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1. Short-term patterns and processes of coastal cliff erosion in Santa Barbara, California 2020

   https://ncsu.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV1LS8NAEB5si-jFRxWsj7IHj4bmtdkESqE-akXwUgUvEnaTXVOpSbH10H_vbB60SkHE68Am2Z0h883sNzMA55wipndd28DQKzJc7kSGcHQXUWpase1LZTniezIHrKoW5ucVfk7FepXZe4av1UysAIVeELg1aKDz8cw6NPp398OHZTEkKxIrlhcYlNLnlbLg9U9a75FWvMxgF16q78vJJXqkwSrLvpN3NszbWVRdHP-0lz3YKeEn6Rf2sg8bMm3CVjkJPVk0YfM2H_W7OIDJKEFobuhfN5nmXTjTGeFpTKZFbYGckUyRKOOILyckmoyVIt2kJ3GTqOtuJ-mRcaolI1QeJ-XFhpZfaOmyKEyLDuFpcPN4NTTK2QwGdxw6NxCmKS6ZClQkuCmYE1PBhEBwpHxbp5VMhnqmVHqKmZFyqbJtXyjp28pB0KKcIyCuiCmzJeNejHGar_xYUQwJXU8iiGQ8bkGnUkw4LXpvhBUp7S2sDjLUBxkWB9mCoNJfWCKIAhmEqIhf1h7_Y-0JbNs6Dtc8P3oK9fnHpzyDuraPdmmfbagNri-_AKHG5uc

   Alessio, Paul; Keller, Edward A.

   Geomorphology (Amsterdam, Netherlands), Vol. 353, p. 106994.

   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, ... Read more

   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. •Sequential TLiDAR scans reveal rates and patterns of coastal cliff erosion.•Finds convergence in retreat rates at the base, middle, and top of the cliff•Quantitatively links wave energy flux with coastal cliff base retreat rates•Maximum retreat observed when wave energy and water levels exceed thresholds.•Identifies zones where abrasion and mechanical wave action are the dominant process. Read less

   Journal Article  |  Full Text Online

2. Beach response dynamics of a littoral cell using a 17-year single-point time series of sand... 2012

   https://ncsu.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV1bS-wwEB7cFfG8eAf3qEsefC3bpkkvIIK3VRF8UcEXCWmT7nrbirvnYf_9mWlabygiPiaQJk0mmW-Sb2YAtrVETC8E99D0yj2hw9zLQooiKv3A8MQWQZi9v8yBoPGF-fiEX1GxBrZ8LLFbF3GTbu942IJZVD6R34bZvdOzk_NXZ8jYXawEUepJKa_fuAV__qWvNFKr0CVRJfUYZ6twaS4cSbLSPf1FuGlGXVFOKNHBW-59r4p3WAW5aGI7_ugPl2ChBqVsz0nRMszY0QrM1_nRh9MVmDuuEgBPV-FhZ7i7TwzMnd5wlz07hq1lxiW2H7OyYJohtJ-Q5z-jZwFG1PoB1qKimuK-YlR8sN5TeTuaMMptz2gb2KrtWI8MIwr-PR3Ba3DVP7o8OPHqjA2eRuAz8TKD1p7xEQME2jeCa5HnockRYplCpKFvjUZElaaZTbAyMmjPJIJnsSQcE0YyXAcmMiNjbmMdGbTekiIxhURDUUQWoWWsTQd6zXKpJxeRQzVUtTvVTKSiiVQBVziRHUibVVU1rnB4QeFCfNt2HcVA6QEeuerqgtMFESJsBNWyA913svEyGkoxEInE__uLfjfgD5Y48cMDuQntyfM_uwVtkq1uLfFdaPUP9_8DwFT_Wg

   Barnard, Patrick L.; Hubbard, David M.; Dugan, Jenifer E.

   Geomorphology (Amsterdam, Netherlands), Vol. 139, pp. 588 - 598.

