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ARS Home » Midwest Area » West Lafayette, Indiana » National Soil Erosion Research Laboratory » Research » Publications at this Location » Publication #137655
Title: A NON-PARAMETRIC/PARAMETRIC ANALYSIS OF THE UNIVERSAL SOIL LOSS EQUATIOON

Author
item SONNEVELD, B - UNITED KINGDOM
item Nearing, Mark

Submitted to: Catena
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 9/20/2002
Publication Date: N/A
Citation: N/A

Interpretive Summary: This study was an analysis of the Universal Soil Loss Equation (USLE). The USLE is used around the world for helping land managers choose conservation practices; as an engineering tool in the design of dams, reservoirs, channels, and other engineering structures; and for laws and regulations related to land use management. In the United States alone, billions of dollars of federal payments, programs, and loans to farmers are based on predictions of the USLE. The objective of this study was to determine if a more robust structure for the model could be derived that would result in significantly more reliable predictions of soil erosion. The USLE was developed in the 1950s and 1960s, and since that time computers have given us data analysis tools that were simply not available at that time. Statistical analysis of the original data (more than 10,000 plot years of data) that were used to create the USLE was relatively primitive relative to today's standards. The results showed that the user must be careful in defining the parameters of the USLE model in order to obtain accurate erosion estimates, however, only slight model improvements could be obtained by drastic modifications of its functional form. The implications of the study are that the USLE remains a very valuable tool for predicting soil erosion, in spite of the many advances in analysis tools provided by modern computer technology.

Technical Abstract: Due to its modest data demands and transparent model structure the Universal Soil Loss Equation (USLE) remains the most popular tool for water erosion hazard assessment. However, the model has several shortcomings, two of which are likely to have prominent implications for the model results. First, the mathematical form of the USLE, the multiplication of six factors, easily leads to large errors whenever one of the input data is misspecified. Second, the USLE has a modest correlation between observed soil losses and model calculations, even with the same data that were used for its calibration. This raises questions about its mathematical model structure and the robustness of the assumed parameter values that are implicitly assigned to the model. This paper, therefore, analyzes if the USLE could benefit from mathematical model transformations that, on one hand, mitigate the impact of incorrect input factors and, on the other hand, result in a better fit between model results and observed soil losses. For the analysis we first use both non-parametric and parametric techniques to test the robustness of the implicit parameter assignments in the USLE equation. Next, we postulate alternative mathematical forms and use parametric test statistics to evaluate parameter significance and model fit. A tenfold cross validation of the model with the best fit tests the sensitivity of the parameters for inclusion or exclusion of the data. The results show that the USLE model is not very robust, however, only slight model improvements are obtained by drastic modifications of its functional form, thereby sacrificing the simple model structure that was intended by its designers.