Measuring Soil Erosion Rates Using Natural (7Be, 210Pb) and Anthropogenic (137Cs, 239,240Pu) Radionuclides

  • Gerald MatisoffEmail author
  • Peter J. Whiting
Part of the Advances in Isotope Geochemistry book series (ADISOTOPE)


This chapter examines the application of natural (7Be and 210Pb) and anthropogenic fallout radionuclides (134Cs, 137Cs, 239,240Pu) to determine soil erosion rates. Particular attention is given to 137Cs because it has been most widely used in geomorphic studies of wind and water erosion. The chapter is organized to cover the formation and sources of these radionuclides; how they are distributed in precipitation and around the globe: their fate and transport in undisturbed and tilled soils; and their time scales of utility. Also discussed are methods for soil collection, sample preparation for 137Cs analysis by gamma spectroscopy, and the selection of standards and instrument calibration. Details are presented on methods for calculating soil erosion, including empirical methods that are related to the Universal Soil Loss Equation (USLE), box models that compare 137Cs activities in a study site to a reference site, and time dependent methods that account for the temporal inputs of 137Cs and precipitation induced erosion. Several examples of recent applications, including the combination of radionuclides with other techniques or measurements, are presented. The chapter concludes with suggestions for future work: the value of new methods and instrumentation to allow for greater spatial resolution of rates and/or greater accuracy; the need to incorporate migration of radionuclides in the time-dependent models; the opportunities to concurrently use the global and Chernobyl signals to better understand temporal variation soil erosion processes and rates; and the importance of the use of these tracers to characterize C storage and cycling.


Erosion Rate Soil Erosion Wind Erosion Universal Soil Loss Equation Soil Erosion Rate 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



This chapter is dedicated to the memory of Jerry Ritchie.

We would like to thank our former students for their contributions to our research, some of which is highlighted in this chapter: undergraduates Rita Cabral, Joel Saylor, Derek Smith, Natalie Vajda, and Lauren Vitko; graduate students Chris Bonniwell, Travis Bukach, Carol Fondran, and Chris Wilson; post-doctoral research associates Bill Fornes and Andrew Stubblefield; and colleagues Michael Ketterer, J. Wojciech Mietelski, Klas Rosén, Fred Soster, Louis Thibodeaux, and their students. James Kaste and an anonymous reviewer provided comments that improved the manuscript.


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© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  1. 1.Department of Geological SciencesCase Western Reserve UniversityClevelandUSA

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