  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.
