Improved USLE-K factor prediction:A case study on water erosion areas in China  

作　　者：Bin Wang Fenli Zheng Yinghui Guan 

机构地区：[1]School of Soil and Water Conservation,Beijing Forestry University,Beijing 100083,PR China [2]State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau,Institute of Soil and Water Conservation,Northwest A&F University,Yangling,Shaanxi 712100,PR China [3]Center for Spatial Analysis,University of Oklahoma,Norman 73019,USA

出　　处：《International Soil and Water Conservation Research》2016年第3期168-176,共9页国际水土保持研究（英文）

基　　金：This study was supported by the National Natural Science Foundation of China(Grant no.41401299);the National Basic Research Program of China(Grant no.2007CB407201);the USDA-ARS Grazinglands Research Laboratory.The authors would like to thank Dr.Römkens M.J.M.,Dr.Xiangming Xiao,the editors and anonymous reviewers for their helpful comments and suggestions.

摘　　要：Soil erodibility(K-factor)is an essential factor in soil erosion prediction and conservation practises.The major obstacles to any accurate,large-scale soil erodibility estimation are the lack of necessary data on soil characteristics and the misuse of variable K factor calculators.In this study,we assessed the per-formance of available erodibility estimators Universal Soil Loss Equation(USLE),Revised Universal Soil Loss Equation(RUSLE),Erosion Productivity Impact Calculator(EPIC)and the Geometric Mean Diameter based(Dg)model for different geographic regions based on the Chinese soil erodibility database(CSED).Results showed that previous estimators overestimated almost all K-values.Furthermore,only the USLE and Dg approaches could be directly and reliably applicable to black and loess soil regions.Based on the nonlinear best ftting techniques,we improved soil erodibility prediction by combining Dg and soil or ganic matter(SOM).The NSE,R^(2)and RE values were 0.94,0.67 and 9.5%after calibrating the results independently:similar model performance was showed for the validation process.The results obtained via the proposed approach were more accurate that the former K-value predictions.Moreover,those improvements allowed us to effectively establish a regional soil erodibility map(1:250,000 scale)of water erosion areas in China.The mean K-value of Chinese water erosion regions was 0.0321(t ha h).(ha MJ mm)^(-1)with a standard deviation of 0.0107(t ha h).(ha MJ mm)^(-1);K-values present a decreasing trend from North to South in water erosion areas in China.The yield soil erodibility dataset also sa-tisfactorily corresponded to former K-values from diferent scales(local,regional,and national).

关 键 词：Erodibility assessment Erodibility map K-VALUE Modeling China 

分 类 号：S15[农业科学—土壤学]