Flash-flood forecasting in two Spanish Mediterranean catchments: a comparison of distinct hydrometeorological ensemble prediction strategies

Abstract

[eng] Hydrological Ensemble Prediction Systems (HEPSs) are becoming more and more popular methods to deal withthe meteorological and hydrological uncertainties that affect discharge forecasts. These uncertainties are particularly difficult to handle when dealing with Mediterranean flash-flood forecasting as many hydrological and meteorological factors take place and precipitation comes from small scale convective systems. In this work, the performances of distinct HEPS are compared for two heavy precipitation events that affected two different semi-arid Spanish Mediterranean catchments: the cases of the 03 November 2011 on the Llobregat River in Catalonia, and the 28 September 2012 on the Guadalentín River near in Murcia. The latter case corresponds to the IOP8 of HYMEX field campaign. The uncertainty on quantitative precipitation forecasting is sampled by using two different meteorological ensemble generation strategies. First, a convection-permitting EPS, which consists in dynamically downscaling the ECMWF-EPS directly by means of the WRF model. The second EPS strategy is based on the AROME-WMED convective-scale model. Its deterministic QPFs are perturbed based on a previous rainfall forecast error climatology and by using the probability density functions of the errors, in term of total amounts and location of the heaviest rainfalls. The population of both ensembles is of 50 members, which are used to drive the HEC-HMS and ISBA-TOP hydrological models. For each HEPS, the performance is assessed in term of the quantitative discharge forecasts. The results point out the benefits of using (i) a hydrological model when evaluating highly-variable and convective-driven precipitation fields and (ii) an EPS to better encompass these uncertainties arising from different level of the HEPS. Issues about the optimal number of ensemble members and impact of the ensemble forecasting lead time are addressed for optimal flash-flood forecasting purposes as well.