Published In

Marine Geology

Document Type

Article

Publication Date

9-2021

Subjects

Marine transgression, Stratigraphic geology, Bioaccumulation

Abstract

The U.S. Pacific Northwest (PNW) coastline (1000 km) has been analyzed for conditions that could impact beach erosion from potential near-future (100 year) sea level rise (SLR). Heavy mineral analysis of river, beach, and shelf samples (n = 105) establish the sources of the beach deposits. River bedload discharge and intervening estuarine sinks for river sand supplies (n = 31) were normalized to the one century time interval. Twenty-six subcell beaches (657 km in combined length) were surveyed (153 profiles) for beach sand widths (20–412 m) and sand cross-sectional areas (20–1810 m2 ) above wave-cut platforms and/or 0 m tidal datum. Cross-sectional areas were multiplied by beach segments to yield subcell beach sand volumes (0.4 × 106 m3 –35.8 × 106 m3 ± 20% uncertainty). Innermost-shelf profiles were measured for distance to the 100-year depth of closure (30 m) to digitize the areas of inner-shelf accommodation space. Both innermost-shelf and estuarine accommodation space volumes for beach sand displacements were established for 0.5 and 1.0 m SLR. The existing subcell beach sand volumes and computed new beach sand supplies (rivers and longshore transport) were subtracted from the estimated sand volumes lost to submarine accommodation spaces to establish potential beach sand deficits from near-future SLR. Of the 26 surveyed active-beaches, some 60% and 80% (by length) are predicted to be lost, respectively, from the 0.5 m and 1.0 m SLR or equivalent littoral sand sedimentation in submarine accommodation spaces. Projected losses reach 90% for all PNW beaches (~900 km total length) from 1.0 m SLR. The computed beach sand deficits are used to estimate soft-sand retreat distances or erosional beach step backs (50–590 m ± 35% uncertainty) in unrevetted barrier spit and beach/dune deflation plains from 1.0 m SLR. Such empirical accommodation space analyses should have worldwide relevance to predicting beach erosion from near-future SLR.

Rights

Copyright (c) 2021The Authors

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

DOI

10.1016/j.margeo.2021.106555

Persistent Identifier

https://archives.pdx.edu/ds/psu/36497

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