UTC 2022 Funding - Cycle 2 Research Projects

Project Number: CY2-OSU-OU-02
Project Title: Coupling Remote Sensing and Machine Learning to Improve Culvert Inventories for Climate Resilient Infrastructure and Aquatic Connectivity
Performing Institutions: Oklahoma State University and University of Oklahoma
Principal Investigators: Jaime Schussler, Oklahoma State University; Thomas Neeson, University of Oklahoma
Proposed Start and End Date: 10/01/2024 to 01/15/2026
Project Description: Culverts are critical infrastructure that provide our transportation network with a safe interface with surface waters; however, only 19% of total road-stream intersections in Oklahoma have a documented hydraulic structure, such as a culvert. Additionally, culverts that are inadequately designed or aged are at risk of causing flooding or even failure during high flow events, which could significantly impact transportation connectivity and safety. The lack of a comprehensive database of the location and condition of culverts in OK severely limits strategic investment in resilient transportation infrastructure and the restoration of aquatic ecosystem connectivity, particularly in rural and tribal areas. This project aims to identify and improve culvert inventory, inspection, and prioritization methods to improve the resilience and aquatic connectivity of culverts using remotely sensed, publicly available data.
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