Soil erosion and slope instability issues are a major concern for New England state Departments of Transportation (DOT), roadway planners, and designers, impacting the cost to maintain transportation networks and other critical infrastructure. Effective screening tools used for modeling, monitoring, and forecasting erosion can aid in assessing erosion and slope failure susceptibility, which is critical for regional operations and planning.
GZA developed a screening-level tool to identify roadways vulnerability to erosion and slope failures based on a number of factors, using the latest GIS Enterprise technology. The work is being performed in collaboration with the New England Transportation Consortium (NETC). The project objective was to develop a multi-scale, multi-season land-based erosion and landslide modeling and monitoring toolkit for infrastructure management for all the New England states (including Maine, New Hampshire, Vermont, Massachusetts, Rhode Island, and Connecticut).
The prototype Esri ArcGIS toolkit was developed for the MaineDOT based on Maine’s state-wide GIS data such as topography, land use, surficial geology, and roadway system inventory. Various environmental parameters were considered as risk factors for roadways, including proximity to surface water body, proximity to the 100-year floodplain, and slope geometric information.
A large set of slope stability simulations were assembled to capture key geotechnical parameters including soil type, material strength, and groundwater depth. This set formed the basis of a “Response Function” that was used to interpolate to all the grid cells in the study area. The end deliverables of this project, i.e., the Esri GIS web viewer, included multiple risk analysis data layers for users to interact with and identify high, medium, and low hazard areas, for screening, analysis, and planning purposes for the Maine DOT.
The innovative approach developed for this project is applicable to other states or even regions and adaptable for future improvements such as inclusion of climate change considerations.
