نبذة مختصرة : Stormwater modelling in small-scale urban catchments is essential for integrating effective landscape design in urban development. However, limited research compares the suitability of various modelling approaches, especially post-development. This study evaluates the InVEST Urban Stormwater Retention model’s applicability in high-density residential estates in Singapore, highlighting its practicality in data-scarce settings. Alongside InVEST USR, we assessed the Storm Water Management Model and a novel sensor-based method using volumetric soil moisture to estimate retention. The sensor approach provides a cost-effective, localized means of capturing infiltration data. All three methods were tested on built-up sites and compared for runoff prediction, calibration ease, and data needs. SWMM excelled in simulating overall and peak discharge, while the sensor method offered empirical insights at finer scales. InVEST USR stood out for its flexibility and low data demands, making it ideal for rapidly urbanizing areas. The study supports integrating model-based and empirical methods for improved stormwater management.
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