Different approaches used in hydrological modelling are compared in terms of the way each one takes the rainfall data into account. We examine the errors associated with accounting for rainfall variability, whether in hydrological modelling (distributed vs lumped models) or in computing catchment rainfall, as well as the impact of each approach on the representativeness of the parameters it uses. The database consists of 1859 rainfall events, distributed on 500 basins, located in the southeast of France with areas ranging from 6.2 to 2851 km 2 . The study uses as reference the hydrographs computed by a distributed hydrological model from radar rainfall. This allows us to compare and to test the effects of various simplifications to the process when taking rainfall information (complete rain field vs sampled rainfall) and rainfall-runoff modelling (lumped vs distributed) into account. The results appear to show that, in general, the sampling effect can lead to errors in discharge at the outlet that are as great as, or even greater than, those one would get with a fully lumped approach. We found that small catchments are more sensitive to the uncertainties in catchment rainfall input generated by sampling rainfall data as seen through a raingauge network. Conversely, the larger catchments are more sensitive to uncertainties generated when the spatial variability of rainfall events is not taken into account. These uncertainties can be compensated for relatively easily by recalibrating the parameters of the hydrological model, although such recalibrations cause the parameter in question to completely lose physical meaning.Key words rainfall distribution; radar rainfall; raingauge network; lumped modelling; distributed modelling; uncertainty Sensibilité des modèles hydrologiques aux incertitudes dues à l'information pluviométrique utiliséeRésumé Cette étude compare différentes approches utilisées en modélisation hydrologique, chaque approche étant différenciée par sa manière de prendre en compte l'information pluviométrique. Nous regardons les erreurs liées à la prise en compte de la variabilité spatiale de la pluie, à travers la modélisation hydrologique (modèles globaux ou distribués) ou à travers le calcul de la pluie de bassin. Nous regardons aussi l'impact de chaque approche sur la représentativité des paramètres qui lui sont associés. Ce travail porte sur 1859 événements pluvieux répartis sur 500 bassins versants situés dans le sud-est de la France, dans une gamme de surface allant de 6.2 à 2851 km 2 . On définit comme étant les hydrogrammes de référence, les crues modélisées par un modèle hydrologique distribué à partir de champs de pluies issus de radars météorologiques. Cela nous permet de travailler de façon relative, et de tester l'effet de différentes simplifications dans la prise en compte des processus, lors de la prise en compte de la pluie (champs de pluie complet ou échantillonnage de la pluie) et/ou lors de la modélisation hydrologique (globale ou distribuée). Les résultats montrent globale...
La méthode SHYREG a été développée pour la connaissance régionale des quantiles de débits de crue (débit de pointe et lames d'eau maximales écoulées sur les durées de 1 h à 72 h) pour les périodes de retour de 2 à 100 ans suivant une approche spatialisée. Elle associe un simulateur de pluies horaires et une modélisation simple pluie-débit, mis en oeuvre à une résolution kilométrique. Les quantiles de débits se déduisent directement des distributions de fréquence empiriques des valeurs maximales extraites des très longues chroniques de débit simulées. On obtient alors une base de quantiles de crues que l'on peut agréger à l'échelle de n'importe quel bassin versant, moyennant une règle d'abattement avec la surface. La régionalisation de la méthode a été réalisée sur la France métropolitaine, à l'exclusion de la Corse, en exploitant les données hydrométriques de 1 359 stations de jaugeage et des caractéristiques hydro-climatiques et hydrogéologiques spatialisées permettant de décrire la variabilité du paramètre saisonnier du modèle. Au final, cette régionalisation permet la connaissance des quantiles de débits de crue en tout bassin versant de la France métropolitaine avec une bonne restitution des quantiles de débit de pointe et journalier, pour les périodes de retour comprises entre 2 et 10 ans : un critère de Nash minimum de 80 % est obtenu sur les quantiles de débit de pointe pseudo-spécifique et de débit journalier spécifique des bassins versants non utilisés pour la régionalisation.The SHYREG method was developed for regional flood frequency analysis to estimate peak flow and flood discharges for various durations (1 h to 72 h) and return periods (2 to 100 years), according to a spatialized approach. For each 1-km2 pixel, the method combines an hourly rainfall model with a simple rainfall-runoff model. The discharge flood frequency estimates are deduced directly from the empirical frequency distributions for the maximum values, which are extracted from very long simulated discharge time series. This gives a database of 1-km2 gridded flood quantiles that can be aggregated for any catchment by using an areal averaging method. The method was regionalized for metropolitan France, excluding Corsica, using flow data from 1,359 gauging stations and regional hydroclimatic and hydrogeological characteristics to describe the variability of the rainfall-runoff model parameter. Such regionalization provides flood discharge quantiles for any catchment in metropolitan France for various durations and return periods. Regarding the method performance, accurate estimates of flood quantiles were produced for peak discharge and mean daily discharge for return periods of two to 10 years for gauged basins in dependent validation and cross-validation. A minimum NASH criterion of 80% is obtained for peak flow and mean daily discharge for the catchments not used in the regionalization process
Abstract. The dreadful floods of 1999, 2002 and 2003 in South of France have alerted public opinion on the need for a more efficient and a further generalized national flood-forecasting system. This is why in 2003 Irstea and Meteo-France have implemented a new warning method for flash floods, including on small watersheds, using radar rainfall data in real-time: the AIGA method. This modelling method currently provides real-time information on the magnitude of floods, but doesn't take into account the elements at risk surrounding the river streams. Its benefit for crisis management is therefore limited as it doesn't give information on the actual flood risk. To improve the relevance of the AIGA method, this paper shows the benefits of the combination of hydrological warnings with an exposure index, to be able to assess the risk of flood-related damage in real time. To complete this aim, this work presents an innovative and easily reproducible method to evaluate exposure to floods over large areas with simple land-use data. For validation purpose, a damage database has been implemented to test the relevance of both AIGA warnings and exposure levels. A case study on the floods of the 3 rd October 2015 is presented to test the effectiveness of the combination of hazard and exposure to assess the risk of flood-related damage. This combination seems to give an accurate overview of the streams at risk, where the most important amount of damage has been observed after the flood.
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