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CoSMoS Southern California v3.0 Phase 2 projections of coastal cliff retreat due to 21st century sea-level rise

Metadata Updated: October 28, 2023

This dataset contains projections of coastal cliff-retreat rates and positions for future scenarios of sea-level rise (SLR). Present-day cliff-edge positions used as the baseline for projections are also included. Projections were made using numerical and statistical models based on field observations such as historical cliff retreat rate, nearshore slope, coastal cliff height, and mean annual wave power, as part of Coastal Storm Modeling System (CoSMoS) v.3.0 Phase 2 in Southern California. Details: Cliff-retreat position projections and associated uncertainties are for scenarios of 0.25, 0.5, 0.75, 1, 1.25, 1.5, 1.75, 2, and 5 meters of SLR. Projections were made at CoSMoS cross-shore transects (CST) spaced 100 m alongshore using a baseline sea-cliff edge from 2010 (included in the dataset). Within each zip file, there are two separate datasets available: one that ignores coastal armoring, such as seawalls and revetments, and allows the cliff to retreat unimpeded (“Do Not Hold the Line”); and another that assumes that current coastal armoring will be maintained and 100% effective at stopping future cliff erosion ("Hold the Line"). Eight numerical models synthesized from literature (Trenhaile, 2000; Walkden and Hall, 2005; Trenhaile, 2009; Trenhaile, 2011; Ruggiero and others, 2011; Hackney and others, 2013) were used to make projections. All models relate breaking-wave height and period to cliff rock or unconsolidated sediment erosion. Models range in complexity from 2-D models in which the entire profile evolves, from below water to the cliff edge, to simple 1-D empirical or statistical models in which only the cliff edge evolves as a function of wave impact intensity and frequency. The projections are a robust average of all models, and the uncertainties are proportional to 1) underlying uncertainties in the model input data, such as historical cliff retreat rates, and 2) the differences between individual model forecasts at each CST so that uncertainty is larger when the models do not agree. As sea level rises, waves break closer to the sea cliff, more wave energy impacts the cliffs, cliff erosion rates accelerate. Model behavior also includes wave run-up (Stockdon and others, 2006), wave set-up that raises the water level during big-wave events, and tidal levels. The more complex 2-D models were run on idealized cliff profiles extending from about 10 m water depth to 1 kilometer inland from the cliff edge. Profiles were extracted by overlaying the cross-shore transects on a high-resolution digital elevation model (DEM) covering the Southern California study area. For all models, the presence of a beach was recorded (yes or no) for all transects using aerial photography, and the cliff toe elevation (or beach/cliff junction) was digitized from the DEM profiles. Using historic cliff edge retreat rates by Hapke and Reid (2007), unknown coefficients within the cliff-profile models were calibrated using a Monte Carlo simulation (in other words, coefficients were tuned until the modeled mean retreat rate equaled the observed mean retreat rate for a given transect). Uncertainty was tallied using a root mean squared error (RMSE) approach. The RMSE represents cumulative uncertainty from multiple sources and assumes that different sources of error will, at times, cancel each other out. It is therefore not a 'worst-case uncertainty' (in other words, a straight sum of errors) but instead an average uncertainty. Total RMSE increased with SLR rate and varied between +/- 2-3 m to a maximum of +/- 50 m for the extreme 5 m SLR scenario.
For more information on model details, data sources, and integration with other parts of the CoSMoS framework, see CoSMoS_3.0_Phase_2_Southern_California_Bight:_Summary_of_data_and_methods (available at https://www.sciencebase.gov/catalog/file/get/57f1d4f3e4b0bc0bebfee139?name=CoSMoS_SoCalv3_Phase2_summary_of_methods.pdf).

Access & Use Information

Public: This dataset is intended for public access and use. License: No license information was provided. If this work was prepared by an officer or employee of the United States government as part of that person's official duties it is considered a U.S. Government Work.

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Dates

Metadata Created Date June 1, 2023
Metadata Updated Date October 28, 2023

Metadata Source

Harvested from DOI EDI

Additional Metadata

Resource Type Dataset
Metadata Created Date June 1, 2023
Metadata Updated Date October 28, 2023
Publisher U.S. Geological Survey
Maintainer
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Identifier USGS:57f4234de4b0bc0bec033f90
Data Last Modified 20211014
Category geospatial
Public Access Level public
Bureau Code 010:12
Metadata Context https://project-open-data.cio.gov/v1.1/schema/catalog.jsonld
Metadata Catalog ID https://datainventory.doi.gov/data.json
Schema Version https://project-open-data.cio.gov/v1.1/schema
Catalog Describedby https://project-open-data.cio.gov/v1.1/schema/catalog.json
Harvest Object Id bb7a1b00-d821-49b7-a12a-453a36fcc15f
Harvest Source Id 52bfcc16-6e15-478f-809a-b1bc76f1aeda
Harvest Source Title DOI EDI
Metadata Type geospatial
Old Spatial -120.48706054569,32.472325899539,-117.01538085833,34.51524902452
Publisher Hierarchy White House > U.S. Department of the Interior > U.S. Geological Survey
Source Datajson Identifier True
Source Hash 8eb8d9e74afe1b9f37e253e307a7aebd3c896839203f55bbff4ffca89d0e06ec
Source Schema Version 1.1
Spatial {"type": "Polygon", "coordinates": -120.48706054569, 32.472325899539, -120.48706054569, 34.51524902452, -117.01538085833, 34.51524902452, -117.01538085833, 32.472325899539, -120.48706054569, 32.472325899539}

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