Location: National Soil Erosion ResearchTitle: Predicting plot soil loss by empirical and process-oriented approaches: A review Author
Submitted to: Agricultural Engineering Journal
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 9/4/2017
Publication Date: 4/10/2018
Citation: Bagerello, V., Ferro, V., Flanagan, D.C. 2018. Predicting plot soil loss by empirical and process-oriented approaches: A review. Agricultural Engineering Journal. 49(1):1-18. Interpretive Summary: This review article discusses a number of different empirical and process-based soil erosion prediction technologies. Mathematical estimation of the soil detachment and sediment loss processes are critically important for determining rates of soil erosion and the effectiveness of various land management practices at reducing and controlling soil loss. Soil erosion by water is a complicated process that is driven by rainfall and subsequent runoff over the soil surface, detachment by the raindrops, sediment transport in shallow overland flow, detachment by concentrated flow in rills, and sediment transport and potential deposition further downslope. Use of equations and computer simulation models are the only practical ways to estimate the amount of soil loss that may occur at a specific location (climate) with a specific soil and slope, under a particular type of agricultural or other land management practice. Information provided in this paper will impact scientists and students, as well as others with an interest in soil erosion prediction technology science, and accuracy.
Technical 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 firstly 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, estimate of the soil loss of given return period, reliability of soil loss measurement, measurement of rill and gully erosion and physical model, are delineated.