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Volume 21 Issue 8 (August 2011)

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Article, pp. 4-10 | Full Text | PDF (3.7MB)

Understanding Earth’s eroding surface with 10Be

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Eric W. Portenga1*, Paul R. Bierman2*

1 Dept. of Geology, University of Vermont, 180 Colchester Ave., Burlington, Vermont 05405, USA
2 Dept. of Geology and Rubenstein School of the Environment and Natural Resources, University of Vermont, 180 Colchester Ave., Burlington, Vermont 05405, USA


For more than a century, geologists have sought to measure the distribution of erosion rates on Earth’s dynamic surface. Since the mid-1980s, measurements of in situ 10Be, a cosmogenic radionuclide, have been used to estimate outcrop and basin-scale erosion rates at 87 sites around the world. Here, we compile, normalize, and compare published 10Be erosion rate data (n = 1599) in order to understand how, on a global scale, geologic erosion rates integrated over 103 to 106 years vary between climate zones, tectonic settings, and different rock types.

Drainage basins erode more quickly (mean = 218 m Myr−1; median = 54 m Myr−1) than outcrops (mean = 12 m Myr−1; median = 5.4 m Myr−1), likely reflecting the acceleration of rock weathering rates under soil. Drainage basin and outcrop erosion rates both vary by climate zone, rock type, and tectonic setting. On the global scale, environmental parameters (latitude, elevation, relief, mean annual precipitation and temperature, seismicity, basin slope and area, and percent basin cover by vegetation) explain erosion rate variation better when they are combined in multiple regression analyses than when considered in bivariate relationships. Drainage basin erosion rates are explained well by considering these environmental parameters (R2 = 0.60); mean basin slope is the most powerful regressor. Outcrop erosion rates are less well explained (R2 = 0.32), and no one parameter dominates. The variance of erosion rates is better explained when subpopulations of the global data are analyzed. While our compilation is global, the grouped spatial distribution of cosmogenic studies introduces a bias that will only be addressed by research in under-sampled regions.

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Manuscript received 27 Oct. 2010; accepted 1 Apr. 2011

DOI: 10.1130/G111A.1