Posted on February 23, 2021
Although there have been numerous studies examining the causes of erosion in rocky coastal bluffs, research that manages to both separate wave effects from precipitation effects and quantify them is rare. Adam Young, a coastal geomorphologist at the Scripps Institution of Oceanography and lead author on the new study, chalks this up to how infrequently cliff data are usually gathered. “Typically, we only had one or two lidar surveys a year,” Young said. “Those are great, but they only provide seasonally averaged information.”
Data collected only at seasonal timescales are a problem when you’re trying to tease out the details of cliff erosion processes. “In studies of coastal systems, especially those that change regularly, like beaches and cliffs, it really pays off to measure them frequently,” explained Jonathan Warrick, a research geologist with the U.S. Geological Survey who was not part of the new study. This problem with seasonal timescales is particularly relevant in places like Southern California, where, as Young noted in an email, “both rainfall and increased wave action occur in the winter. Therefore, higher frequency surveys that capture individual rainfall and large wave events are needed to separate and quantify how these processes drive cliff erosion.”
For their new study, published online in November in the journal Geomorphology, Young and his research team mapped a 2.5-kilometer (1.5-mile) stretch of cliffs and adjacent beaches an average of once per week for 3 years. The researchers gathered the bulk of their richly detailed data set by using a truck-mounted lidar system, which they drove slowly along the beach in multiple passes, aiming the lidar system at different angles to precisely capture all the variations of the cliff face and the beach elevation. They supplemented their lidar data with wave pressure sensors they buried along the beach, as well as rainfall data provided by their local weather station and data from the nearby La Jolla tide gauge.
New Findings from Improved Data Collection
The combination of more frequent data collection and a better remote sensing system—the researchers’ truck-mounted lidar system was an upgrade from the GPS and all-terrain vehicles they had previously been using—enabled scientists to quantify the relationships between wave-driven and rainfall-driven cliff erosion. Their analyses of the data found that erosion of the lower part of the cliff was more strongly correlated with wave impacts and that rainfall was more closely correlated with erosion of the upper cliff.“In our coastal [research] community, we’ve long asked the question about why cliff change occurs and what are the driving forces,” Warrick said. He explained that although scientists have understood that “ocean- and land-based processes” are the primary processes that contribute to cliff failure, “it’s been challenging to measure those competing processes and compare them.” Speaking about Young’s findings, Warrick stated, “[This study] really helps us answer some of those questions that we’ve been asking for decades in our field. And one of the neat things about it is that it showed it’s not an either-or question. It’s not a question about whether it’s waves or hydrology [eroding a cliff]. These two dominant processes are working together.”
Being able to distinguish between wave effects and rainfall effects is important when it comes to modeling and forecasting cliff erosion, Young explained. “Currently, most models either use waves or rainfall to drive cliff erosion, but usually not combined together. In many locations such as Southern California, both processes are important.” He clarified by email, “With the relationships quantified in this study, we can estimate how much erosion is going to occur for a particular storm forecast at the study site.” Young also specified that this new information enables scientists to forecast how high on the cliff’s profile the erosion from an incoming storm is likely to occur.
The team’s research and future work like it could also be influential for cliff modeling that looks at longer timescales, such as projecting how quickly and how far coastal cliffs will retreat. As Warrick explained, “having an understanding like this and quantifying it is essential for [cliff change] forecasts. Ultimately, we would like to know how much erosion [to expect] over the next century—whether it is ten meters or a hundred meters—and these studies are going to help us do those forecasts in the future.”
The new study was funded by the California Department of Parks and Recreation and by the U.S. Army Corps of Engineers.
—Jady Carmichael (@jadycarmichael), Science Writer
