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Research Project: Technologies for Managing Water and Sediment Movement in Agricultural Watersheds

Location: Watershed Physical Processes Research

Title: Comparison of soil erodibility factors in USLE, RUSLE2, EPIC and Dg models based on a Chinese soil erodibiity database.

item WANG, BIN - Northwest Agriculture And Forestry University
item ZHENG, FENLI - Northwest Agriculture And Forestry University
item Romkens, Mathias

Submitted to: Acta Agriculturae Scandinavica
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 10/24/2012
Publication Date: 9/3/2012
Publication URL:
Citation: Wang, B., Zheng, F., Romkens, M.J. 2013. Comparison of soil erodibility factors in USLE, RUSLE2, EPIC and Dg models based on a Chinese soil erodibiity database.. Acta Agriculturae Scandinavica, Section B - Soil & Plant Science. 63(1): 69-79.

Interpretive Summary: Soil erodibility is an essential parameter for predicting soil losses from upland areas and for conservation planning. This parameter, together with other parameters for topography, the existing cropping practices, storm characteristics, and erosion control practices, allow erosion control practitioners to estimate soil loss using the Revised Universal Soil Loss Equation (RUSLE2) and other soil loss equations. RUSLE2 is the most widely used soil loss prediction equation in the world. The soil erodibility factor in RUSLE2 is determined by intrinsic soil properties (physical, chemical, mineralogical, etc.) and by the mix of driving forces (rainfall, overland flow, seepage, each one of which is affected differently by a different mix of these properties) that are operative and prevalent in a given situation. Many attempts have been made to estimate soil erodibility from intrinsic properties alone. These attempts were mostly based on soil loss measurements and data sets in the U.S.A. The most important property controlling erodibility turned out to be soil texture. In this paper, the various soil erodibility relationships of the most commonly used soil loss equations (USLE, RUSLE2, EPIC) were tested against Chinese soil erodibility data sets from the Loess Plateau and other regions in China. This paper shows that a texturally based modified version of the RUSLE soil erodibility factor derived for the U.S. best predicted soil erodibility for the soils of the Loess Plateau. This finding shows that the U.S. derived erodibility factor relationship has wide applicability to soil classes for which only limited data sets of a textural nature are available.

Technical Abstract: Soil erodibility (K-value) is a key parameter in erosion prediction and is important for conservation planning in the face of a rising need for protecting the limited land resources. This study investigated the predictive capability of the K-value estimated by Universal Soil Loss Equation (USLE), Revised Universal Soil Loss Equation (RUSLE), Erosion Productivity Impact Calculator (EPIC), and Dg models for different soil regions using a Chinese soil erodibility database covering 51 natural runoff plots. Model performance was evaluated using R^2 (coefficient of determination), relative error (RE), Nash-Sutcliff efficiency (NSE), and P-value (Mann-Whitney U test) statistics. The results showed that the existing four models overestimated almost all the K-values for the Chinese erodibility database, with most observed values concentrated in the range of 0.015-0.035. Without calibration, only the USLE and Dg models could be reliable and directly applied for the black soil region and the loess soil region, respectively. The Dg-OM model (R^2 = 0.67, n = 32) was established by the non-linear best fitting techniques of multiple regression. In the Dg-OM model, K-values accounted for the vibration in a combination of the D sub g (geometric mean diameter) and OM (soil organic matter). NSE, R^2 and the average RE was 0.94, 0.67 and 9.5% for the Dg-OM model’s calibration based on the Chinese erodibility database; similar results were found for the validation process, with NSE of 0.93, R^2 of 0.66 and average RE of 6.5%. The model performances showed that the DF-OM model reached “good” satisfactory level. Compared with the four existing erodibility models, the Dg-OM model permitted the best parameterization and accuracy, and was proved to be suitable for estimating soil erodibility values in China.