Title: Hurricanes alter 10Be concentrations in tropical river sediment but do not change regional erosion rate estimates

Journal Article · · Earth Surface Processes and Landforms
DOI: https://doi.org/10.1002/esp.5310 · OSTI ID:1837630
 [1]; ORCiD logo [2];  [1];  [3];  [4];  [5]
  1. Univ. of Vermont, Burlington, VT (United States)
  2. Oberlin College, OH (United States)
  3. Univ. of Vermont, Burlington, VT (United States). Gund Inst. for the Environment
  4. Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States). Center for Accelerator Mass Spectrometry
  5. Purdue Univ., West Lafayette, IN (United States). PRIME Lab.

Tropical islands, including many in island arcs, are subjected to recurring disturbances from extreme storms such as tropical cyclones. To test whether such storms influence cosmogenic nuclide concentrations such that they do not reflect long-term rates of erosion, we measured meteoric and in situ 10Be in river sediment samples from Dominica, an andesitic island in the Caribbean, before and after category five Hurricane Maria (2017). Populations of before- and after-storm concentrations are statistically indistinguishable (n=7 pairs for in situ 10Be, n=11 pairs for meteoric 10Be). 10Be concentrations vary from -138% to +73% within before-after sample pairs relative to the mean of the pair. These new data suggest that the effects of extreme storms on the depth and amount of near-surface erosion on Dominica vary spatially. Our data support calculations of Niemi, et al. (2005) and Yanites, et al. (2009) suggesting that basin-by-basin comparisons of erosion rates based on cosmogenic nuclides should be approached with caution in small (<~100 km2) watersheds affected by mass movements and extreme storms. Erosion rates determined from in situ 10Be in Dominica (geometric mean=0.102 mm y-1, n=12) are low compared to similarly steep and wet areas globally and correlate positively with the spatial density of mass movements.

Research Organization:
Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)
Sponsoring Organization:
National Science Foundation (NSF); USDOE National Nuclear Security Administration (NNSA)
Grant/Contract Number:
AC52-07NA27344
OSTI ID:
1837630
Report Number(s):
LLNL-JRNL-778336; 972466
Journal Information:
Earth Surface Processes and Landforms, Journal Name: Earth Surface Processes and Landforms Journal Issue: 5 Vol. 47; ISSN 0197-9337
Publisher:
WileyCopyright Statement
Country of Publication:
United States
Language:
English

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Meteoric Beryllium 10 flux calculated from latitude and mean annual precipitation dataset January 2019
Sample preparation and laboratory measurement values for fine-grain meteoric Beryllium 10 concentrations before and after Hurricane Maria in Dominica and the percent difference between the two time periods dataset January 2019
Sample locations and upstream basin average parameters for all sampled watersheds dataset January 2019
Beryllium 10 blanks processed with Dominica river sediment samples collected before and after Hurricane Maria dataset January 2020
Meteoric Beryllium 10 flux calculated from latitude and mean annual precipitation dataset January 2019
Sample preparation and laboratory measurement values for coarse-grain meteoric Beryllium 10 concentrations before and after Hurricane Maria in Dominica and the percent difference between the two time periods dataset January 2019
Sample preparation and laboratory measurement values for fine-grain meteoric Beryllium 10 concentrations before and after Hurricane Maria in Dominica and the percent difference between the two time periods dataset January 2019
Sample preparation and laboratory measurement values for in-situ meteoric Beryllium 10 concentrations before and after Hurricane Maria in Dominica and the percent difference between the two time periods dataset January 2019
Sample locations and upstream basin average parameters for all sampled watersheds dataset January 2019
Beryllium 10 blanks processed with Dominica river sediment samples collected before and after Hurricane Maria dataset January 2020