Assessing the USLE Crop and Management Factor C for Soil Erosion Modeling in a Large Mountainous Watershed in Central China

Due to the impoundment of the Yangtze River, the Three Gorges Dam in China fosters high land-use dynamics. Soil erosion is expected to increase dramatically. One of the key factors in soil erosion control is the vegetation cover and crop type. However, determining these factors adequately for the use in soil erosion modeling is very time-consuming especially for large mountainous areas, such as the Xiangxi （香溪） catchment in the Three Gorges area. In our study, the crop and management factor C was calculated using the fractional vegetation cover （CFvc） based on Landsat-TM images from 2005, 2006, and 2007 and on literature studies （CLIT）. In 2007, the values of CFvc range between 0.001 and 0.98 in the Xiangxi catchment. The mean CFVC value is 0.05. CLIT values are distinctly higher, ranging from 0.08 to 0.46 with a mean value of 0.32 in the Xiangxi catchment. The mean potential soil loss amounts to 120.62 t/ha/a in the Xiangxi catchment when using CLIT for modeling. Based on CFVC, the predicted mean soil loss in the Xiangxi catchment is 11.50 t/ha/a. Therefore, CLIT appears to bemore reliable than the C factor based on the fractional vegetation cover.

An estimation method of soil wind erosion in Inner Mongolia of China based on geographic information system and remote sensing

Studies of wind erosion based on Geographic Information System（GIS） and Remote Sensing（RS） have not attracted sufficient attention because they are limited by natural and scientific factors.Few studies have been conducted to estimate the intensity of large-scale wind erosion in Inner Mongolia,China.In the present study,a new model based on five factors including the number of snow cover days,soil erodibility,aridity,vegetation index and wind field intensity was developed to quantitatively estimate the amount of wind erosion.The results showed that wind erosion widely existed in Inner Mongolia.It covers an area of approximately 90×104 km2,accounting for 80% of the study region.During 1985–2011,wind erosion has aggravated over the entire region of Inner Mongolia,which was indicated by enlarged zones of erosion at severe,intensive and mild levels.In Inner Mongolia,a distinct spatial differentiation of wind erosion intensity was noted.The distribution of change intensity exhibited a downward trend that decreased from severe increase in the southwest to mild decrease in the northeast of the region.Zones occupied by barren land or sparse vegetation showed the most severe erosion,followed by land occupied by open shrubbery.Grasslands would have the most dramatic potential for changes in the future because these areas showed the largest fluctuation range of change intensity.In addition,a significantly negative relation was noted between change intensity and land slope.The relation between soil type and change intensity differed with the content of Ca CO3 and the surface composition of sandy,loamy and clayey soils with particle sizes of 0–1 cm.The results have certain significance for understanding the mechanism and change process of wind erosion that has occurred during the study period.Therefore,the present study can provide a scientific basis for the prevention and treatment of wind erosion in Inner Mongolia.

Comparison of Slope Length Factor Extraction in Hillslope Soil Erosion Model with Different DEM Resolutions

In this study, non-cumulative slope length(NCSL) calculation method and spatial analytical calculation(SAC) method were respectively applied to extract slope length and slope length factor from 10 sample areas, which are located in Ansai County, north Shaanxi Province. The comparison of computation precision between variable DEM resolutions showed that NCSL was superior to SAC entirely. And the results were best when the DEM resolutions were 5 and 10 m. Besides, the results of slope length factor were nearly the same under the two conditions. So DEM of 10 m resolution can be used to extract slope length.

Applying seepage modeling to improve sediment yield predictions in contour ridge systems

Contour ridge systems may lead to seepage that could result in serious soil erosion. Modeling soil erosion under seepage conditions in a contour ridge system has been overlooked in most current soil erosion models. To address the importance of seepage in soil erosion modeling, a total of 23 treatments with 3 factors, row grade, field slope and ridge height, in 5 gradients were arranged in an orthogonal rotatable central composite design. The second-order polynomial regression model for predicting the sediment yield was improved by using the measured or predicted seepage discharge as an input factor, which increased the coefficient of determination(R^2) from 0.743 to 0.915 or 0.893. The improved regression models combined with the measured seepage discharge had a lower P(0.007) compared to those combined with the predicted seepage discharge(P=0.016). With the measured seepage discharge incorporated, some significant(P<0.050) effects and interactions of influential factors on sediment yield were detected, including the row grade and its interactions with the field slope, ridge height and seepage discharge, the quadratic terms of the field slope and its interactions with the row grade and seepage discharge. In the regression model with the predicted seepage discharge as an influencing factor, only the interaction between row grade and seepage discharge significantly affected the sediment yield. The regression model incorporated with predicted seepage discharge may be expressed simply and can be used effectively when measured seepage discharge data are not available.