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