Climate change increases the likelihood of extreme rainfall events, while ongoing urbanization leads to greater surface imperviousness. Together, these trends result in more frequent and severe urban flooding. Sustainable Urban Drainage Systems (SUDS) are implemented to enhance the resilience of urban drainage infrastructure and mitigate urban flooding. Among the available modelling approaches, coupling a one-dimensional (1D) sewer system model with a two-dimensional (2D) surface model (1D2D) is considered the most accurate method to assess urban flooding. However, the practical application of 1D2D models in the design of SUDS is limited by their high computational requirements. In comparison, a 1D urban drainage model demands significantly less computational power, allowing for many more simulation iterations to be completed within the same timeframe. This study investigates the trade-offs between 1D and 1D2D models in the design of SUDS for flood prevention. It proposes a heuristic approach that integrates both a 1D and a 1D2D model (method 1). This approach aims to leverage the speed of the 1D model and the accuracy of the 1D2D model to optimize SUDS design. The methodology was applied to an urban drainage model of Bloemendaal, the Netherlands. To evaluate the efficiency of the proposed method, its results were compared to those obtained using a second approach that relies solely on the 1D2D model (method 2). Method 1 was more effective than method 2 in reducing the number of flooded buildings. Specifically, method 1 achieved the greatest reduction in areas affected by higher flood levels (>0.30 m), while method 2 was more effective at decreasing the area exposed to lower flood levels (>0.10 m). Method 1 may assist decision makers in selecting and implementing SUDS more effectively for flood prevention, ultimately leading to more resilient urban drainage systems. Future research could expand method 1 to incorporate additional benefits of SUDS, enabling a multi-objective design approach.