Probabilistic modeling of flood characterizations with parametric and minimum information pair-copula model

Alireza Daneshkhah, Renji Remesan, Omid Chatrabgoun, Ian Holman

Research output: Contribution to journalArticle

26 Citations (Scopus)
17 Downloads (Pure)

Abstract

This paper highlights the usefulness of the minimum information and parametric pair-copula construction (PCC) to model the joint distribution of flood event properties. Both of these models outperform other standard multivariate copula in modeling multivariate flood data that exhibiting complex patterns of dependence, particularly in the tails. In particular, the minimum information pair-copula model shows greater flexibility and produces better approximation of the joint probability density and corresponding measures have capability for effective hazard assessments. The study demonstrates that any multivariate density can be approximated to any degree of desired precision using minimum information pair-copula model and can be practically used for probabilistic flood hazard assessment.
Original languageEnglish
Pages (from-to)469-487
Number of pages20
JournalJournal of Hydrology
Volume540
Early online date21 Jun 2016
DOIs
Publication statusPublished - Sep 2016
Externally publishedYes

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Open Access funded by Natural Environment Research Council
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Keywords

  • Flood frequency analysis
  • Flood hazard characterization
  • Return period
  • D-vine model
  • Minimum information pair-copula model
  • Himalaya (India)

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