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The Impacts of the 2015/2016 El Niño on California’s Sandy Beaches

  • Author(s): Smith, Schuyler Ann
  • Advisor(s): Edwards, Christopher
  • Barnard, Patrick
  • et al.
Abstract

Abstract

The Impacts of the 2015/2016 El Niño on California’s Sandy Beaches

By Schuyler Smith

The El Niño Southern Oscillation is the most dominant mode of interannual climate variability in the Pacific. The 2015/2016 El Niño event was one of the strongest of the last 145 years, resulting in anomalously high wave energy across the U.S. West Coast, and record coastal erosion for many California beaches (Barnard et al., 2017). Currently, 26 million people live in California’s coastal counties (2010 U.S. Census), and over 600,000 people in California will likely be at risk of coastal flooding by the end of this century due to projected sea level rise and storms (Barnard et al., 2019). To better manage our coastal resources, it is critical that we understand the impacts of both short-term climate variability and long-term climate impacts across the varied coastal settings of California. This study is the first to quantify the effects of one of the strongest El Niño events in the historical record across the entire coast of California, represented by 8000, 50-m spaced shore-normal transects across sandy beaches along the length of the state’s shoreline.

The response of sandy shorelines to the extreme El Niño winter of 2015/2016 is quantified in the context of net shoreline movement, using the mean high water (MHW) line as a shoreline proxy. MHW contours were extracted from Light Detection and Ranging (LiDAR) digital elevation models (DEMS) from the Oregon border to Mexico using ArcGIS, to represent the 1998/2002, 2015 and 2016 shorelines. Both net shoreline movement values (from fall of 2015 to spring of 2016) and long-term end-point rates of change (1998/2002-2016) were calculated. Satellite-derived long-term (1984-2019) rates of shoreline change acquired from Luijendijk et al. (2018) are summarized for comparison. To determine the influence of wave energy on the coastal response observed here, wave energy flux values for the El Niño winter were calculated at the 20 m depth contour every 100 m along the entire California coastline using hindcast data generated by O'Reilly et al. (2016).

We find that central and northern California experienced the most sandy beach erosion during the El Niño winter, with 96% of analyzed beaches in Central California eroding (mean = 45.7 m of erosion), compared to 89% in northern California (mean = 25.5 m of erosion), and 79% in southern California (mean = 9.7 m of erosion). Although local beach response was highly variable, much of the erosion was observed at river mouths, and on the southern side of structures impeding littoral drift, with accretion observed on the northern or upcoast side of these structures. Within west-facing embayments, more extreme erosion was observed in the north than in the south. These erosional patterns contrast to those of typical El Niño events, when the direction of alongshore transport has been observed as south to north, and accretion occurs in the northern end of embayments. In the long-term (1998/2002-2016), southern California and central California beaches are moderately accreting, while northern California is eroding on average at 79 cm per year. A significant correlation was found between cumulative wave energy flux and shoreline change during the El Niño winter across the state of California (R2 = -0.45, P<0.001). The correlation is lower (-0.25, P<0.001) for the 2015/2016 winter cumulative wave energy flux anomaly and shoreline change in southern California. After assessing the impact of the 2015/2016 El Niño event, spatial patterns indicate that an unusual, more northerly wave direction, extreme wave energy, and coastline orientation were key factors in the observed shoreline response. This response was markedly different from the classic El Niños of 1982-83 and 1997-98, where more southerly storm tracks and southerly wave directions were key factors controlling shoreline behavior.

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