WEPP模型预测参数在紫色土区的研究
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摘要
土壤侵蚀,是导致土地资源退化和损失的主要原因,是限制当今人类生存与发展的全球性环境灾害。土壤侵蚀预报模型用于了解土壤侵蚀过程与强度,是进行土壤侵蚀动态监测预报的核心工具和难点问题,体现着土壤侵蚀定量化研究的成果。WEPP模型是迄今为止较为复杂的基于连续事件的分布式参数土壤侵蚀模型,其需要考虑气候、地形、土壤和管理四大方面的影响因素,具有外延性好、反映侵蚀分布好、模拟侵蚀物质输移过程好的优点。已有对WEPP模型在紫色土区的研究主要是部分预测参数及其在休闲地上的研究,因此本论文利用四川盆地中部丘陵区遂宁水土保持试验站2006～2008年四个标准径流小区(10°农耕地小区、10°果园地小区、15°农耕地小区和15°林地小区)的29次单次降雨侵蚀实际观测资料,通过相对误差、模型有效性系数(ME)、Pearson相关系数、敏感度值(S)、变化倍数等指标,对WEPP(坡面版)模型预测参数在紫色土丘陵区的建立、验证和敏感性进行研究。
本研究共分三个部分,第一部分是WEPP模型预测参数的建立,采用单一直线坡建立坡度为17.63%(10°)或26.79%(15°),坡长水平投影为20m,坡侧面宽度为5m的地形参数；选择CLIGEN Generated的方式,利用遂宁站内气象观测场1985～2008年降雨和气温观测数据及美国得克萨斯州(TEXAS)森特维尔(CENTERVILLE)参证站点数据建立气象参数；直接选取WEPP模型中自带的措施文件建立管理参数；在土样采集、土壤理化性质测定的基础上,采用计算输入或模型生成的方式建立土壤参数。
第二部分是不同预测参数的验证,通过相对误差、模型有效性系数、Pearson相关系数等指标,以29次实测单次降雨侵蚀产流量和产沙量数据与不同预测参数组合下WEPP模型模拟预测得到的对应数据进行比较,研究表明：(1)计算输入好于模型生成的土壤参数建立方式,且产流量预测效果好于产沙量的预测。手工计算对产流量的相对误差为±5%、±10%、-5%～-50%和-30%～-100%：模型有效性系数ME为0.982、0.990、0.789、-2.645和Pearson相关系数为0.994、0.996、0.970、0.365,按其排序为10°果园地小区>10°农耕地小区>15°农耕地小区>15°林地小区。当用产沙量进行验证时,10°和15°农耕地小区的手工计算方式模拟相对误差(-60%～-100%%和-80%～-100%)略好于模型计算方式(-75%～-100%%和-85%～-100%),10°果园地小区和15°林地小区的相对误差一样(-65%～-100%%和-100%)：10°和15°农耕地小区手工计算方式模拟的ME值为-0.555和-1.035；手工计算方式模拟的Pearson相关系数排序为10°果园地小区(0.866)>15°农耕地小区(0.612)>10°农耕地小区(0.378)。(2)对10°和15°农耕地小区的“玉米+红苕+小麦”种植模式所选取模型自带的“Com,soybean,wheat, alfalfa(4yrs)-consv till.rot、Corn, soybean, wheat, alfalfa(4yrs)-conv till.rot和Corn, soybean,wheat, alfalfa(4yrs)-no till.rot"三种措施文件得到相同的产流量或产沙量,其对应的ME值为0.982或-0.555和0.789或-1.035,Pearson相关系数为0.994或0.866和0.970或0.612；对10。果园地小区选用“30%Cover after fire. rot"措施文件时,其预测产流量和产沙量的ME值为0.990和-0.758,Pearson相关系数为0.996和0.866；对15°林地小区的五种模型自动措施文件都不理想,但"Tree-5 yr old forest.rot"的ME值(-2.645)略好于其他四个措施文件(-3.540)。
第三部分是不同预测参数的敏感性分析,通过相对误差、变化倍数和敏感度值等指标,以10°或15°农耕地小区和10°果园地小区中具有代表性的2008年8月24日单次降雨侵蚀的产流量或产沙量为基准值,15°林地小区选用2007年6月28日,进行单参数在±20%、±40%、±60%、±80%、+100%范围内变化的敏感性分析,结果表明：(1)坡度对产流量敏感,且为正相关,按S值排序为15。林地小区(3.993)>10°农耕地小区(0.133)>10°果园地小区(0.132)>15°农耕地小区(0.063)；10°或15°农耕地小区对产沙量不敏感(S值为0.000),仅10。果园小区对产沙量中度敏感(S值为0.531),且为正相关。(2)降雨量、降雨历时、最大雨强和TP(%)的四个指标对10°农耕地小区、10°果园地小区、15°农耕地小区的产流量和产沙量达中度或高度敏感,除降雨历时为开口向上先减小再增大的二次曲线外,其他三个指标均为正相关,其变化程度为降雨量>最大雨强>最大历时>TP(%)；降雨量对产流量和产沙量的敏感度值排序为15°农耕地小区(2.262和2.394)>10°农耕地小区(2.201和2.255)>10°果园地小区(2.193和1.704)；在15°林地小区中最大雨强(S值为0.027)和TP(S值为0.000)对的产流量不敏感,但降雨量(S值为2.604)和降雨历时(S值为2.283)高度敏感,且除基准值外,无法模拟到产流量预测值。(3)土壤反照率、细沟侵蚀值、临界剪切力在10°农耕地小区、10°果园地小区、15°农耕地小区对产流量或产沙量都不敏感(S值均为0.000)；细沟间侵蚀值对四个小区的产流量都不敏感(S值都为0.000)；15°林地小区的土壤反照率和细沟侵蚀值对产流量也不敏感(S值为0.000),而临界剪切力却高度敏感(S值为1.152)；初始饱和度和有效水力传导率对产流量和产沙量都高度敏感,初始饱和度对产流量正相关,有效水力传导率对产流量或产沙量都是负相关；细沟间侵蚀值对产沙量正相关,其S值大小为10°农耕地小区(1.281)>10°果园地小区(0.444)>15°农耕地小区(0．385)。
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 generation
The 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).
