Sustainable Urban Drainage Systems (SUDs) are increasingly used to alleviate the sewer system and thus contribute to reduce combined sewer overflows (CSO). However, this approach raises several questions about the minimal number of SUDs, their types, and optimal locations to achieve a significant decreasing of CSO at the catchment scale. Those questions are often appraised through modelling approaches and scenario analyses. However, hydrological and hydraulic (HH) models require a minimal description of the territory and its characteristics, notably the catchment and sub-catchment delineation, and the appropriate level of sewer network plan. Several catchment delimitation methods already exist (Li et al., 2020). A first group of methods are generally applied to a single data source. Delimitation can be made with land use, mostly consisting of urban block divisions according to existing roads (Khurelbaatar et al., 2021); network sewer plans (Ghosh and Hellweger, 2012); or topography. For example, the “D8 algorithm” is used quite frequently, and is based on the Voronoïi geometric division principle. A second group of methods, referred as “hybrid” partitioning methods, sequentially uses the different data sources to identify sub-catchments. The present study investigates the effect of different strategies for catchment and sub-catchment delineation – and when applicable, sewer network identification – based on different spatial data: topography and/or sewer network plans and/or land use data. Four scenarios of data availability are proposed and tested in two different sites, followed by HH modelling to compare the computed flow dynamics. The final objective is to test solutions for CSO mitigation.