Description

The research project will create a fully dynamic web application to predict vulnerability of potentially undersized and geomorphologically hazardous culverts. This web application will be fully automated to sort risk associated with culvert-under-road sites to support prioritization of culvert maintenance and/or redesign to reduce vulnerability, such as washouts. Multiple hydrologic and hydrogeospatial models will be used in this web application, with peer-reviewed methodologies ensuring prediction reliability. These models will overlay culvert lifespan with site-specific factors (peak flood discharge, extent of existing erosion, scour, sediment load, debris flows, soil stability, and precipitation events) to determine the culvert vulnerability. The project will evaluate the model on pilot sites in U.S. Forest Service experimental forests (Santee, South Carolina and Hubbard-Brook, New Hampshire). The application will incorporate hydrologic, hydro-geomorphologic, and debris-flow models incorporating precipitation-intensity-duration-frequency (PIDF) curves as well as site Hw/D factor to minimize risks of failure due to under-sizing, flooding, overtopping culverts (hydrologic risks) and scour, erosion/sediment buildup (geomorphologic risks) for infrastructure resiliency.

Phase 2 of this project will expand the research to Forest Service Pacific Northwest and Southwest sites experiencing frequent and intense wildfires This project will enhance a web-GIS-based online interactive tool for assessment of culverts that could be vulnerable to precipitation and post-wildfire flood-debris-flow. In cooperation with USGS, NFLs, USEPA, NPA, and academia, this project will use high resolution USGS road-stream crossings database, LIDAR, soil moisture, hydrometeorologic, and geomorphologic data/models.

Status 

Phase 1: In Progress

Phase 2: Not Started

Deliverables

Report: Hydro-geomorphological assessment of culvert vulnerability to flood-induced soil erosion using an ensemble modeling approach

Culvert Vulnerability Assessment Tool: pending

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
https://orcid.org/0000-0003-2641-9267 (Devendra Amatya)
https://orcid.org/0000-0002-3845-4310 (Sudhanshu Panda)