本研究共分三个部分,第一部分是WEPP模型预测参数的建立,采用单一直线坡建立坡度为17.63%(10°)或26.79%(15°),坡长水平投影为20m,坡侧面宽度为5m的地形参数；选择CLIGEN Generated的方式,利用遂宁站内气象观测场1985～2008年降雨和气温观测数据及美国得克萨斯州(TEXAS)森特维尔(CENTERVILLE)参证站点数据建立气象参数；直接选取WEPP模型中自带的措施文件建立管理参数；在土样采集、土壤理化性质测定的基础上,采用计算输入或模型生成的方式建立土壤参数。
第二部分是不同预测参数的验证,通过相对误差、模型有效性系数、Pearson相关系数等指标,以29次实测单次降雨侵蚀产流量和产沙量数据与不同预测参数组合下WEPP模型模拟预测得到的对应数据进行比较,研究表明：(1)计算输入好于模型生成的土壤参数建立方式,且产流量预测效果好于产沙量的预测。手工计算对产流量的相对误差为±5%、±10%、-5%～-50%和-30%～-100%：模型有效性系数ME为0.982、0.990、0.789、-2.645和Pearson相关系数为0.994、0.996、0.970、0.365,按其排序为10°果园地小区>10°农耕地小区>15°农耕地小区>15°林地小区。当用产沙量进行验证时,10°和15°农耕地小区的手工计算方式模拟相对误差(-60%～-100%%和-80%～-100%)略好于模型计算方式(-75%～-100%%和-85%～-100%),10°果园地小区和15°林地小区的相对误差一样(-65%～-100%%和-100%)：10°和15°农耕地小区手工计算方式模拟的ME值为-0.555和-1.035；手工计算方式模拟的Pearson相关系数排序为10°果园地小区(0.866)>15°农耕地小区(0.612)>10°农耕地小区(0.378)。(2)对10°和15°农耕地小区的“玉米+红苕+小麦”种植模式所选取模型自带的“Com,soybean,wheat, alfalfa(4yrs)-consv till.rot、Corn, soybean, wheat, alfalfa(4yrs)-conv till.rot和Corn, soybean,wheat, alfalfa(4yrs)-no till.rot"三种措施文件得到相同的产流量或产沙量,其对应的ME值为0.982或-0.555和0.789或-1.035,Pearson相关系数为0.994或0.866和0.970或0.612；对10。果园地小区选用“30%Cover after fire. rot"措施文件时,其预测产流量和产沙量的ME值为0.990和-0.758,Pearson相关系数为0.996和0.866；对15°林地小区的五种模型自动措施文件都不理想,但"Tree-5 yr old forest.rot"的ME值(-2.645)略好于其他四个措施文件(-3.540)。
第三部分是不同预测参数的敏感性分析,通过相对误差、变化倍数和敏感度值等指标,以10°或15°农耕地小区和10°果园地小区中具有代表性的2008年8月24日单次降雨侵蚀的产流量或产沙量为基准值,15°林地小区选用2007年6月28日,进行单参数在±20%、±40%、±60%、±80%、+100%范围内变化的敏感性分析,结果表明：(1)坡度对产流量敏感,且为正相关,按S值排序为15。林地小区(3.993)>10°农耕地小区(0.133)>10°果园地小区(0.132)>15°农耕地小区(0.063)；10°或15°农耕地小区对产沙量不敏感(S值为0.000),仅10。果园小区对产沙量中度敏感(S值为0.531),且为正相关。(2)降雨量、降雨历时、最大雨强和TP(%)的四个指标对10°农耕地小区、10°果园地小区、15°农耕地小区的产流量和产沙量达中度或高度敏感,除降雨历时为开口向上先减小再增大的二次曲线外,其他三个指标均为正相关,其变化程度为降雨量>最大雨强>最大历时>TP(%)；降雨量对产流量和产沙量的敏感度值排序为15°农耕地小区(2.262和2.394)>10°农耕地小区(2.201和2.255)>10°果园地小区(2.193和1.704)；在15°林地小区中最大雨强(S值为0.027)和TP(S值为0.000)对的产流量不敏感,但降雨量(S值为2.604)和降雨历时(S值为2.283)高度敏感,且除基准值外,无法模拟到产流量预测值。(3)土壤反照率、细沟侵蚀值、临界剪切力在10°农耕地小区、10°果园地小区、15°农耕地小区对产流量或产沙量都不敏感(S值均为0.000)；细沟间侵蚀值对四个小区的产流量都不敏感(S值都为0.000)；15°林地小区的土壤反照率和细沟侵蚀值对产流量也不敏感(S值为0.000),而临界剪切力却高度敏感(S值为1.152)；初始饱和度和有效水力传导率对产流量和产沙量都高度敏感,初始饱和度对产流量正相关,有效水力传导率对产流量或产沙量都是负相关；细沟间侵蚀值对产沙量正相关,其S值大小为10°农耕地小区(1.281)>10°果园地小区(0.444)>15°农耕地小区(0．385)。
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 generation
The 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).
引文
[1]刘宝元,谢云,张科利.土壤侵蚀预报模型[M],中国科学技术出版社,2001.[2]余新晓,秦富仓,等.流域侵蚀动力学[M],科学出版社,,2007.[3]南秋菊,华珞.国内外土壤侵蚀研究进展[J].首都师范大学学报(自然科学版)2003,24(2)：86～95.[4]张洪江主编.土壤侵蚀原理[M].北京：中国林业出版社,2000：3-12,22,199，210-219.[5]史德明.如何正确理解有关水土保持术语的讨论.土壤侵蚀与水土保持学报,1998,4(4)：89～91.[6] Hudson N W. Soil Conservation,[M]Second Edition, Cornell Univ. Press,1981.[7]彭舜磊,赵迎春.为什么我国森林覆盖率逐年提高而水土流失和荒漠化却日益严重[J].生态环境和保护,2002(2).[8]郑粉莉,王占礼,杨勤科.土壤侵蚀学科发展战略.水土保持研究,2004,11(4)：1～10.[9]苏锋,WEPP模型在紫色土休闲地的应用及其因子权重分析[D].重庆：西南大学,2008：1,9,18,11～14.[10]王礼先.水土保持学[M].北京：中国林业出版社,1995：1-18.[11]M.J.柯比克,R.P.C.摩根编著,王礼先,吴斌等译.土壤侵蚀.水利电力出版社,1987.[12] Meyer L D. Evolution of the universal soil loss equation [J]. Journal of Soil and Water Conservation,1984,39:99～104. [13] Laws. J.0. Recent Studies in Raindrops and Erosion. Agricultural Engineering 24,1940:431-433.[14]美国土壤保持协会编,窦葆章译.土壤侵蚀预报与控制,北京：农业出版社,1981[15] Meyer L.D. and Wischmeier W.H. Mathematical Simulation of the Process of Soil Erosion by Water.Trans. Am. Soc. Agric. Engrs,1969(12):754-758. [16] Foster GR. etc. Close from soil erosion equation for upland areas. Water Resources Research,1968(6):1176-1187.[17]江忠善,刘志.降雨因素和坡度对溅蚀影响的研究.水土保持学报,1989(2)：29～35.[18]邵颂东,王礼先,周金星.国外土壤侵蚀研究的新进展.水土保持科技情报,2000(1)：32-36.[19] Lowery B, Swan J,Schumacher T,Jones A. Physical Properties of selected soils by erosion class Journal Soil and water Conservation,1995,50(3):306-311. [20] Halvorson J J,Smith J L, Papendick R I. Issues of scale for evaluating soil quality. J. Soil and Water Cons.,1997,52(1):26～30. 21] Poeson J W,Torri D,Bunte K. Effects of rock fragments on soil erosion by water at different spatial scales:a review,Catena 23,1994,141～166. [22] Bunte K,Poeson J W.Effects of rock fragment covers on erosion and transport of noncohesive sediment by shallow overland flow.Water Resources Research,1993,29(5):1415～1424.[23]万丹,紫色土不同利用方式下土壤侵蚀及氮磷流失研究[D].重庆：西南大学,2007：2-3.[24] Morgan R P C, Quinton J N, Smith R E, etc. The European Soil Erosion Model(EUROSEM): A dynamic approach for predicting sediment transport from fields and small catchments. Earth Surface Processes and landforms,1998,23:527-544. [25] De Roo A.P.J, Wesseling C.Gand C.J.Ritsema 1996.LISEM:a single event physically-based hydrological soil erosion model for drainage basins:I.theory, input and output. Hydrological Processes 10(8):1107～1118.
[26]Latlen J.M. et al.WEPP-Predicting water erosion using a process-based model. J.soil water cors. 1997.52(2):96～102.
[27]Vieux B E Geographic information systems and non-point source water quality and quantity modeling. Hydrological Processes,1991.5:101～113.
[28]Chow T L,Daigle J L.Ghanem I,Cormier H. Effects of potato cropping on water run-off and soil erosion.Can.J. Soil Sci.990.70:137-148.
[29]王锐亮,川北紫色土深丘区小流域降雨及土壤侵蚀特征分析[D].重庆：西南大学.2007：1～4.
[30]罗细芳，姚小华.水土流失机理与模型研究进展[J].江西农业大学学报.2004，26(5)：813～817.
