Predicting plot soil loss by empirical and process-oriented approaches. A review

  • Vincenzo Bagarello Department of Agricultural, Food and Forest Sciences, University of Palermo, Italy.
  • Vito Ferro | vito.ferro@unipa.it Department of Earth and Sea Sciences, University of Palermo, Italy. http://orcid.org/0000-0003-3020-3119
  • Dennis Flanagan Agricultural Engineer and Lead Research Scientist, USDA-ARS National Soil ErosionResearch Laboratory, Purdue University, West Lafayette, IN, United States.

Abstract

Soil erosion directly affects the quality of the soil, its agricultural productivity and its biological diversity. Many mathematical models have been developed to estimate plot soil erosion at different temporal scales. At present, empirical soil loss equations and process-oriented models are considered as constituting a complementary suite of models to be chosen to meet the specific user need. In this paper, the Universal Soil Loss Equation and its revised versions are first reviewed. Selected methodologies developed to estimate the factors of the model with the aim to improve the soil loss estimate are described. Then the Water Erosion Prediction Project which represents a process-oriented technology for soil erosion prediction at different spatial scales, is presented. The available criteria to discriminate between acceptable and unacceptable soil loss estimates are subsequently introduced. Finally, some research needs, concerning tests of both empirical and process-oriented models, estimates of the soil loss of given return periods, reliability of soil loss measurements, measurements of rill and gully erosion, and physical models are delineated.

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Published
2018-04-05
Section
Review Articles
Keywords:
Soil erosion, soil loss measurements, Universal Soil Loss Equation, water erosion prediction project.
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How to Cite
Bagarello, V., Ferro, V., & Flanagan, D. (2018). Predicting plot soil loss by empirical and process-oriented approaches. A review. Journal of Agricultural Engineering, 49(1), 1-18. https://doi.org/10.4081/jae.2018.710