Using Vessel-Based LIDAR to Quantify Coastal Erosion during El Niño and Inter-El Niño Periods in Monterey Bay, California

Vessel-based light detection and ranging (LIDAR) was employed to collect coastal topography data and to quantify the rates of erosion and spatial distribution of coastal retreat around Monterey Bay, California during the 2008–09 (non-El Niño) and 2009–10 El Niño. These data were compared with pre/post-El Niño LIDAR data from 1997–98 to assess shoreline change and to test the following hypotheses: (1) that broad-scale (km) spatial distribution of erosion rates is positively correlated with wave energy, and (2) that fine-scale erosion hot spots (segments of the coastline exhibiting considerably higher rates of erosion than adjacent areas) shift at predictable alongshore wavelengths between consecutive El Niño and inter-El Niño periods. Broad-scale erosion was found to be significantly higher during the 2009–10 El Niño vs. the 2008–09 non-El Niño period in both the south (1.8 m vs. 0.1 m average) and north bays (0.5 m vs. 0.0 m average). The broad-scale distribution of erosion rates during the 2009–10 El Niño was positively correlated with wave energy. In southern Monterey Bay, erosion rates increased along a wave energy gradient from south to north, whereas erosion and wave energy were both focused and highest at a single location in the northern bay. Fine-scale erosion hot spots were found to occur during the 1997–98 and 2009–10 El Niño and the 1998–08 inter-El Niño period. These hot spots were found to be significantly correlated at −160 m during the 1997–98 El Niño to 1998–2009 inter-El Niño periods and 100 m during the 1998–2009 inter-El Niño to 2009–10 El Niño periods in southern Monterey Bay. Hot spots that occurred during one El Niño or inter-El Niño period shifted spatially alongshore during the subsequent El Niño or inter-El Niño period. Vessel-based LIDAR proved to be effective for detecting coastal change at high spatial resolutions and revealing fine-scale patterns of shoreline retreat.