| Soil erosion, as the main reason of leading degradation and loss of land, is the global environmental disaster which limits human existence and development. Soil erosion prediction model is applied to find out the processes and intensity of soil erosion and is the core tool used to monitor and predict trends of soil erosion, which embodies achievement of the quantitative study of soil erosion. WEPP model is comparatively complex soil erosion model of distributed parameter based on continuous events. It entails consideration of the four influencing factors, that is, climate, landform, soil and management. The model is with good extension, and can reflect erosion well and the transferring process of simulating erosion materials is good. Previous studies of WEPP model have been mainly on the prediction parameters and their corresponding researches in the fallow lands. Therefore, through such indexes as relative error, coefficient of efficiency of the model (ME), relative Pearson coefficient, sensitivity value(S) and variation multiples etc, and this paper systemically and integrally does some research on the establishment, validation and sensitivity of prediction parameter of WEPP model (slope version) in purple soil areas based on actual observation data of 29 times of rainfall erosion from four standard runoff plots (farmland with 10°, orchard land with 10°, farmland with 15°and woodland with 15°) of Suining Water Conservation Experiment Station in hilly areas of Sichuan Basin from 2006 to 2008.This study is divided into three parts. The first part is the establishment of the WEPP model prediction parameters. Based on single linear slope, a topographic parameter is established with a gradient of 17.63%(10°), or 26.79%(15°), horizontal projection of slope length as 20m, width of the side slope as 5m; way of CLIGEN Generated is chosen; The meteorological parameter is established by using observation data of rainfall and temperature in Suining Station from 1985 to 2008 and data of Centerville Reference Station of Texas in the United States:management parameter is established by select the measure files in the WEPP model directly; based on soil sample collection and measured data of physical and chemical properties of soil. soil parameter is built by manual calculation or model input generationThe second part is the verification of different prediction parameters. Through the relative error, model efficiency coefficient, relative Pearson coefficients as well as comparison of relevant data obtained by simulating prediction of WEPP model under the combination of statistics of measured erosion and sediment production of 29 times of rainfall with different prediction parameters, study shows that:(1) Manual calculation is better than the establishing method of soil parameter generating from model calculation. Besides, effect of runoff prediction is better than prediction of sediment production. The relative error of runoff by manual calculation are=5%.±10%,-5%～-50%.-30% and-100%. Model efficiency coefficients (ME) are 0.982.0.990.0.789 and-2.645. Pearson coefficients are 0.994,0.996,0.970, and 0.365. According to the two coefficients above the order is like this:orchard land with 10°> farmland with 10°>farmland with 15°> woodland with 15°. When the sediment production is used for validation. simulating relative error of manual calculation in farmlands with 10°nd 15°(-60%-100%% and-80%-100%) is slightly better than model calculation (-75%-100%% and-85%～-100%). Relative error in orchard land with 10°is the same with woodland with 15°(-65%-100% and-100%). Simulating ME value of manual calculation in farmland with 10°and 15°are-0.555 and-1.035. The order of Pearson coefficient of simulation by manual calculation is orchard land with 10°(0.866)> farmland with 15°(0.612)>farmland with 10°(0.378). (2) The same runoff and sediment production art obtained through the three kinds of measures. namely, corn, soybean, wheat, alfalfa(4yrs)-consv till.rot:corn, soybean. wheat. alfalfa(4yrs)-conv till.rot; and corn, soybean, wheat, alfalfa(4yrs)-no till.rot. in the" sweet potato-corn+wheat"planting patter in farmland with 10°and 15°. The corresponding value of ME is 0.982 or-0.555. and 0.789 or-1.035. The Pearson coefficient is 0.994. or 0.866.0.970 and 0.612. As the measure file "Cover after fire. rot" is applied to orchard land with 10°, ME values of predicted runoff and sediment production are 0.990 and-0.758. The Pearson coefficients are 0.996 and 0.866. Automatic measures of the five models are not appropriate to woodland with 15°. Whereas ME value of the "Tree-5 yr old forest.rot" (-2.645) is much better than the other four measure files (-3.540).The third part is the sensitivity analysis of different prediction parameters. Through such indexes as relative error, variation multiple and sensitivity value etc, the runoff and sediment production of single rainfall erosion on 28th June,2008 in farmland with 10°or 15°and orchard land with 10°re used as reference values. Woodland with 15°on 28th June.2007 is selected. Sensitivity analysis with single index which change within±20%,±40%,±60%,±80%.and+100% is made. Results show that:(1) Slope is sensitive to runoff production and there is positive correlation between them. According to the value of S, the order is woodland with 15°(3.993)>farmland with 10°(0.133)> orchard land with 10°(0.132)> farmland with 15°(0.063). Farmland with 10°or 15°is not sensitive to runoff production(S=0.000). Orchard land with 10°is moderately sensitive to runoff production (S=0.531) and the correlation is positive.(2) The four indicators of diachrony of rainfall, rainfall, maximum rainfall intensity and TP (%) are moderately or highly sensitive to the runoff and sediment production in farmland with 10°, orchard land with 10°, and farmland with15°. The rainfall diachrony is a conic opening up which first decreases and then increases. The other three indicators are positively related to the runoff and sediment production. The degree of change is rainfall>maximum rainfall intensity> maximum diachrony>TP (%). The order of sensitivity value of rainfall to runoff and sediment production is farmland with 15°(2.262 and 2.394)> farmland with 10°(2.201 and 2.255)> orchard land with 10°(2.193 and 1.704); The maximum rainfall intensity(S=0.027) and TP (S=0.000) in woodland with 15°re not sensitive to runoff production but the rainfall (S=2.604) and rainfall diachrony (S=2.283) are highly sensitive to the runoff production. The predicted runoff production can not be simulated except the reference value.(3) Soil albedo, the value of rill erosion, and the critical cut force are not sensitive to runoff and sediment production in farmland with 10°, orchard land with 10°and farmland with 15°(S=0.000). The inner rill erosion value is not sensitive to the runoff production in the four areas either (S=0.000), while the critical cut force is highly sensitive to the runoff (S=1.152). Initial saturation and the effective hydraulic conductivity are both highly sensitive to runoff and sediment production and there is positive correlation between initial saturation and runoff production. The effective hydraulic conductivity is negatively correlated with runoff or sediment production. The inner-rill erosion value is positively related to sediment production. The order of S is farmland with 10°(1.2813)> orchard land with 10°(0.444)> farmland with 15°(0.385).
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