4.7 Article

Evaluation of bedload transport predictions using flow resistance equations to account for macro-roughness in steep mountain streams

期刊

WATER RESOURCES RESEARCH
卷 47, 期 -, 页码 -

出版社

AMER GEOPHYSICAL UNION
DOI: 10.1029/2011WR010645

关键词

-

资金

  1. Swiss Federal Office for the Environment [06.0083.PJ/G063-0651]
  2. SNF [200021_124634/1]
  3. Ingo Volksch

向作者/读者索取更多资源

Steep mountain streams typically feature macro-roughness elements like boulders, step-pool sequences, and a varying channel width. Flow resistance because of such roughness elements appears to be an important control on bedload transport rates. Many commonly used bedload transport equations overestimate the transport in steep streams by orders of magnitude. Few approaches take into account the typical macro-roughness elements, and systematic tests of these models with field observations are lacking. In the present study several approaches were considered that allow calculating the contribution of macro-roughness elements to flow resistance. These approaches were combined with bedload transport equations and the predictions were compared to field measurements of discharge, transported bedload volumes, and channel characteristics in 13 Swiss mountain streams. The streams have channel slopes ranging from 2% to 19%, and catchment areas of 0.5 to 170 km(2). For six streams there were time series of sediment yields, mostly measured annually, and for the other seven streams sediment volume estimates were available for large flood events in 2000 and 2005. All tested equation combinations achieved an improvement in bedload prediction compared to a reference equation that was uncorrected for macro-roughness. The prediction accuracy mainly depended on the size and density of the macro-roughness and on flow conditions. The best performance overall was achieved by an empirical approach accounting for macro-roughness, on the basis of an independent data set of flow resistance measurements.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.7
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据