[31]夏卫生.具有中国特色的水土保持科学体系[J].水土保持通报.1989,9(4)：30～35.
[32]刘善建.天水水土流失试验站的初步分析[J].科学通报，1953，12：59～65.
[33]杨建英,赵廷宁.坡面侵蚀研究现状及展望[J].北京林业大学学报.1994.16(1)：95～101.
[34]周佩华,李银锄,黄义端.等.2000年中国水土流失趋势预测及其防治对策[J].见：中国科学学院西北水土保持研究所集刊(第7集),1988：57～71.
[35]胡良军，李锐,杨勤科.基于GIS的区域水土流失评价研究[J].土壤学报,2001.38(2)：169～174.
[36]张宝信.黄土高原小流域泥沙来源的137Cs法的研究[J].科学通报,1989,(3)：210～213.
[37]田均良，周佩华.土壤侵蚀REE示踪法研究初报[J].水土保持学报,1992,6(4)：23～27.
[38]汤立群.流域产沙模型的研究[J].水科学进展,1996，7(1)：47～53.
[39]蔡强国,陆兆熊，王(?)平.黄土丘陵沟壑区典型小流域侵蚀产沙过程模拟[J].地理学报.1996.51(2)：108～116.
[40]李文银.王治国,蔡继清.工矿区水土保持[M].北京：科学出版社,1996：127.
[41]白中科等.工矿区土地复垦与生态重建[M].北京：中国农业科技出版社，2000,4：1～18.
[42]叶翠玲.许兆义,杨成永.秦沈客运专线建设过程中的水土流失实验研究[J].水土保持学报.2001.15(2)：9～13.
[43]杨成永,王美芝，许兆义等.秦沈客运专线路堤边坡土壤侵蚀预报研究[J].水土保持学报.2001.15(2)：14～16.
[44]李忠武,蔡强国，吴淑安.等.内昆铁路施工期不同下垫面土壤侵蚀模拟研究[J].水土保持学报．2001，15(2)：5～8.
[45]唐晓春,谢世友，罗鉴银,等.南昆铁路威红区段家河流域地貌演化与水土流失[J].水土保持学报，1993,7(4)：1～7.
[46]孙虎,甘枝茂.城市周边地区侵蚀景观特征分析[J].土壤侵蚀与水土保持学报，1998，4(4)：31～36.
[47]张玉斌,郑粉莉.贾媛媛.WEPP模型概述.水土保持研究2004，11(4)：146～149.
[48]莫放,水蚀模型WEPP与GIS的联合应用[D]，陕西,西安理工大学，2004：3.13.
[49]Zingg A W. Degree and length of Land Slope as It Affects Soil Loss in Runoff [J]. Agricultural Engineering.1940.21:59～64..
[50]Musgrave G W. The Quantitative Evaluation of Factors in Water Erosion[J].Soil and Water Conservation.1947:2(3)133～138.
[51]Wischmeier W H and Smith D D. Rainfall Energy and Its Relation to Soil Loss [M].Trans AM Geography. Union,1958,39.285～291.
[52]Wischmeier W H, Smith D D and Uhland R E. Evaluation of Factors in the Soil Loss Equation, [M] Agric Eng,1985,39,458-464.
[53]贾志伟等.降雨特征与水土流失的研究.中国科学院水利部西北水土保持研究所集刊[J],1990,12,9～15.
[54]Negev M A.A Sediment Model on a Digital Computer,Technical Report 76, Deportment of Civil Engineering, Stanford University,1967.
[55]Meyer L D. and Wischmeier W H. Mathematical Simulation of Process of Soil Erosion by Water,Trans. ASAE,1969,12(6).
[56]Foster G R. and Meyer L D. Mathematical Simulation of Upland Erosion by Fundamental Erosion Principles, Trans. ASAE,1975,20 (4).
[57]David W P. and Beer C E. Simulation of Soil Erosion,Part Ⅰ,Development of a Mathematical Erosion Model,Trans. ASAE,1975,18(1).
[58]Fogel M M, Heknan and Duckstein L.A stochastic Sediment Yield Model Using the Modified Universal, Soil Loss Equation, In:Soil Erosion:Prediction and Control, Soil Conservation Society of America, Special Publication,1976,21.
[59]Julien P Y. Soil Erosion Loss from Upland Areas, Proc, the 4th International Symposium on River Sedimentation,1989.
[60]中华人民共和国水利部.土壤侵蚀分类分级标准[1997-02-13].北京：中国水利出版社,1997.
[61]缪驰远,WEPP模型在紫色土地区的应用及与USLE的对比研究[D].重庆：西南农业大学,2005：2,10，16-20.
[62]李进峰,嘉陵江上游不同土地利用方式土坡侵蚀模型应用研究[D].四川：四川农业大学,2007：2.
[63]李勉,李占斌.中国土壤侵蚀定量研究进展[J].水土保持研究2002,vol.9.No.3.
[64]Wischmeier W H, Smith D D.A universal soil loss equation to guide conservation farm planning trans 7th International Cong. Soil Sci,1960,1:418～425.
[65]Wischmeier W H, Smith D D. Predicting rainfall-erosion losses from cropland east of the Rocky Mountains, USDA Agricultural Handbook No.282.Washington:USDA,1965.
[66]Renard K G., Fosrer G. R., Weesies G. A. et al. Coordinators Predicting soil erosion by water:A Guide to conservation planning with the Revised Universal Soil Loss Equation(RUSLE)[S]. USDA Agricultural Handbook,1997:703.
[67]Foster G. R. and L.J. Lane.1987. User requirements USDA-Water Erosion Prediction project (WEPP)[J].NSERL No.1, National Soil Erosion Research Laboratory, West Lafayette, Indiana.
[68]Nearing M A, Foster G R, Lane L J. A process-based soil erosion model for USDA-water erosion prediction project technology [J]. Trans of ASAE,1989,32(5):1587～1593.
[69]Flanagan, D.C, J.C. Ascough Ⅱ, A. D. Nicks, M. A. Nearing and J.M. Laflen; Overview of the WEPP Erosion Prediction,1995.
[70]Beasley DB, L F Huggins, and E J Monke. ANSWERS:A model for watershed Planning, Transactions of the ASAE23(4),1980:938～944.
[71]Bouraoui F., Dillaha T A. ANSWERS-2000:Runoff and sedment transport model [J]. Journal of Environmental Engineering.1996.122(6):493～502.
[72]Foster G R.. Lane L J., Nowlin J D., et al. A model to estinate sediment yield from field-sized areas:Development of model [A]. In:W. G. Knisel(ed) CREAMS:A field scale model for Chemicals, Runoff, and Erosion from Agricultural Management Systems [M].USDA, Sci and Educ Admin.. Conser Rep. No.26,1980:36～64.
[73]Knisel W G(ed).1980.CREAMS:A Field Scale Model for Chemicals. Runoff, and Erosion from Agricultural Management Systems. USDA, Conservation Research Report.No.26.
[74]Young R A..C.A. Onstad, D.D. Bosch, and W. P. Anderson, AGNPS:A non-point source pollution model for evaluating agricultural watershed[J]. Journal of Soil and Water Conservation.1989.44(2):168～173.
[75]Morgan R P C. Quinton J N.. Smith R E., et al. The European Soil Erosion Model (EUROSEM)[S(?) Documentation and user guide, version Silsoe College, Cranfield University.1998.
[76]De Roo A P J. Jetten V G. Calibrating and validating the LISEM Model for two data sets from the Netherlands and South Africa[J]. Catena.1999.37(3～4):477～493.
[77]Froster D L., R P Richards, D B Baker, et al. Blue EPIC modeling of the effects of farming practice changes on water quality in two lake Erie watersheds[J]. Journal of Soil and Water Conservation.2000,55(1):85～90.
