A univariate gamma distribution is one of the most commonly adopted statistical distributions
in hydrological frequency analysis. A bivariate gamma distribution constructed from …

The statistics of extremes have played an important role in engineering practice for water
resources design and management. How recent developments in the statistical theory of …

This article presents the modeling of multivariate extreme values using copulas. Our
approach allows us to model the dependence structure independently of the marginal …

Risk assessment requires a description of the probabilistic properties of hydrological
variables. In a number of cases, this description is made on a single variable, whereas most …

Basic concepts such as conditional probability distributions, conditional return periods, and
joint return periods are important to understand and to interpret multivariate hydrological …

On coasts with high tidal ranges, or subject to high surges, both still water levels and waves
can be important in assessing flood risk; their relative importance depends on location and …

A gamma distribution is one of the most frequently selected distribution types for
hydrological frequency analysis. The bivariate gamma distribution with gamma marginals …

This paper highlights the importance of taking into account the tail dependence in the
context of bivariate frequency analysis based on copulas. Three nonparametric estimators of …

Various methods have been developed over the past five decades for dependence
modeling of multivariate variables in hydrology and water resources, but there has been no …

In this paper, a copula-based methodology is presented for probabilistic assessment of flood
risks and investigated the performance of trivariate copulas in modeling dependence …