UCSD - University of California - San Diego

07/09/2026 | Press release | Distributed by Public on 07/09/2026 12:12

New Report Outlines Potential to Predict Coastal Cliff Collapses

Published Date

July 09, 2026

Article Content

Key Takeaways

  • Following a four-year study of San Diego County coastal cliffs, Scripps Oceanography scientists found that a network of in-ground sensors can provide a reliable warning of impending, dangerous landslides with hours to days notice.
  • These promising findings could be used by emergency response authorities to create an actionable warning system to protect the public from hazardous cliff failures.

Following a four-year study, scientists at UC San Diego's Scripps Institution of Oceanography released a new report to determine if an early warning system could potentially detect a landslide before it happens. The "California Coastal Landslide Early Warning Research" report found that a network of in-ground sensors can provide a reliable warning of impending, dangerous landslides with hours to days notice, but that more work is needed to formalize the findings into an actionable warning system.

Roughly 70% of the California coast is made up of eroding coastal cliffs. These cliffs are home to important infrastructure like highways, railways, coastal access points, energy facilities, and structures, and can be deadly to beachgoers when a cliff collapse occurs.

In August 2019, at Grandview Beach in Encinitas, Calif., three women were killed following a 30-foot by 25-foot section of a cliff collapsing onto the beach. Other fatal events have occurred throughout the state in Big Sur, Santa Barbara, Point Reyes and San Francisco. The tragedy in Encinitas inspired California Assemblymember Tasha Boerner, whose district includes San Diego's coastal North County, to introduce a bill, AB 66, and secure funding through the State budget, to enhance coastal monitoring to better understand the timing of bluff failures and help inform recommendations towards the development of a potential early landslide warning system.

Many of California's eroding coastal bluffs contain critical cliff top infrastructure including highways, railways, power plants, wastewater facilities, military installations, housing, businesses, and more. Image credit: Adam Young/Scripps Institution of Oceanography.

"Bluff collapses are a constant threat to coastal neighborhoods in my district and across the California coast, presenting the risk of fatalities, injuries, and millions of dollars in damage to vital infrastructure," said Assemblymember Boerner (D-Encinitas). "With this study completed, the science is clear: We can save lives, protect our coastal economy, and vital transportation networks in the face of sea-level rise with a bluff-collapse early warning notification system. This could not have been possible without Dr. Adam Young and the rest of the team at Scripps Institution of Oceanography."

A Scripps technician installs a shallow in-ground sensor in Del Mar. Image credit: Scripps Institution of Oceanography.

Instrumenting the Cliff Sites

To conduct the research, Scripps coastal geomorphologist Adam Young and geophysicist Mark Zumberge took a two-fold approach. They instrumented key sites with advanced in-ground monitoring technology, installing a range of sensors of varying costs and sensitivity. They expanded coastal lidar surveys, using the advanced laser imaging technology to map the surface elevation to precisely track the state of cliffs and beaches before and after failures.

The sites included Beacon's Beach in Encinitas, a beach with a public access trail on an intermittently moving complex landslide; Railway Corridor in Del Mar, a critical coastal rail corridor overlooking a beach below unstable bluffs; and San Elijo State Beach, a beach with eroding cliffs and a cliff top campground, park facilities and public access points.

"While others had reported signals that preceded landslides, we wondered what we would see in this environment," said Zumberge, who has spent decades developing instrumentation to take precise measurements of earthquakes. "Scientists have been trying to predict earthquakes for a very long time. This study provided a unique opportunity to leverage what we've learned with earthquakes and apply it for these coastal hazards."

The sensor technology used included tiltmeters, instruments often used to measure the movement of earthquake faults. Those can measure ground tilting to an accuracy of 10 micrometers over a one-meter baseline, roughly 1/8 the width of a human hair. Extensometers were also installed perpendicular to the cliff edge at Beacon's Beach and Del Mar. These sensors are fiber optic cables that extend or compress if any ground deformation occurs, the movement of which can be detected up to a nanometer, or one-billionth of a meter. Other instruments installed at select sites included seismometers to monitor shaking in the cliff face, GPS monuments to measure ongoing change in the position of the cliff top, and wave pressure sensors installed in the beach to measure the intensity of waves reaching the base of cliffs.

During the study period, the team tracked five collapses - two at Del Mar and three at San Elijo State Beach. In all cases, the sensors detected movement of cliffs several hours to days prior to collapse. The landslides ranged in size from a few to several hundred cubic yards of material, typically falling from the upper cliff down to the beach below.

At around 5 a.m. on April 21, 2024, an estimated 200 tons of material fell to the beach from the cliffs in Del Mar. A tiltmeter sending data in real time alerted Scripps researchers several days before the failure that a landslide was highly likely. Image credit: Adam Young/Coastal Processes Group.

