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Technologies such as aerial photogrammetry allow production of 3D topographicdata including complex environments such as urban areas. Therefore, it ispossible to create High Resolution (HR) Digital Elevation Models (DEM)incorporating thin above ground elements influencing overland flow paths. Eventhough this category of big data has a high level of accuracy, there are stillerrors in measurements and hypothesis under DEM elaboration. Moreover,operators look for optimizing spatial discretization resolution in order toimprove flood models computation time. Errors in measurement, errors in DEMgeneration, and operator choices for inclusion of this data within 2D hydraulicmodel, might influence results of flood models simulations. These errors andhypothesis may influence significantly flood modelling results variability. Thepurpose of this study is to investigate uncertainties related to (i) the ownerror of high resolution topographic data, and (ii) the modeller choices whenincluding topographic data in hydraulic codes. The aim is to perform a GlobalSensitivity Analysis (GSA) which goes through a Monte-Carlo uncertaintypropagation, to quantify impact of uncertainties, followed by a Sobol' indicescomputation, to rank influence of identified parameters on result variability.A process using a coupling of an environment for parametric computation(Prom{\'e}th{\'e}e) and a code relying on 2D shallow water equations (FullSWOF2D) has been developed (P-FS tool). The study has been performed over the lowerpart of the Var river valley using the estimated hydrograph of 1994 floodevent. HR topographic data has been made available for the study area, which is17.5 km 2 , by Nice municipality. Three uncertain parameters were studied: themeasurement error (var. E), the level of details of above-ground elementrepresentation in DEM (buildings, sidewalks, etc.) (var. S), and the spatialdiscretization resolution (grid cell size for regular mesh) (var. R). Parametervar. E follows a probability density function, whereas parameters var. S andvar. R. are discrete operator choices. Combining these parameters, a databaseof 2, 000 simulations has been produced using P-FS tool implemented on a highperformance computing structure. In our study case, the output of interest isthe maximal

Global Sensitivity Analysis with 2D Hydraulic Codes: Application on Uncertainties Related to High-Resolution Topographic Data