Potential of a probabilistic hydrometeorological forecasting approach for the 28 September 2012 extreme flash flood in Murcia, Spain
Published on Dec 1, 2015in Atmospheric Research4.676
· DOI :10.1016/J.ATMOSRES.2015.06.012
Abstract An improved understanding, modeling and forecasting of hydrometeorological extremes over the flood-prone Western Mediterranean region is one of the milestones of the international HyMeX program. A set of severe hydrometeorological episodes affected various basins across south and eastern Mediterranean Spain from 27 to 29 September 2012. Flooding was particularly catastrophic in Andalusia and Murcia, where 10 fatalities occurred and material losses were estimated at 120 M€. The predictability bounds set by the type and scales of the processes involved in such high-impact episodes require the explicit representation of uncertainty in the hydrometeorological forecasting chain. A short-range ensemble prediction system (EPS) provides the optimal framework to generate risk-based forecasts supporting valuable early warning procedures and mitigation measures. We explore the potential of this probabilistic forecasting approach on the 28 September 2012 flash flood in the Guadalentin river basin, a medium-sized catchment located in Murcia, southeastern Spain. After a rigorous calibration with rain-gauge data, the hydrological response of the basin to this flooding is accurately simulated by the Hydrologic Engineering Center's Hydrological Modeling System runoff model. Then, we explore the uncertainty transference from a collection of mesoscale meteorological deterministic and probabilistic 48 h predictions provided by the Weather Research and Forecasting (WRF) model. The meteorological simulations are nested within the global EPS of the European Centre for Medium-Range Weather Forecasts, therefore inheriting the spread of the global system and providing probabilistic high-resolution precipitation structures to the hydrological model. By assuming the calibrated model as a good representation of a perfect hydrological model for this event, it becomes an advanced and user-oriented verification tool for quantitative precipitation forecasts. Results highlight the benefits of accounting for uncertainties in the precipitation forecasts and the value of the proposed set-up for the short-range prediction of quantitative discharge forecasts. The warn-on-forecast approach is shown to be possible within a probabilistic hydrometeorological forecasting chain for basins as small and fast-responsive as the Guadalentin basin, proving to be suitable for civil protection warning procedures.