[78]张建.CREAMS模型在计算黄土坡地径流量及侵蚀量中的应用[J].土壤侵蚀与水土保持报,1995,1(1)：54～57.
[79]陈一兵ANSWERS土壤侵蚀模型及其应用[J].土壤农化通报.1998,13(2)：28～32.
[80]刘宝元.中国土壤侵蚀预报模型研究[R].第12届国际水土保持大会,北京,2001.
[81]傅伯杰，邱扬,王军，等.黄土丘陵小流域土地利用变化对水土流失的影响[J].地理报，2002,57(6)：717～722.
[82]常欣,邱化蛟,等.计算机模拟模型在黄土丘陵区土地可持续利用中的实证研究[J].农业工程学报,2003，19(4)：295-298.
[83]徐崇刚.胡远满,常禹,等.空间直观景观模型在呼中林区土侵蚀预测研究中的初步应用[J]．应用生态学报,2004,15(10)：1821～1828.
[84]任希岩,张雪松,郝芳华.等.DEM分辨率对产流产沙模拟影响研究[J].水土保持研究,2004.11(1)：1～5.
[85]雷廷武,张晴雯,姚春梅，等.WEPP模型中细沟可蚀性参数估计方法误差的理论分析[J].农业工程学报,2005.21(1)：9～12.
[86]杨武德,王兆骞.红壤坡地不同利用方式土壤侵蚀模型研究[J].土壤侵蚀与水土保持学报,1999.5(1)：52-58.
[87]白清俊，刘业相.流域坡面综合产流数学模型的研究[J].土壤侵蚀与水土保持报,1999,5(3)：54～58.
[88]王协康,方铎.土壤侵蚀产沙量的人工神经网格模拟[J].神经网络模拟[J].成都理工学院学报,2000.27(2)：197～201.
[89]符素华.张卫国.刘宝元，等.北京山区小流域土壤侵蚀模型[J].水土保持研究，2001.8(4)：114-120.
[90]唐政洪,蔡强国,李忠武,等.GIS与小流域侵蚀产沙模型在淤地坝设计中的应用[J].水土保持学报,2002,16(1)：55～58.
[91]张佳华,姚凤梅.江西兴国土壤侵蚀动态的研究[J].北京林业大学学报,2004,26(1)：53～56.
[92]徐向舟,张红武,张羽,等.坡面水土流失比尺模型相似性的试验研究[J].水土保持学报,2005,19(1)：25～28.
[93]Foster G R,Lane L J.User requirements,USDA-Water Erosion Prediction Project(WEPP)[R] NSERL Report No.1,West Lafayette:USDA- ARS National Soil Erosion Research Laboratory,1987.
[94]Nearing M A,Lane L J,Alberts E E,et al.Prediction technology for soil erosion by water:status and research needs[J].Soil Sei.Soc.Am.J.,1990,54(6):1702-1711.
[95]Laflen J M,Lwonard J L,Foster G R.WEPP a new generation of erosion prediction technology[J].J of Soil and Water Cons.,1991,46(1):34～38.
[96]Foster G R, Nearing M A,Laflen J M.et al.Hillslope Erosion Component,chll.USDA-Water Erosion Prediction Project,Hillslope Profile and Watershed Model Documentation[R].W Lafayette:Ind:NSERL Report No.10.USDA-ARS.Purdue Univ.,1995.
[97]刘宝元,史培军.WEPP水蚀预报流域模型[J]..水土保持通报,1998,18(5).
[98]Savabi M R,Flanagan D C,et al.WEPP和GIS—GRASS在小流域中的应用[J].水土保持科技情报,1995,(3)：28～30.
[99]Savabi M R(?)用WEPP模型模拟地下排水和地表径流[J].黑龙江水利科技,1996,(2)：119～124.
[100]Baffaut C,Nearing M A,AscoughII J C, et al.The W EPP watershed model:Ⅱ.Sensitivity and discrimination on small watersheds[J].Trans.ASAE,1996,40(4):935-944.
[101]Liu B Y,Nearing M A, Baffaut C,The W EPP watershed model:Ⅲ. Com-parisons to measured data from small watersheds[J].Trans.ASAE,1997,40(4):945～952.
[102]Williams J,Nearing M,Nicks A,et al利用土壤侵蚀模型研究全球变化[J].水土保持科技情报,1998,(2)：14～19.
[103]Laflen JM,et al用编程的WEPP软件预测水蚀[J].水土保持科技情报,1998,(3)：42～46.
[104]Cochrane T A,Flanagan D C基于GIS和DEM下的WEPP模型对水蚀的评价[J].水土保持科技情报,2001,(4)：20～25.
[105]Joan Q Wu,Xu Arthur C,Elliot William J改进WEPP研究森林小区的土壤侵蚀[J].中国水土保持,2002,(2)：40.
[106]谢春燕,陈晓燕,何炳辉,等.土壤可蚀性在WEPP模型中的应用[J].水土保持科技情报,2003,(4)：6～9.
[107]唐政洪,蔡强国,侵蚀产沙漠型研究进展和GIS应用[J].泥沙研究,2002,10,NO.5.
[108]幸定武,基于WEPP.模型的降雨径流调控数值模拟研究[D].陕西：西北农林科技大学,2008：8～9,12～18.
[109]林素兰,黄毅,聂振刚等.辽北低山丘陵区坡耕地土壤流失方程的建立[J].土壤通报,1997,28(6)：251～253.
[110]J C AscoughⅡ,C Baffaut,M A Nearing and,Y Liu.1997.The WEPP Watershed Model I Hydrology and Erosion. Transactions of the ASAE.40(4):921～933.
[111]牛志明,解明署.新一代土壤水蚀预测模型——WEPP[J].中国水土保持SWCC,2001,(1):20-21.
[112]吴金栋,王馥棠.利用随机天气模式及多种插值方法生成逐日气侯变化情景的研究[J].用气象学报,2000.11(2)：129～136.
[113]缪驰远，何丙辉,陈晓燕等.WEPP模型中的CLIGEN与BPCDG应用对比研究[J].中国农学通报.2004,20(6)：321～324.
[114]张光辉.CLIGEN天气发生器在黄河流域的适应性研究[J].水土保持学报.2004，18(1):75-178,196.
[115]廖要明,张强,陈德亮.中国天气发生器降水模拟[J].地理学报.2004,59(5)：689-698.
[116]张岩，朱清科.土壤侵蚀过程模型中的天气生成器研究述评[J].中国水土保持科学,2006，4(3)：103-108.
[117]史婉丽，杨勤抖,穆婉红.随机气候生成器在黄土高原的适用性检验[J].中国水土保持科2006,4(2)：18～23.
[118]Richardson, C.W. Dependence structure of daily temperature and solar radiation [J].Trans.ASAE.1982.25:735～739.
[119]李志,刘文兆，张勋昌,等.CLIGEN降水要素在黄土塬区的适应性评估[J].中国水土保持科学.2006,4(6)：31～36.
[120]何丙辉,缪弛远,陈晓燕.等.CLIGEN气候生成器模型在紫色土地区的适应性研究.水土保持学报,2007,21(3)：183～187.
[121]王幼奇,樊军，邰明安.LARS-WG天气发生器在黄土高原的适应性研究[J].中国水土保持科学2007,5(3)：24～27.
[122]刘淑燕,秦富仓，项元和，等.基于WEPP模型进行坡度因子与侵蚀量关系研究.干旱区资源与环境,2006.20(4)：97～101.
[123]王建勋.WEPP模型(坡面版)在黄土高原丘陵沟壑区的适用性评价[D].陕西：西北农林科技大学,2006：13～1 5,30.
