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Use of the Water Erosion Prediction Project (WEPP) model to predict road surface erosion in mountain rangeland areas.

机译:使用水蚀预测项目(WEPP)模型来预测山区草地的路面侵蚀。

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The Watershed Erosion Prediction Project (WEPP) model represents the most current erosion prediction technology. WEPP has been applied to the problems of logging road erosion in more mesic forests but has not been tested or evaluated on roadways located in semiarid mountainous ecosystems.; Six rainfall simulation experiments were conducted to measure runoff and sediment yield off three separate plots located on Tickville Road, located on Camp W.G. Williams, a National Guard Training Center in Utah.; There was an excellent correlation between predicted and observed total runoff volumes for all simulations (R{dollar}sp2{dollar} = 0.96). The differences were greater than 10% only for plot 2 wet; otherwise, the average difference for all six simulations was 4.9%. When using Kr, Ki, and TAUc as predicted by rangeland methods, predicted sediment yields differed from those measured, on average, by 82%. Predicted sediment yields differed by only 22% compared to calculated sediment yields, when using the cropland erodibility equations to predict Kr, Ki, and TAUc. A sensitivity analysis showed that percent slope, slope length, days since last tillage, and ridge roughness all had a significant impact on WEPP predicted sediment yields. Results show the effectiveness of the WEPP model in predicting runoff and erosion off native surfaced roads in these semiarid mountainous regions. (Abstract shortened by UMI.)
机译:流域侵蚀预测项目(WEPP)模型代表了最新的侵蚀预测技术。 WEPP已被用于解决更多的中性森林伐木道路侵蚀问题,但尚未在半干旱山区生态系统的道路上进行测试或评估。进行了六次降雨模拟实验,以测量位于犹他州国民警卫队训练中心W.G. Williams营地Tickville Road上三个不同地块的径流和沉积物产量;所有模拟的预测和观测总径流量之间都具有极好的相关性(R {dollar} sp2 {dollar} = 0.96)。仅在地块2湿润时,差异大于10%。否则,所有六个模拟的平均差异为4.9%。当按照牧场方法预测使用Kr,Ki和TAUc时,预测的泥沙产量与平均测得的泥沙产量相差82%。当使用农田侵蚀性方程式预测Kr,Ki和TAUc时,预测的泥沙产量与计算的泥沙产量仅相差22%。敏感性分析表明,坡度百分比,坡度长度,上次耕作后的天数和山脊粗糙度均对WEPP预测的泥沙产量有重大影响。结果表明,WEPP模型在预测这些半干旱山区天然路面的径流和侵蚀方面是有效的。 (摘要由UMI缩短。)

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