One of the biggest challenges of the flood frequency analysis that water resources
managers have to face recently is modelling two or more inter-dependent flood variables
(floods at river confluences; flood and the respective volumes and durations), and
accounting for the non-stationarity of the environment. The IMPALA project offers
multidisciplinary solution to this problem by copula-based multivariate frequency
modelling of flood extremes with the inclusion of information on historical and regional
ungauged extremes and respecting the effects of the changing environment, including
further development of methods for spatial data extension and their verification on a
Europe-wide scale.
Copulas are novel and flexible statistical tool suitable for frequency modelling of
multivariate flood extremes. Nevertheless, their application is not trivial, and additionally,
the general lack of the available data in the extreme spectrum of the joint distribution
makes the flood risk assessment unreliable. The project IMPALA is aimed at improving
the multivariate frequency modelling of flood characteristics by increasing the density of
the observations in the extreme tails of the marginal distributions. This will be reached by
direct inclusion of extraordinary flood data into a univariate flood frequency analysis of
marginals, by means of the Bayesian Markov chain Monte Carlo techniques. Depending
on the type of the extraordinary data, different strategies will be adopted: (a) flood
extremes from ungauged catchments will be included using a regional approach and the
stationary concept, while (b) historical flood extremes will be included using the local
approach and the non-stationarity assumption. The project IMPALA will take advantage
of existing pan-European databases of streamflow records and catchment descriptors
such as those held by the FRIEND or HYDRATE projects, and data from the relevant
gauging authorities in Slovakia and Austria.