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This paper presents a spatial Global Sensitivity Analysis (GSA) approach in a2D shallow water equations based High Resolution (HR) flood model. The aim of aspatial GSA is to produce sensitivity maps which are based on Sobol indexestimations. Such an approach allows to rank the effects of uncertain HRtopographic data input parameters on flood model output. The influence of thethree following parameters has been studied: the measurement error, the levelof details of above-ground elements representation and the spatialdiscretization resolution. To introduce uncertainty, a Probability DensityFunction and discrete spatial approach have been applied to generate 2, 000DEMs. Based on a 2D urban flood river event modelling, the produced sensitivitymaps highlight the major influence of modeller choices compared to HRmeasurement errors when HR topographic data are used, and the spatialvariability of the ranking. Highlights $\bullet$ Spatial GSA allowed theproduction of Sobol index maps, enhancing the relative weight of each uncertainparameter on the variability of calculated output parameter of interest. 1$\bullet$ The Sobol index maps illustrate the major influence of the modellerchoices, when using the HR topographic data in 2D hydraulic models with respectto the influence of HR dataset accuracy. $\bullet$ Added value is for modellerto better understand limits of his model. $\bullet$ Requirements and limits forthis approach are related to subjectivity of choices and to computational cost.

Spatial Global Sensitivity Analysis of High Resolution classified topographic data use in 2D urban flood modelling