As urban environments become increasingly complex and precipitation events more extreme, managing stormwater is a growing challenge. Localised flash floods can occur unexpectedly, leading to significant risks for communities and putting stress on traditional drainage systems. Analysing these issues requires high-precision spatial data and efficient computational algorithms to predict risk, identify problematic locations and evaluate possible mitigation strategies. Nature-based solutions, such as green roofs, permeable pavements, and the restoration of natural waterways, have emerged as well-suited strategies for mitigating urban stormwater challenges [1]. To support planning and assessment of these strategies, robust modelling tools are essential. To this end, we extend the open-software package called Surface Water Integrated Modelling (SWIM) [2] with capabilities to model and evaluate the effects of nature-based interventions in urban settings. SWIM employs a topography-based approach that facilitates rapid simulations to evaluate water flow patterns and accumulation, with particular attention to the enhancements provided by nature-based interventions. This requires extending the topographical analysis with capabilities to model infiltration processes and temporal developments, as well as integrating data on urban infrastructure (e.g., walls, drains, culverts, permeable surfaces) and rainfall events. We also address simplified estimation of local flow intensities to minimise the need of more costly simulations. The methodology allows for efficient workflows, enabling the use of ensemble simulations to quantify uncertainties in predictions, or for calibration. This is particularly important in urban environments where small-scale variations can significantly impact flood risk.