[124]王建勋，郑粉莉.江忠善等.WEPP模型坡面版在黄土丘陵沟壑区的适用性评价——以坡长因子为例[J].水土保持通报.2007,27(2)：50～55.
[125]缪驰远.何丙辉,陈晓燕,等.CSLE与WEPP土壤可蚀性因子的关联性分析[J]，中国水土保持，2004年第6期.23～25.
[126]张晴雯,雷廷武.姚春梅.等.WEPP细沟剥蚀率模型正确性的理论分析与实验验证.农业工程学报.2004,20(1)：35～39.
[127]宙廷武,张晴雯,赵军.陡坡纸沟含沙水流剥蚀率的试验研究及其计算方法.农业工程学报，2001,17(3)：24～27.
[128]张晴雯.细沟投流剥蚀率与载沙量以及沟长的耦合关系水土保持学报，2001,15(2)：92～95
[129]张晴雯,应用REE示踪法研究细沟流净剥蚀率.土壤学报，2005，42(1)：163～166.
[130]张靖雯.细沟侵蚀性参数及土壤临界抗剪应力的有理(实验)求解方法.中国科学究生院学报,2004,(4)：468-475.
[131]张岩,袁建平,刘宝元.土壤侵蚀预报模型中的植被覆盖与管理因子研究进展[J].应用生态 学报,2002.8：1033～1036.
[132]蒋定生,江忠善等.黄土高原丘陵区水土流失规律与水土保持措施优化配置研究[J].水土保持学报,1992,6(3).
[133]江忠善,王志强,刘志.黄土丘陵区小流域土壤侵蚀空间变化定量研究[J].土壤侵蚀与水土保持学报,1996,1(2)：1-9.
[134]江忠善,王志强,刘志.应用地理信息系统评价黄土丘陵区小流域土壤侵蚀的研究.见：第二届全国泥沙基本理论研究学术讨论会论文集.1995.
[135]张岩,刘宝元.不同植被类型对土壤水蚀的影响[J].植物学报.2003,45(10)：1204-1209.
[136]邱扬,傅伯杰等.黄土丘陵小流域土壤侵蚀的时空变异及其影响因子[J].生态学报.2004,9：1871～1877.
[137]张建辉,刘刚才等.紫色土不同土地利用条件下的土壤抗冲性研究[J].中国科学E辑.2003,33(B12)：61～68.
[138]蔡庆,唐克丽.植被对土壤侵蚀影响的动态分析[J].水土保持学报.1992,6(2)：47～51.
[139]罗伟祥,白立强.不同覆盖度林地和草地的径流量与冲刷量[J].水土保持学报.1990,1：30～35.
[140]侯喜芦,梁一民,曹清玉.黄土丘陵区林草地水土保持效益研究[M].中科院、水利部水土保持研究所集刊.1991,14.
[141]余新晓,毕华兴.黄土地区森林植被水土保持作业研究!J].植物生态学报1997,21(5)：433～440.
[142]石生新,蒋定生.关于渗透和土壤流失的几种保护措施效应研究[J].水土保持研究1994,1(1).
[143]张光辉,梁一民.黄土丘陵区人工草地盖度季动态及其水保效益[J].水土保持通报.1995,15(2)：38～43.
[144]邓慧平,李秀彬等.流域土地覆被变化水文效应的模拟[J].地理学报.2003,58(1)：53～62.
[145]吴钦孝.黄土高原植被保持水土功能和机理研究及趋势.中国科学院水利部水土保持研究所、黄土高原土壤侵蚀与早地农业国家重点试验室主编.土壤侵蚀环境调控制与农业持续发展.1995.
[146]孙立达,朱金兆.水土保持林体系综合效益研究与评价[M].北京：中国科学技术出版社,1995.
[147]王治国,张云龙等.林业生态工程学—林草植被建设的理论与实践[M].北京：中国林业出版社,2000：54～58.
[148]吴钦孝,赵鸿雁,刘向东.森林枯落物对水资源和水土保持作用的评价[J].土壤侵蚀与水土保持学报.1998,4(2)：23～28.
[149]吴钦孝,刘向东.山杨次生林枯枝落叶蓄积量及其水文作用[J].水土保持学报.1992,6(1)：71～76.
[150]吴钦孝,赵鸿雁,韩冰.黄土高原森林枯枝落叶层保持水土的有效性[J].西北农林科技大学学报(自然科学版)2001,29(5)：95～98.
[151]李勇,朱显谟,田积莹.黄十高原植物根系提高土壤抗蚀性的有效性[J].科学通报.1991,!2：307～378.
[152]吴钦孝,李勇.黄土高原植物根系提高土壤抗冲性能的研究[J].水土保持学报.1990,4(I)：11～16.
[153]郑粉莉.美国土壤侵蚀过程及其预报模型研究进展[J].水土保持通报,2003,23(3)：1～5.
[154]陈晓燕,何丙辉,缪驰远,等.WEPP模型在紫色土坡面侵蚀预测中的应用研究[J].水土保持学报,2003,17(3)：42～44.
[155]莫放，贾忠华.罗纨.等.基于水蚀模型WEPP和GIS的高原小流域侵蚀模拟——以延安地区向阳沟小流域为例[J].水资源与工程学报.2005，16(4)：41-45.
[156]缪驰远,保丙辉,陈晓燕.水蚀模型USLE与WEPP住紫色土水蚀预测中的应用对比研究农业工程学报,2005.21(1)：13～16.
[157]景卫华，贾忠华,罗纨，等.WEPP模型在黄土地区的适用性分析.水资源与水工程学报2006.17(2)：28～31.
[158]郑进军.张信宝,贺秀斌.用中丘陵医坡耕地侵蚀空间分布的WEPP模型和137Cs法研究[J].水土保持学报2007，21(2)：19-23.
[159]史婉丽.WEPP模型在黄土高原小流域的应用[D].北京：中国科学院教育部水土保持与生态环境研究中心.2006.
[160]严冬春,文安邦，张忠启.等.坡面版WEPP模型在(?)中丘陵区的应用研究.水土保持学报,2007,21(5)：42～45.
[161]陈晓燕.紫色土坡面土壤侵蚀预测模型应用研究[D].重庆：西南农业大学,2003：23～30.
[162]杨剑虹等.土壤农化分析与环境监测[M].北京,中国大地出版社,2008：19,27,78,88,171.185.
[163]皮广洁，唐书源.农业环境监测原理与应用[M].成都,成都科技大学出版社,1998：69-80.
[164]中国科学院南京土壤研究所土壤物理研究室.土壤物理性质测定法[M].科学出版社,1978：11，26,99.
[165]Zhang X-C. Calibration, refinement, and application of the WEPP model for simulation climatic impact on wheat production. American Society of Agricultural Engineer,2004,47(4):1075～1085.
[166]胡川.无形资产评估中运用敏感性分析的探讨[J].数量经济技术经济研究,2003,1：57～60.
[167]孙雪.大气环境影响预测模式中参数的敏感性分析[D].黑龙江：东北林业大学.2009：14～15.
[168]朱正旺，练松良.轨道参数对无缝线路稳定性影响的敏感性分析[J].中国铁道科学,2004，2S(1)：72～75.
[169]李慧,靳晟,雷晓云,朱连勇,张翔.SWAT模型参数敏感性分析与自动率定的重要性研究[J].水资源与水工程学报,2010,21(1)：79-82.
[26]Latlen J.M. et al.WEPP-Predicting water erosion using a process-based model. J.soil water cors. 1997.52(2):96～102.
[27]Vieux B E Geographic information systems and non-point source water quality and quantity modeling. Hydrological Processes,1991.5:101～113.
