The integration of Low Impact Development (LID) and real-time monitoring, modeling, and control demonstrates significant potential for optimizing qualitative and quantitative processes. Integrating Digital Twins (DT) with LID can enhance system knowledge by improving data transmission, storage, and usage. Despite the advances in LID models, existing solutions lack the scalability and adaptability needed for different techniques. This results in a critical gap in employing real-time models that evolve with new data and predict future system performance. This study aims to adapt a 2D hydrodynamic model, HydroPol2D, for LID with a 1D Richard’s infiltration and automatic calibration to be part of the digital entity of a Digital Twin of four different types of permeable pavements (Permeable Concrete, Permeable Asphalt, Plastic Grid, and Permeable Interlocking Concrete Block). The pavements are located in San Antonio and have an area of 190 m2, and the performance is being compared with a conventional pavement installed on the same site. The runoff estimation by the HydroPol2D uses a conservative mass balance approach using diffusive wave approximation to estimate the outflow of a cell to its neighbors. The model decreases process time by solving Manning's equation once per cell, then distributes the excess using Cellular Automata rules. For the infiltration module, a one-dimensional Richards infiltration using the Van Genuchten model is applied in each cell, with parameters automatically calibrated with real-time data based on system outflow.