   A 17-year time series of near-daily sand thickness measurements at a single intertidal location was compared with 5 years of semi-annual 3-dimensional beach surveys at the same beach, and at two ot... Read more

   A 17-year time series of near-daily sand thickness measurements at a single intertidal location was compared with 5 years of semi-annual 3-dimensional beach surveys at the same beach, and at two other beaches within the same littoral cell. The daily single point measurements correlated extremely well with the mean beach elevation and shoreline position of ten high-spatial resolution beach surveys. Correlations were statistically significant at all spatial scales, even for beach surveys 10s of kilometers downcoast, and therefore variability at the single point monitoring site was representative of regional coastal behavior, allowing us to examine nearly two decades of continuous coastal evolution. The annual cycle of beach oscillations dominated the signal, typical of this region, with additional, less intense spectral peaks associated with seasonal wave energy fluctuations (~ 45 to 90 days), as well as full lunar (~ 29 days) and semi-lunar (~ 13 days; spring-neap cycle) tidal cycles. Sand thickness variability was statistically linked to wave energy with a 2 month peak lag, as well as the average of the previous 7–8 months of wave energy. Longer term anomalies in sand thickness were also apparent on time scales up to 15 months. Our analyses suggest that spatially-limited morphological data sets can be extremely valuable (with robust validation) for understanding the details of beach response to wave energy over timescales that are not resolved by typical survey intervals, as well as the regional behavior of coastal systems. Read less

   Journal Article  |  Full Text Online

3. A sand budget for the Santa Barbara Littoral Cell, California 2008

   https://ncsu.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV1LSwMxEB5siyCCjyr4rDl4dGmz2UcLRaiPtlLRgxUPHpZkk_hAq9jtwX_vZDfRKhRRCHtKwm5mNvNNMvMNwD4PEdMHge-h65V6AWepJ5hhEQ0bVPpNpSkT3w9zoO5yYX5e4eehWM8mKPrFBj5SbKwEFTQ9UaMMlc7ZoH_xuflSRn1XpRV1NXbZcjPmmWWNpvdlZo1Ndxlu3WvmMSamssF0sH09JzjMWS0cmeMfPmkFliwGJZ1CaVZhTo2qMN_La_y-V2HxMlV8ZKms12DQIWM-kkRM5J3KCIJcgqCRtO8Pr1AqnNgbi3b9_pCcP2SZSfknx-rp6cD0-cr9Mh3W4bp7Ojzue7YEg8fRdGeekJrTRgu92MhAHaalQpeWMRmJVshj4UseUi1QvIL6XGuqmEwDhBFaxI0URb8BJBAyjH0V80iiO9bUTalD9PyCSCFWjLncBM_JIHktKDYSF3v2mBQLZatlUmxsE2InqMTChML8J7jMv4zcc3JN8C8yVyN8pF4mY-zUNGehdOvfc2_DQhFKEnm0tQPl7G2idqFsdKMGpXjYq1lVrRkq0hvzPDn6AHjW5tw

   Patsch, Kiki; Griggs, Gary

   Marine Geology, Vol. 252, Issue 1, pp. 50 - 61.

   The coastline of California has been divided into a set of distinct, essentially self-contained littoral cells or beach compartments. These compartments are geographically limited and consist of a ... Read more

   The coastline of California has been divided into a set of distinct, essentially self-contained littoral cells or beach compartments. These compartments are geographically limited and consist of a series of sand sources (such as streams and eroding coastal bluffs), that provide sand to the shoreline; sand sinks (such as coastal dunes and submarine canyons) where sand is lost from the shoreline; and longshore transport or littoral drift that moves sand along the shoreline. A regional understanding of littoral cell boundaries and sand budgets can be an important tool in coastal engineering and land-use management decisions. Many harbors function as efficient sediment traps, such that average annual long-term dredging volumes should be a valuable tool for approximating littoral drift rates at specific locations within littoral cells, as well as changes in these rates over time due to natural or human impacts on the sediment budget. The Santa Barbara Littoral Cell contains three harbors with long-term dredging records and essentially unidirectional littoral drift, which provide an excellent opportunity for testing this concept. The littoral drift rates determined using this approach show a significant downdrift increase (from ~ 300,000 yds 3/yr at the Santa Barbara harbor to ~ 1,000,000 yds 3/yr at Channel Islands harbor) and are compatible with the fluvial sediment input and other components of the littoral sediment budget. Despite the damming of the four major rivers discharging into the Santa Barbara Cell, and the apparent reduction in fluvial sediment supply, there has been no systematic or significant reduction in the dredging rates at any of the harbors. Long-term dredging rates can provide useful and valuable information for better quantifying littoral cell budgets and also for documenting changes in these cells. Read less

   Journal Article  |  Full Text Online

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