivariate Statistics and Hydrodynamic Models in the Coastal City," IJERPH, MDPI, vol. 19(19), pages 1-18, October.
    7. Milan Cisty & Anna Becova & Lubomir Celar, 2016. "Analysis of Irrigation Needs Using an Approach Based on a Bivariate Copula Methodology," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(1), pages 167-182, January.

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