A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Mapping Slope-Failure Susceptibility for Infrastructure Management
Every year, slope failures result in millions of dollars’ worth of damages to infrastructure. Damage to roads, sewers, pipelines, bridges, and buildings can be severe—and slope failures can also endanger human life and adversely impact the environment. With the goal of addressing this problem more proactively, Barr Engineering Co. (Barr) conducted a research project to develop maps showing which of Minnesota’s many roadside slopes are most susceptible to failure. Based on a review of slope-failure research from around the world, and drawing upon established slope-failure theory, a GIS-based model was created to predict the likelihood of slope failure based on what appear to be the most critical factors: soil characteristics, topography, and rainfall. Data from existing and historical Minnesota slope failures was used to calibrate and validate the model. The maps generated by the model identify at-risk slopes and assign them one of five levels of very low, low, medium, high, and very high susceptibility to failure.
Mapping Slope-Failure Susceptibility for Infrastructure Management
Every year, slope failures result in millions of dollars’ worth of damages to infrastructure. Damage to roads, sewers, pipelines, bridges, and buildings can be severe—and slope failures can also endanger human life and adversely impact the environment. With the goal of addressing this problem more proactively, Barr Engineering Co. (Barr) conducted a research project to develop maps showing which of Minnesota’s many roadside slopes are most susceptible to failure. Based on a review of slope-failure research from around the world, and drawing upon established slope-failure theory, a GIS-based model was created to predict the likelihood of slope failure based on what appear to be the most critical factors: soil characteristics, topography, and rainfall. Data from existing and historical Minnesota slope failures was used to calibrate and validate the model. The maps generated by the model identify at-risk slopes and assign them one of five levels of very low, low, medium, high, and very high susceptibility to failure.
Mapping Slope-Failure Susceptibility for Infrastructure Management
Mohseni, Omid (author) / Strong, Mike (author) / Grosser, Aaron T. (author) / Hathaway, Charles (author) / Mielke, Aaron M. (author)
First Congress on Technical Advancement ; 2017 ; Duluth, Minnesota
2017-09-07
Conference paper
Electronic Resource
English
Slope susceptibility map for preventive measures against rainfall-induced slope failure
| Springer Verlag | 2023
Assessment of slope failure susceptibility using Fuzzy Logic
| British Library Conference Proceedings | 2005
Slope Failure Investigation Management System
| NTIS | 2013
Engineered slope failure susceptibility modelling using high spatial resolution geospatial data
| Springer Verlag | 2021