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.
|Number of pages||20|
|Journal||Journal of Hydrology|
|Early online date||21 Jun 2016|
|Publication status||Published - Sep 2016|
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- Flood frequency analysis
- Flood hazard characterization
- Return period
- D-vine model
- Minimum information pair-copula model
- Himalaya (India)
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