Computer Science
Scientific paper
Sep 2005
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2005e%26psl.237..480n&link_type=abstract
Earth and Planetary Science Letters, Volume 237, Issue 3-4, p. 480-498.
Computer Science
25
Scientific paper
The successful quantification of long-term erosion rates underpins our understanding of landscape formation, the topographic evolution of mountain ranges, and the mass balance within active orogens. The measurement of in situ produced cosmogenic radionuclides (CRNs) in fluvial and alluvial sediments is perhaps the method with the greatest ability to provide such long-term erosion rates. Although deep-seated bedrock landsliding is an important erosional process in active orogens, its effect on CRN-derived erosion rates is largely unquantified. We present a numerical simulation of cosmogenic nuclide production and distribution in landslide-dominated catchments to address the effect of bedrock landsliding on erosion rates. Results of the simulation indicate that the temporal stability of erosion rates determined from CRN concentrations in sediment decreases with increased ratios of landsliding to bedrock weathering rates within a given catchment area, and that as the frequency of landsliding increases, larger catchment areas must be sampled in order to accurately evaluate long-term erosion rates. In addition, results of this simulation suggest that sediment sampling for CRNs is the appropriate method for determining long-term erosion rates in regions dominated by mass-wasting processes, whereas bedrock surface sampling for CRNs may generally underestimate long-term erosion rates. Response times of CRN concentrations to changes in erosion rate indicate that climatically driven cycles of erosion may be detected, but that complete equilibration of CRN concentrations to new erosional conditions may take tens of thousands of years. Comparison of simulated CRN-derived erosion rates with a new data set of such rates from the Nepalese Himalaya underscore the conclusions drawn from the model results.
Burbank Douglas W.
Gabet Emmanuel J.
Heimsath Arjun M.
Niemi Nathan A.
Oskin Michael
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