Data quality and availability is a common problem in many modelling studies dealing with regional, spatially distributed case studies. This is true for both, urban development models and urban water management models. As current research in urban water management more and more tries to benefit from an integrated view of the performance of water networks in the context of dynamically growing and shrinking cities, this problem of data scarcity increases. Having different applications with different levels of details available, the question arises which data (and which temporal and spatial resolution) is really necessary to be collected in a modeling study with a certain modeling aim. This work tackles this question by running an integrated urban development and urban water model with different detail levels of input data. The approach uses variations in quality (temporal and spatial) of input data for simulating urban development (population data & projections) and given data on existing city structures (e.g. buildings, road network). Permutations of the given information propagated through the urban development model represent several scenarios to calculate parameters for the urban water models (effective impervious area (EIA), dry weather flow (DWF) and water supply demand (WSD)) As urban water models in this study SWMM (storm water management model) for drainage systems and EPAnet for water supply systems is used. Consequently the impact of the input data variation on the results of the hydraulic and hydrodynamic simulations is statistically analyzed using different performance indicators: EIA in relation to ponded volume, DWF to flow velocities and WSD to system pressure clustered by input data. For comparison reasons simulation runs with a well-established urban development model are conducted