期刊文献+
共找到2篇文章
< 1 >
每页显示 20 50 100
Comparison of Slope Length Factor Extraction in Hillslope Soil Erosion Model with Different DEM Resolutions
1
作者 Feng KONG 《Agricultural Biotechnology》 CAS 2020年第1期89-95,共7页
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 ... 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. 展开更多
关键词 DEM RESOLUTION Slope length Precision differentiation soil erosion model
下载PDF
Applying seepage modeling to improve sediment yield predictions in contour ridge systems
2
作者 LIU Qianjin MA Liang ZHANG Hanyu 《Journal of Arid Land》 SCIE CSCD 2020年第4期676-689,共14页
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... 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. 展开更多
关键词 soil erosion model contour ridge SEEPAGE geometry factors rainfall simulation
下载PDF
上一页 1 下一页 到第
使用帮助 返回顶部