Abstract

Sequential terrestrial LiDAR scans and 3D volumetric change were used to document coastal cliff erosion at several sites along the coast of Santa Barbara, California. Retreat rates along the base, middle, and cliff top were calculated for six different scans throughout the El Niño of 2015–16 to quantitatively link wave action to cliff base erosion, and two seasonal scans were taken during 2017 to investigate patterns in erosion and retreat rates. Retreat rates along the cliff base, middle, and top converged over the course of the study period and observations and patterns in erosion help characterize the fundamental mechanisms that govern the retreat of soft shale cliffs. The base and middle of the cliff preferentially eroded during high-energy swell events and are strongly coupled, whereas cliff top erosion is temporally variable and retreat rates increased with higher seasonal rainfall totals. We observe that the cliff base experiences erosion from both abrasion and mechanical wave action, but the dominant processes is segregated by elevation above the cliff toe. Abrasion was found to be the dominant processes at elevations up to ~0.8 m above the cliff toe, whereas block removal from mechanical wave action was dominant at elevations above 0.8 m. Threshold behavior was observed for cliff base retreat rates, and Spearman correlation coefficients suggest strong relationships with the sum of the wave energy flux imparted to the cliff base (R2 = 0.84), the sum of the wave energy flux >35,000 W/m (R2 = 0.82), and the average total water level above the cliff toe (R2 = 0.85). Threshold behavior and maximum retreat rates occurred when average total water levels were >0.8 m above the cliff toe. Seasonal Schmidt-hammer measurements suggest that energy thresholds are modulated by weathering rates which remain poorly understood. These thresholds, when exceeded, produced the highest cliff base retreat rates during the study period and reinforce the expectation that coastal cliff retreat rates will increase with rising sea levels.

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