IMPALA - IMProved multivariate frequency Analysis of flood extremes by copuLAs in a non-stationary environment Completed Project uri icon

description

  • "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."

date/time interval

  • February 1, 2013 - January 31, 2015