[28]Chow T L,Daigle J L.Ghanem I,Cormier H. Effects of potato cropping on water run-off and soil erosion.Can.J. Soil Sci.990.70:137-148.
[29]王锐亮,川北紫色土深丘区小流域降雨及土壤侵蚀特征分析[D].重庆：西南大学.2007：1～4.
[30]罗细芳，姚小华.水土流失机理与模型研究进展[J].江西农业大学学报.2004，26(5)：813～817.
[31]夏卫生.具有中国特色的水土保持科学体系[J].水土保持通报.1989,9(4)：30～35.
[32]刘善建.天水水土流失试验站的初步分析[J].科学通报，1953，12：59～65.
[33]杨建英,赵廷宁.坡面侵蚀研究现状及展望[J].北京林业大学学报.1994.16(1)：95～101.
[34]周佩华,李银锄,黄义端.等.2000年中国水土流失趋势预测及其防治对策[J].见：中国科学学院西北水土保持研究所集刊(第7集),1988：57～71.
[35]胡良军，李锐,杨勤科.基于GIS的区域水土流失评价研究[J].土壤学报,2001.38(2)：169～174.
[36]张宝信.黄土高原小流域泥沙来源的137Cs法的研究[J].科学通报,1989,(3)：210～213.
[37]田均良，周佩华.土壤侵蚀REE示踪法研究初报[J].水土保持学报,1992,6(4)：23～27.
[38]汤立群.流域产沙模型的研究[J].水科学进展,1996，7(1)：47～53.
[39]蔡强国,陆兆熊，王(?)平.黄土丘陵沟壑区典型小流域侵蚀产沙过程模拟[J].地理学报.1996.51(2)：108～116.
[40]李文银.王治国,蔡继清.工矿区水土保持[M].北京：科学出版社,1996：127.
[41]白中科等.工矿区土地复垦与生态重建[M].北京：中国农业科技出版社，2000,4：1～18.
[42]叶翠玲.许兆义,杨成永.秦沈客运专线建设过程中的水土流失实验研究[J].水土保持学报.2001.15(2)：9～13.
[43]杨成永,王美芝，许兆义等.秦沈客运专线路堤边坡土壤侵蚀预报研究[J].水土保持学报.2001.15(2)：14～16.
[44]李忠武,蔡强国，吴淑安.等.内昆铁路施工期不同下垫面土壤侵蚀模拟研究[J].水土保持学报．2001，15(2)：5～8.
[45]唐晓春,谢世友，罗鉴银,等.南昆铁路威红区段家河流域地貌演化与水土流失[J].水土保持学报，1993,7(4)：1～7.
[46]孙虎,甘枝茂.城市周边地区侵蚀景观特征分析[J].土壤侵蚀与水土保持学报，1998，4(4)：31～36.
[47]张玉斌,郑粉莉.贾媛媛.WEPP模型概述.水土保持研究2004，11(4)：146～149.
[48]莫放,水蚀模型WEPP与GIS的联合应用[D]，陕西,西安理工大学，2004：3.13.
[49]Zingg A W. Degree and length of Land Slope as It Affects Soil Loss in Runoff [J]. Agricultural Engineering.1940.21:59～64..
[50]Musgrave G W. The Quantitative Evaluation of Factors in Water Erosion[J].Soil and Water Conservation.1947:2(3)133～138.
[51]Wischmeier W H and Smith D D. Rainfall Energy and Its Relation to Soil Loss [M].Trans AM Geography. Union,1958,39.285～291.
[52]Wischmeier W H, Smith D D and Uhland R E. Evaluation of Factors in the Soil Loss Equation, [M] Agric Eng,1985,39,458-464.
[53]贾志伟等.降雨特征与水土流失的研究.中国科学院水利部西北水土保持研究所集刊[J],1990,12,9～15.
[54]Negev M A.A Sediment Model on a Digital Computer,Technical Report 76, Deportment of Civil Engineering, Stanford University,1967.
[55]Meyer L D. and Wischmeier W H. Mathematical Simulation of Process of Soil Erosion by Water,Trans. ASAE,1969,12(6).
[56]Foster G R. and Meyer L D. Mathematical Simulation of Upland Erosion by Fundamental Erosion Principles, Trans. ASAE,1975,20 (4).
[57]David W P. and Beer C E. Simulation of Soil Erosion,Part Ⅰ,Development of a Mathematical Erosion Model,Trans. ASAE,1975,18(1).
[58]Fogel M M, Heknan and Duckstein L.A stochastic Sediment Yield Model Using the Modified Universal, Soil Loss Equation, In:Soil Erosion:Prediction and Control, Soil Conservation Society of America, Special Publication,1976,21.
[59]Julien P Y. Soil Erosion Loss from Upland Areas, Proc, the 4th International Symposium on River Sedimentation,1989.
[60]中华人民共和国水利部.土壤侵蚀分类分级标准[1997-02-13].北京：中国水利出版社,1997.
[61]缪驰远,WEPP模型在紫色土地区的应用及与USLE的对比研究[D].重庆：西南农业大学,2005：2,10，16-20.
[62]李进峰,嘉陵江上游不同土地利用方式土坡侵蚀模型应用研究[D].四川：四川农业大学,2007：2.
[63]李勉,李占斌.中国土壤侵蚀定量研究进展[J].水土保持研究2002,vol.9.No.3.
[64]Wischmeier W H, Smith D D.A universal soil loss equation to guide conservation farm planning trans 7th International Cong. Soil Sci,1960,1:418～425.
[65]Wischmeier W H, Smith D D. Predicting rainfall-erosion losses from cropland east of the Rocky Mountains, USDA Agricultural Handbook No.282.Washington:USDA,1965.
[66]Renard K G., Fosrer G. R., Weesies G. A. et al. Coordinators Predicting soil erosion by water:A Guide to conservation planning with the Revised Universal Soil Loss Equation(RUSLE)[S]. USDA Agricultural Handbook,1997:703.
[67]Foster G. R. and L.J. Lane.1987. User requirements USDA-Water Erosion Prediction project (WEPP)[J].NSERL No.1, National Soil Erosion Research Laboratory, West Lafayette, Indiana.
[68]Nearing M A, Foster G R, Lane L J. A process-based soil erosion model for USDA-water erosion prediction project technology [J]. Trans of ASAE,1989,32(5):1587～1593.
[69]Flanagan, D.C, J.C. Ascough Ⅱ, A. D. Nicks, M. A. Nearing and J.M. Laflen; Overview of the WEPP Erosion Prediction,1995.
[70]Beasley DB, L F Huggins, and E J Monke. ANSWERS:A model for watershed Planning, Transactions of the ASAE23(4),1980:938～944.
[71]Bouraoui F., Dillaha T A. ANSWERS-2000:Runoff and sedment transport model [J]. Journal of Environmental Engineering.1996.122(6):493～502.
[72]Foster G R.. Lane L J., Nowlin J D., et al. A model to estinate sediment yield from field-sized areas:Development of model [A]. In:W. G. Knisel(ed) CREAMS:A field scale model for Chemicals, Runoff, and Erosion from Agricultural Management Systems [M].USDA, Sci and Educ Admin.. Conser Rep. No.26,1980:36～64.
[73]Knisel W G(ed).1980.CREAMS:A Field Scale Model for Chemicals. Runoff, and Erosion from Agricultural Management Systems. USDA, Conservation Research Report.No.26.
[74]Young R A..C.A. Onstad, D.D. Bosch, and W. P. Anderson, AGNPS:A non-point source pollution model for evaluating agricultural watershed[J]. Journal of Soil and Water Conservation.1989.44(2):168～173.
[75]Morgan R P C. Quinton J N.. Smith R E., et al. The European Soil Erosion Model (EUROSEM)[S(?) Documentation and user guide, version Silsoe College, Cranfield University.1998.
