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Predicting the annual erosion rates on a small stream by the BANCS model

机译:通过Bancs模型预测一股小型流的年度侵蚀率

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The erosion of streambanks causes soil loss and degrades the stream habitat. To optimize the prevention of bank erosion, we first need to determine the most vulnerable places on banks. This can be done by the BANCS model. However, data are still missing on its accuracy in small streams. We measured the real annual erosion rates on 18 experimental sections established on the Lomnicka stream. Using the Near Bank Stress (NBS) and Bank Erosion Hazard Index (BEHI) we developed the erosion prediction curves and evaluated the relationship between these two indices and the real annual erosion rates. We found a strong relationship between BEHI and real annual erosion rates, with R-2 = 0.72. The relationship between the NBS index and real annual erosion rates was also strong, with R-2 = 0.53. Then we constructed erosion prediction curves for very high and extreme BEHI and for moderate and high BEHI. Despite the strong correlation between BEHI and annual erosion rates, the prediction curves had no real relationship with real annual erosion rates, with R-2 = 0.004 and 0.15, respectively.
机译:Streambanks的侵蚀会导致土壤损失,降低河流栖息地。为了优化防止银行侵蚀,我们首先需要确定银行最脆弱的地方。这可以通过Bancs模型来完成。但是,数据仍缺少其在小型流中的准确性。我们在Lomnicka Stream上建立的18个实验部分测量了真正的年度侵蚀利率。使用近岸压力(NBS)和银行侵蚀危险指数(BEHI)我们开发了侵蚀预测曲线,并评估了这两个指数与实际年度侵蚀率之间的关系。我们发现了Behi与真正的年度侵蚀率之间的牢固关系,R-2 = 0.72。 NBS指数与实际年度侵蚀率之间的关系也很强劲,R-2 = 0.53。然后我们构建了非常高和极端教育的侵蚀预测曲线和适度和高等教育。尽管Behi和年侵蚀率之间存在强烈的相关性,但预测曲线与真正的年度侵蚀率没有实际关系,分别与R-2 = 0.004和0.15。

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