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

Date published

2016-06-21

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Elsevier

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Article

ISSN

0022-1694

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Citation

Alireza Daneshkhah, Renji Remesan, Omid Chatrabgoun, Ian P. Holman, Probabilistic modeling of flood characterizations with parametric and minimum information pair-copula model, Journal of Hydrology, Volume 540, September 2016, pp. 469-487

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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Github

Keywords

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

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Attribution 4.0 International

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