[76]De Roo A P J. Jetten V G. Calibrating and validating the LISEM Model for two data sets from the Netherlands and South Africa[J]. Catena.1999.37(3～4):477～493.
[77]Froster D L., R P Richards, D B Baker, et al. Blue EPIC modeling of the effects of farming practice changes on water quality in two lake Erie watersheds[J]. Journal of Soil and Water Conservation.2000,55(1):85～90.
[78]张建.CREAMS模型在计算黄土坡地径流量及侵蚀量中的应用[J].土壤侵蚀与水土保持报,1995,1(1)：54～57.
[79]陈一兵ANSWERS土壤侵蚀模型及其应用[J].土壤农化通报.1998,13(2)：28～32.
[80]刘宝元.中国土壤侵蚀预报模型研究[R].第12届国际水土保持大会,北京,2001.
[81]傅伯杰，邱扬,王军，等.黄土丘陵小流域土地利用变化对水土流失的影响[J].地理报，2002,57(6)：717～722.
[82]常欣,邱化蛟,等.计算机模拟模型在黄土丘陵区土地可持续利用中的实证研究[J].农业工程学报,2003，19(4)：295-298.
[83]徐崇刚.胡远满,常禹,等.空间直观景观模型在呼中林区土侵蚀预测研究中的初步应用[J]．应用生态学报,2004,15(10)：1821～1828.
[84]任希岩,张雪松,郝芳华.等.DEM分辨率对产流产沙模拟影响研究[J].水土保持研究,2004.11(1)：1～5.
[85]雷廷武,张晴雯,姚春梅，等.WEPP模型中细沟可蚀性参数估计方法误差的理论分析[J].农业工程学报,2005.21(1)：9～12.
[86]杨武德,王兆骞.红壤坡地不同利用方式土壤侵蚀模型研究[J].土壤侵蚀与水土保持学报,1999.5(1)：52-58.
[87]白清俊，刘业相.流域坡面综合产流数学模型的研究[J].土壤侵蚀与水土保持报,1999,5(3)：54～58.
[88]王协康,方铎.土壤侵蚀产沙量的人工神经网格模拟[J].神经网络模拟[J].成都理工学院学报,2000.27(2)：197～201.
[89]符素华.张卫国.刘宝元，等.北京山区小流域土壤侵蚀模型[J].水土保持研究，2001.8(4)：114-120.
[90]唐政洪,蔡强国,李忠武,等.GIS与小流域侵蚀产沙模型在淤地坝设计中的应用[J].水土保持学报,2002,16(1)：55～58.
[91]张佳华,姚凤梅.江西兴国土壤侵蚀动态的研究[J].北京林业大学学报,2004,26(1)：53～56.
[92]徐向舟,张红武,张羽,等.坡面水土流失比尺模型相似性的试验研究[J].水土保持学报,2005,19(1)：25～28.
[93]Foster G R,Lane L J.User requirements,USDA-Water Erosion Prediction Project(WEPP)[R] NSERL Report No.1,West Lafayette:USDA- ARS National Soil Erosion Research Laboratory,1987.
[94]Nearing M A,Lane L J,Alberts E E,et al.Prediction technology for soil erosion by water:status and research needs[J].Soil Sei.Soc.Am.J.,1990,54(6):1702-1711.
[95]Laflen J M,Lwonard J L,Foster G R.WEPP a new generation of erosion prediction technology[J].J of Soil and Water Cons.,1991,46(1):34～38.
[96]Foster G R, Nearing M A,Laflen J M.et al.Hillslope Erosion Component,chll.USDA-Water Erosion Prediction Project,Hillslope Profile and Watershed Model Documentation[R].W Lafayette:Ind:NSERL Report No.10.USDA-ARS.Purdue Univ.,1995.
[97]刘宝元,史培军.WEPP水蚀预报流域模型[J]..水土保持通报,1998,18(5).
[98]Savabi M R,Flanagan D C,et al.WEPP和GIS—GRASS在小流域中的应用[J].水土保持科技情报,1995,(3)：28～30.
[99]Savabi M R(?)用WEPP模型模拟地下排水和地表径流[J].黑龙江水利科技,1996,(2)：119～124.
[100]Baffaut C,Nearing M A,AscoughII J C, et al.The W EPP watershed model:Ⅱ.Sensitivity and discrimination on small watersheds[J].Trans.ASAE,1996,40(4):935-944.
[101]Liu B Y,Nearing M A, Baffaut C,The W EPP watershed model:Ⅲ. Com-parisons to measured data from small watersheds[J].Trans.ASAE,1997,40(4):945～952.
[102]Williams J,Nearing M,Nicks A,et al利用土壤侵蚀模型研究全球变化[J].水土保持科技情报,1998,(2)：14～19.
[103]Laflen JM,et al用编程的WEPP软件预测水蚀[J].水土保持科技情报,1998,(3)：42～46.
[104]Cochrane T A,Flanagan D C基于GIS和DEM下的WEPP模型对水蚀的评价[J].水土保持科技情报,2001,(4)：20～25.
[105]Joan Q Wu,Xu Arthur C,Elliot William J改进WEPP研究森林小区的土壤侵蚀[J].中国水土保持,2002,(2)：40.
[106]谢春燕,陈晓燕,何炳辉,等.土壤可蚀性在WEPP模型中的应用[J].水土保持科技情报,2003,(4)：6～9.
[107]唐政洪,蔡强国,侵蚀产沙漠型研究进展和GIS应用[J].泥沙研究,2002,10,NO.5.
[108]幸定武,基于WEPP.模型的降雨径流调控数值模拟研究[D].陕西：西北农林科技大学,2008：8～9,12～18.
[109]林素兰,黄毅,聂振刚等.辽北低山丘陵区坡耕地土壤流失方程的建立[J].土壤通报,1997,28(6)：251～253.
[110]J C AscoughⅡ,C Baffaut,M A Nearing and,Y Liu.1997.The WEPP Watershed Model I Hydrology and Erosion. Transactions of the ASAE.40(4):921～933.
[111]牛志明,解明署.新一代土壤水蚀预测模型——WEPP[J].中国水土保持SWCC,2001,(1):20-21.
[112]吴金栋,王馥棠.利用随机天气模式及多种插值方法生成逐日气侯变化情景的研究[J].用气象学报,2000.11(2)：129～136.
[113]缪驰远，何丙辉,陈晓燕等.WEPP模型中的CLIGEN与BPCDG应用对比研究[J].中国农学通报.2004,20(6)：321～324.
[114]张光辉.CLIGEN天气发生器在黄河流域的适应性研究[J].水土保持学报.2004，18(1):75-178,196.
[115]廖要明,张强,陈德亮.中国天气发生器降水模拟[J].地理学报.2004,59(5)：689-698.
[116]张岩，朱清科.土壤侵蚀过程模型中的天气生成器研究述评[J].中国水土保持科学,2006，4(3)：103-108.
[117]史婉丽，杨勤抖,穆婉红.随机气候生成器在黄土高原的适用性检验[J].中国水土保持科2006,4(2)：18～23.
[118]Richardson, C.W. Dependence structure of daily temperature and solar radiation [J].Trans.ASAE.1982.25:735～739.
[119]李志,刘文兆，张勋昌,等.CLIGEN降水要素在黄土塬区的适应性评估[J].中国水土保持科学.2006,4(6)：31～36.
[120]何丙辉,缪弛远,陈晓燕.等.CLIGEN气候生成器模型在紫色土地区的适应性研究.水土保持学报,2007,21(3)：183～187.
[121]王幼奇,樊军，邰明安.LARS-WG天气发生器在黄土高原的适应性研究[J].中国水土保持科学2007,5(3)：24～27.
