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

Alireza Daneshkhah; Renji Remesan; Omid Chatrabgoun; Ian Holman

doi:10.1016/j.jhydrol.2016.06.044

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

Alireza Daneshkhah, Renji Remesan, Omid Chatrabgoun, Ian Holman

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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 language	English
Pages (from-to)	469-487
Number of pages	20
Journal	Journal of Hydrology
Volume	540
Early online date	21 Jun 2016
DOIs	https://doi.org/10.1016/j.jhydrol.2016.06.044
Publication status	Published - Sept 2016
Externally published	Yes

Bibliographical note

Open Access funded by Natural Environment Research Council
Under a Creative Commons license.

Copyright © and Moral Rights are retained by the author(s) and/ or other
copyright owners. A copy can be downloaded for personal non-commercial
research or study, without prior permission or charge. This item cannot be
reproduced or quoted extensively from without first obtaining permission in
writing from the copyright holder(s). The content must not be changed in any way
or sold commercially in any format or medium without the formal permission of
the copyright holders.

Keywords

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

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10.1016/j.jhydrol.2016.06.044Licence: CC BY

PublishedFinal published version, 1.82 MBLicence: CC BY

Alireza Daneshkhah
- EEC School of Computing, Mathematics and Data Sciences (CMDS) - Curriculum Lead (Associate Professor - Academic)
Person: Teaching and Research

Cite this

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title = "Probabilistic modeling of flood characterizations with parametric and minimum information pair-copula model",

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.",

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author = "Alireza Daneshkhah and Renji Remesan and Omid Chatrabgoun and Ian Holman",

note = "Open Access funded by Natural Environment Research Council Under a Creative Commons license. Copyright {\textcopyright} and Moral Rights are retained by the author(s) and/ or other copyright owners. A copy can be downloaded for personal non-commercial research or study, without prior permission or charge. This item cannot be reproduced or quoted extensively from without first obtaining permission in writing from the copyright holder(s). The content must not be changed in any way or sold commercially in any format or medium without the formal permission of the copyright holders.",

year = "2016",

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doi = "10.1016/j.jhydrol.2016.06.044",

language = "English",

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AU - Daneshkhah, Alireza

AU - Remesan, Renji

AU - Chatrabgoun, Omid

AU - Holman, Ian

N1 - Open Access funded by Natural Environment Research Council Under a Creative Commons license. Copyright © and Moral Rights are retained by the author(s) and/ or other copyright owners. A copy can be downloaded for personal non-commercial research or study, without prior permission or charge. This item cannot be reproduced or quoted extensively from without first obtaining permission in writing from the copyright holder(s). The content must not be changed in any way or sold commercially in any format or medium without the formal permission of the copyright holders.

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Y1 - 2016/9

N2 - 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.

AB - 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.

KW - Flood frequency analysis

KW - Flood hazard characterization

KW - Return period

KW - D-vine model

KW - Minimum information pair-copula model

KW - Himalaya (India)

U2 - 10.1016/j.jhydrol.2016.06.044

DO - 10.1016/j.jhydrol.2016.06.044

M3 - Article

SN - 0022-1694

SN - 1879-2707

VL - 540

SP - 469

EP - 487

JO - Journal of Hydrology

JF - Journal of Hydrology

ER -

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

Abstract

Bibliographical note

Keywords

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Alireza Daneshkhah

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