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Developing an Automated Geospatial Model-based Decision Support Tool for Assessing Road Culvert Vulnerability

Status

Active

Description

The research project will create a model to predict vulnerability of potentially undersized culverts and provide sorting of highest at-risk culvert-under-road sites for prioritization of culvert maintenance and/or redesign to reduce vulnerability, such as washouts. The model is based on culvert lifespan, overlaid with site-specific factors (extent of existing erosion, scour, sediment load, debris flows, soil stability, and precipitation events). The geospatial model is based on two pilot sites located on experimental forests owned by the U.S. Forest Service (Santee, South Carolina and Hubbard- Brook, New Hampshire. The model incorporates Develop Design Discharge Models (DDM) for precipitation-intensity-duration-frequency (PIDF) curves as well as site Hw/D factor to minimize risks of failure due to under sizing, flooding, and overtopping culverts (hydrologic risks) for climate resiliency. 

For More Information

Digital Object Identifier (DOI):

https://doi.org/10.1061/(ASCE)HE.1943-5584.0002052

https://doi.org/10.1016/j.envsoft.2022.105413

ORCID for the principal investigator 

0000-0003-2641-9267 (Devendra Amatya)

0000-0002-3845-4310 (Sudhanshu Panda)

Southern Research Station
Santee Experimental Forest/Center for Forest Watershed Science
3734 Highway 402
Cordesville, SC 29434