[122]刘淑燕,秦富仓，项元和，等.基于WEPP模型进行坡度因子与侵蚀量关系研究.干旱区资源与环境,2006.20(4)：97～101.
[123]王建勋.WEPP模型(坡面版)在黄土高原丘陵沟壑区的适用性评价[D].陕西：西北农林科技大学,2006：13～1 5,30.
[124]王建勋，郑粉莉.江忠善等.WEPP模型坡面版在黄土丘陵沟壑区的适用性评价——以坡长因子为例[J].水土保持通报.2007,27(2)：50～55.
[125]缪驰远.何丙辉,陈晓燕,等.CSLE与WEPP土壤可蚀性因子的关联性分析[J]，中国水土保持，2004年第6期.23～25.
[126]张晴雯,雷廷武.姚春梅.等.WEPP细沟剥蚀率模型正确性的理论分析与实验验证.农业工程学报.2004,20(1)：35～39.
[127]宙廷武,张晴雯,赵军.陡坡纸沟含沙水流剥蚀率的试验研究及其计算方法.农业工程学报，2001,17(3)：24～27.
[128]张晴雯.细沟投流剥蚀率与载沙量以及沟长的耦合关系水土保持学报，2001,15(2)：92～95
[129]张晴雯,应用REE示踪法研究细沟流净剥蚀率.土壤学报，2005，42(1)：163～166.
[130]张靖雯.细沟侵蚀性参数及土壤临界抗剪应力的有理(实验)求解方法.中国科学究生院学报,2004,(4)：468-475.
[131]张岩,袁建平,刘宝元.土壤侵蚀预报模型中的植被覆盖与管理因子研究进展[J].应用生态 学报,2002.8：1033～1036.
[132]蒋定生,江忠善等.黄土高原丘陵区水土流失规律与水土保持措施优化配置研究[J].水土保持学报,1992,6(3).
[133]江忠善,王志强,刘志.黄土丘陵区小流域土壤侵蚀空间变化定量研究[J].土壤侵蚀与水土保持学报,1996,1(2)：1-9.
[134]江忠善,王志强,刘志.应用地理信息系统评价黄土丘陵区小流域土壤侵蚀的研究.见：第二届全国泥沙基本理论研究学术讨论会论文集.1995.
[135]张岩,刘宝元.不同植被类型对土壤水蚀的影响[J].植物学报.2003,45(10)：1204-1209.
[136]邱扬,傅伯杰等.黄土丘陵小流域土壤侵蚀的时空变异及其影响因子[J].生态学报.2004,9：1871～1877.
[137]张建辉,刘刚才等.紫色土不同土地利用条件下的土壤抗冲性研究[J].中国科学E辑.2003,33(B12)：61～68.
[138]蔡庆,唐克丽.植被对土壤侵蚀影响的动态分析[J].水土保持学报.1992,6(2)：47～51.
[139]罗伟祥,白立强.不同覆盖度林地和草地的径流量与冲刷量[J].水土保持学报.1990,1：30～35.
[140]侯喜芦,梁一民,曹清玉.黄土丘陵区林草地水土保持效益研究[M].中科院、水利部水土保持研究所集刊.1991,14.
[141]余新晓,毕华兴.黄土地区森林植被水土保持作业研究!J].植物生态学报1997,21(5)：433～440.
[142]石生新,蒋定生.关于渗透和土壤流失的几种保护措施效应研究[J].水土保持研究1994,1(1).
[143]张光辉,梁一民.黄土丘陵区人工草地盖度季动态及其水保效益[J].水土保持通报.1995,15(2)：38～43.
[144]邓慧平,李秀彬等.流域土地覆被变化水文效应的模拟[J].地理学报.2003,58(1)：53～62.
[145]吴钦孝.黄土高原植被保持水土功能和机理研究及趋势.中国科学院水利部水土保持研究所、黄土高原土壤侵蚀与早地农业国家重点试验室主编.土壤侵蚀环境调控制与农业持续发展.1995.
[146]孙立达,朱金兆.水土保持林体系综合效益研究与评价[M].北京：中国科学技术出版社,1995.
[147]王治国,张云龙等.林业生态工程学—林草植被建设的理论与实践[M].北京：中国林业出版社,2000：54～58.
[148]吴钦孝,赵鸿雁,刘向东.森林枯落物对水资源和水土保持作用的评价[J].土壤侵蚀与水土保持学报.1998,4(2)：23～28.
[149]吴钦孝,刘向东.山杨次生林枯枝落叶蓄积量及其水文作用[J].水土保持学报.1992,6(1)：71～76.
[150]吴钦孝,赵鸿雁,韩冰.黄土高原森林枯枝落叶层保持水土的有效性[J].西北农林科技大学学报(自然科学版)2001,29(5)：95～98.
[151]李勇,朱显谟,田积莹.黄十高原植物根系提高土壤抗蚀性的有效性[J].科学通报.1991,!2：307～378.
[152]吴钦孝,李勇.黄土高原植物根系提高土壤抗冲性能的研究[J].水土保持学报.1990,4(I)：11～16.
[153]郑粉莉.美国土壤侵蚀过程及其预报模型研究进展[J].水土保持通报,2003,23(3)：1～5.
[154]陈晓燕,何丙辉,缪驰远,等.WEPP模型在紫色土坡面侵蚀预测中的应用研究[J].水土保持学报,2003,17(3)：42～44.
[155]莫放，贾忠华.罗纨.等.基于水蚀模型WEPP和GIS的高原小流域侵蚀模拟——以延安地区向阳沟小流域为例[J].水资源与工程学报.2005，16(4)：41-45.
[156]缪驰远,保丙辉,陈晓燕.水蚀模型USLE与WEPP住紫色土水蚀预测中的应用对比研究农业工程学报,2005.21(1)：13～16.
[157]景卫华，贾忠华,罗纨，等.WEPP模型在黄土地区的适用性分析.水资源与水工程学报2006.17(2)：28～31.
[158]郑进军.张信宝,贺秀斌.用中丘陵医坡耕地侵蚀空间分布的WEPP模型和137Cs法研究[J].水土保持学报2007，21(2)：19-23.
[159]史婉丽.WEPP模型在黄土高原小流域的应用[D].北京：中国科学院教育部水土保持与生态环境研究中心.2006.
[160]严冬春,文安邦，张忠启.等.坡面版WEPP模型在(?)中丘陵区的应用研究.水土保持学报,2007,21(5)：42～45.
[161]陈晓燕.紫色土坡面土壤侵蚀预测模型应用研究[D].重庆：西南农业大学,2003：23～30.
[162]杨剑虹等.土壤农化分析与环境监测[M].北京,中国大地出版社,2008：19,27,78,88,171.185.
[163]皮广洁，唐书源.农业环境监测原理与应用[M].成都,成都科技大学出版社,1998：69-80.
[164]中国科学院南京土壤研究所土壤物理研究室.土壤物理性质测定法[M].科学出版社,1978：11，26,99.
[165]Zhang X-C. Calibration, refinement, and application of the WEPP model for simulation climatic impact on wheat production. American Society of Agricultural Engineer,2004,47(4):1075～1085.
[166]胡川.无形资产评估中运用敏感性分析的探讨[J].数量经济技术经济研究,2003,1：57～60.
[167]孙雪.大气环境影响预测模式中参数的敏感性分析[D].黑龙江：东北林业大学.2009：14～15.
[168]朱正旺，练松良.轨道参数对无缝线路稳定性影响的敏感性分析[J].中国铁道科学,2004，2S(1)：72～75.
[169]李慧,靳晟,雷晓云,朱连勇,张翔.SWAT模型参数敏感性分析与自动率定的重要性研究[J].水资源与水工程学报,2010,21(1)：79-82.
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