Using Ground-based InSAR Data to Catagorize Levels of Rockfall Risk from an Unstable Slope
Updated: Apr 10, 2020
Gravity is one of several triggers for rockfall, and even though all stable slopes feel the constant pull of gravity, the amount of rockfall occurring during a 24-hour interval, from gravity alone, can generally be described as negligible. Alternatively, with the help of gravity, an unstable slope that is experiencing the stress of displacement, can expect a significant increase of rockfall during a 24-hour interval. Unlike many other slope monitoring technologies, ground-based InSAR (GBInSAR) provides almost total coverage of an entire slope surface, in near-real-time. The ability to see data nearly instantaneously is useful for many reasons. But in this example, the steep unstable slope presented dangerous and difficult access for the placement for any in-situ monitoring devices. More importantly, GBInSAR is highly accurate while monitoring a slope from a safe distance. One of GBInSAR's unique abilities is its high-speed presentation of displacement rates allowing for identification of individual surface areas moving at different velocities on an unstable slope surface. At some locations, the radar has been able to identify areas of displacement long before disruptive surface deformation occurs, allowing for the placement of in-situ technology in preferred locations. With the fast near-real-time presentation of GBInSAR data, displacement rates, including velocity and inverse velocity, can be temporally correlated from slope provenance to the 3D radar displacement map. The data values shown on the Level of Rockfall Risk matrix (above) were acquired while monitoring the Mud Creek Landslide in California after it had failed and during repair operations. During the post-failure monitoring, rockfall from the unstable slope was occurring daily, creating a dangerous threat to repair efforts. In an attempt to reduce some of the approaching rockfalls, several empty cargo containers were lined up, end-to-end, near the base of the head scarp to deflect approaching rocks and boulders (see arial image below). Although this helped, some of the falling rocks and boulders were able to bounce over the cargo containers into repair operations.
In addtion to the distribution of the Level of Rockfall Risk to site engineers and geologist we also provided inverse velocity time series data of selected areas on the slope. The colored dashed horizontal lines on the time series data below represents the upper limits of the corresponding colored Levels of Rockfall Risk exhibited on the matrix.
Most unstable slopes will often require multiple strategies to help reduce risk. During the Mud Creek repair project, rockfall was occurring daily. In response, the contractor employed several spotters in an attempt to identify approaching rocks and boulders visually. This strategy is often used but should be a last resort considering the advances in monitoring technology. Using the approximate provenance locations noted by the spotters, back-analysis of the radar data was performed to identify movement rates that preceded the rockfall events. In all cases, we were able to define small areas of movement that exhibited a fast transition to acceleration before a rockfall event occurred. Movement trend analysis became a forecasting tool for daily communication with the site engineer by providing accurate information regarding the level of rockfall risk at any given time.
Unfortunately, the Mud Creek landslide radar monitoring project is one of only a few government agencies and private sector projects that have employed radar monitoring compared to its overwhelming use in open-pit mines around the world. Most of the concepts and examples in this blog post, and others on this site, are currently being used in mines today. Mine sites have confirmed that consistent and accurate radar data interpretation will decrease high-wall risk to miners and equipment. Proactive slope radar monitoring should be considered where potentially unstable slopes present a dangerous threat to people and infrastructure.