Three-dimensional Drainage Infrastructure Modeling for Flood Vulnerability in Southeast Texas

Urban flooding poses escalating risks to transportation infrastructure in low-lying, flood-prone regions, underscoring the need for scalable, elevation-aware assessment frameworks. This study evaluates the flood vulnerability of drainage infrastructure in Southeast Texas by developing an automated 3D modeling framework that integrates digital elevation models, airborne lidar data, and water surface elevation scenarios through a fully automated pipeline incorporating large-language-model–assisted data standardization, Python/ArcPy geometry generation, and attribute-driven computer-generated architecture procedural modeling. Using ArcGIS Pro and CityEngine, 842 culverts and 223 bridges were modeled following quality-control filtering, and flood exposure was quantified using an elevation-differencing metric for 100- and 500-year flood events. The results indicate that fewer than 2% of culverts remain above water during a 100-year flood, while fewer than 1% remain accessible under a 500-year event, with median inundation depths of approximately 0.54 and 0.90 m, respectively. The proposed workflow reduces manual processing time by approximately 80% while preserving vertical consistency, providing a transferable and uncertainty-aware framework to support regional flood-resilience planning and future integration with hydrodynamic models. The code and supporting materials associated with this study are publicly available via GitHub at: aibironke/3D-Drainage-Flood-Vulnerability.