"Our team selected locations where we anticipated cliff activity could happen, but we had no guarantee," said Young. "The five events provided vital data to inform our findings that this type of monitoring can enable prediction."

One of the most significant collapses Young and Zumberge measured was a Del Mar failure event on April 21, 2024. During a maintenance visit to the site, the team observed a new, small crack in the cliff top, about 0.1 inches wide, extending 30 feet parallel to the cliff edge. Over the next several weeks, the sensors measured that the crack widened by 0.015 inches per day, a rate not visible to the human eye. Several rain events also happened during that time, and on April 19, the tilt sensor measurements were accelerating at a rate the science team determined would lead to imminent failure, and coastal managers were notified. On April 21st at 5:00 a.m. the cliff failure occurred, and an estimated 200 tons of material fell on the beach below.

At Beacon's Beach, landslides closed the beach trail in May 2022. Complications obtaining permits delayed the installation of the most sensitive sensors, so the time-series data does not become available until 2025. The report concluded that a longer observation period would be needed at Beacon's Beach to determine if the high-sensitivity and more costly sensors are useful in predicting failures at the site.

Before and after oblique images of the landslide with red triangles representing the locations of MEMS tilt sensors. Image credit: Scripps Institution of Oceanography

Laser Mapping of Cliffs

Rainfall and waves are primary drivers of coastal cliff erosion. Waves erode the base and cause cliff steepening and instability. Rainfall and groundwater can then trigger landslides in the unstable cliffs. To better understand the timing of cliff failure after rainfall, the team conducted weekly lidar cliff mapping from 2022-2025 from Torrey Pines State Beach to Encinitas.

Using a truck-mounted mobile lidar system and drone photogrammetry provided detailed spatial maps, allowing scientists to track movement and change on the cliffs. Rain gauges near the study sites provided daily rainfall observations data. The team's analysis of the data provides preliminary environmental thresholds associated with elevated coastal landslide activity and a foundation for a regional probabilistic coastal landslide warning system. For example, a system could be developed to issue warnings when rainfall thresholds are exceeded. The mobile lidar instrumentation used in this study was purchased using Community Project Funding supported by U.S. Rep. Mike Levin (CA-49).

A truck-mounted LIDAR system allowed scientists to track movement and change on the cliffs. Photo credit: Erik Jepsen/ UC San Diego.

A Warning System: Turning the Data into Action

Now that warning signals have been detected, the report cites the need for the State of California to establish a process where local emergency response authorities can take action if monitoring indicates that imminent failure is likely. The report identifies the need for a plan of action for coastal managers, lifeguards and marine safety units, rail operators, and other stakeholders to develop protocols to respond once a signal is detected. Possible actions could include temporary beach closure, temporary closure of cliff top areas, controlled removal of cliff sections likely to fail, adding signage to at-risk locations, structural stabilization, and more.

Additional public education is also recommended to increase awareness of the hazards of cliff dangers. This could take the form of public service announcements, pop-up education events at beaches, social media campaigns, education programs targeted towards youth and junior lifeguard programs, and lifeguard and State Parks staff training programs.

As part of the study, the researchers also developed an experiential smartphone app to forecast beach width at Torrey Pines State Beach. Adequate beach width provides beachgoers enough distance to stay safely away from cliffs. The forecast used data from the most recent Scripps lidar beach survey, and the nearshore wave and tide height forecasts to predict beach width. The tool provided hourly beach width forecasts three days in advance, showing a test case of how the data could be applied to improve beach safety.

Continued Research

The study area profiled in the report was limited to north San Diego County. The report authors say numerous other coastal locations in California pose threats to safety and infrastructure, and would benefit from further study. Example locations could include Orange County, Palos Verdes, Santa Barbara County, Big Sur, Santa Cruz, Pacifica and others.

The authors would also like to extend the period of study of the San Diego research locations. U.S. Rep. Mike Levin (CA-49) submitted a Community Project Funding request that would support a one-time extension of the existing sites. The request is pending passage of a final spending package for Fiscal Year 2027.

"Some of the most significant landslides occur infrequently, and additional long-term observations are needed to better understand them," said Young.

While the report concluded that prediction is possible, identifying the best observation strategy and measurement tools - those that balance sensitivity, deployment coverage and cost - will become clearer as more data are collected.

Read the full report here: California Coastal Landslide Early Warning Research.

In April, the data was also published in the study "Real-Time Ground Deformation Records of Coastal Cliff Failures in San Diego County, California" in the Journal of Geophysical Research: Earth Surface.

Learn more about research and education at UC San Diego in: Climate Change

"Some of the most significant landslides occur infrequently, and additional long-term observations are needed to better understand them." Adam Young, Coastal Geomorphologist at UC San Diego's Scripps Institution of Oceanography
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