Predicting Slippery Slopes

April 14, 2017

Researchers Lisa Dunham, Matthew O’Banion, and Keith Cunningham have developed a new, automated technology to analyze the potential for rockfalls from cliffs onto roads and areas below. Their findings, published in Engineering Geology, will give public works and transportation departments new data that will improve their rock slide risk evaluations faster and with greater accuracy.

Rock slides are a significant concern for motorists and transportation planners, especially in areas such as the Pacific Northwest where cliff erosion and heavy precipitation endanger roads that thread around the area's mountain ranges.

“Rockfalls are a huge road maintenance issue,” said Michael Olsen, an associate professor of geomatics in the College of Engineering at Oregon State University, and co-author of the report.

“Pacific Northwest and Alaskan highways, in particular, are facing serious concerns for these hazards. A lot of our highways in mountainous regions were built in the 1950s and 60s, and the cliffs above them have been facing decades of erosion that in many places cause at least small rockfalls almost daily. At the same time traffic is getting heavier, along with increasing danger to the public and even people who monitor the problem.”

The new technology developed by scientists from the University of Washington, Oregon State University and the University of Alaska Fairbanks uses LIDAR analysis to map large areas. The mapped data can then be analyzed to evaluate the risk of rock slides. Currently, evaluations are done by observers who put themselves in danger to gather their information.

The LiDAR image of a rock slope on Alaska’s Glenn Highway (above) shows the “kinetic energy” of the slope, with red indicating a higher hazard from rockfalls.

"Transportation agencies and infrastructure providers are increasingly seeking ways to improve the reliability and safety of their systems, while at the same time reducing costs," said Joe Wartman, associate professor of civil and environmental engineering at the University of Washington, and corresponding author of the study.

"As a low-cost, high-resolution landslide hazard assessment system, our rockfall activity index methodology makes a significant step toward improving both protection and efficiency."

The study, based on some examples in southern Alaska, showed the new system could evaluate rockfalls in ways that very closely matched the dangers actually experienced. It produces data on the "energy release" to be expected from a given cliff, per year, that can be used to identify the cliffs and roads at highest risk and prioritize available mitigation budgets to most cost-effectively protect public safety.

"This should improve and speed assessments, reduce the risks to people doing them, and hopefully identify the most serious problems before we have a catastrophic failure," Olsen said.

The technology is now complete and ready for use, researchers said, although they are continuing to develop its potential, possibly with the use of flying drones to expand the data that can be obtained.