Assessing Culvert Vulnerability to Floods and Flood-induced Erosion and Debris Flow with Climate and Upland Loading Vulnerability Evaluation and Risk Analysis Tool (CULVERT)
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Extreme precipitation events are increasingly compromising culvert infrastructure on forest roads, making it more vulnerable to floods, erosion, and post-wildfire debris flows. We developed the Climate and Upland Loading Vulnerability Evaluation and Risk analysis Tool (CULVERT)—a dynamic, web-based decision support system or web-GIS application, to assess culvert infrastructure risks against flooding. CULVERT integrates high-resolution geospatial data (e.g., sub-meter LiDAR-derived DEMs), nonstationary regional frequency analysis, the empirical Rational Method, the Graphical Peak Discharge method, and both empirical and process-based erosion models (e.g., Modified Universal Soil Loss Equation, Water Erosion Prediction Project). It also incorporates qualitative spatial hydrogeomorphological models such as Stream Bank Erosion Vulnerability Assessment and the Watershed Debris Flow Model), to assess site-specific culvert vulnerabilities under current and projected climate conditions.
Operating at ≥1m spatial resolution, the tool enables precise watershed delineation and hydro-enforced terrain modeling, empowering practitioners with minimal GIS expertise to conduct complex hydrologic and hydrogeomorphologic assessments. Its computationally efficient parallelized architecture executes multiple models simultaneously, optimizing performance and tailoring output to individual culvert locations within the area of interest. CULVERT fetches real-time and forecast data from open-source APIs such as NOAA (climate) and gSSURGO (soil), creating a fully automated and dynamic framework, dashboard, and final report that minimizes manual preprocessing. Unlike basin-scale or general GIS-based approaches, CULVERT targets culvert-scale infrastructure in headwater catchments with globally scalable applicability. Initial implementations at the low-gradient Santee Experimental Forest (SC) and high-gradient Hubbard Brook Experimental Forest (NH) validate its operational utility in prioritizing restoration efforts and supporting climate-resilient infrastructure planning. This study presents the tool’s scientific foundations, system architecture, and application outcomes, underscoring its significant role for land managers and engineers to handle flood hazard mitigation of road culvert infrastructure.