Collaborative Research: Experimental Study of Downstream Fining in Coarse-grained River Channels

合作研究：粗粒河道下游细化试验研究

• 批准号: 9004756
• 负责人: Christopher Paola
• 金额: $ 11.86万
• 依托单位: University of Minnesota-Twin Cities
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 1990
• 资助国家: 美国
• 起止时间: 1990-08-01 至 1993-01-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9004756&HistoricalAwards=false
• 关键词: Collaborative; Research; Experimental; Study; Downstream

Recently it has become clear from a variety of field observations that downstream size decrease in aggrading river systems is caused in large part by selective deposition of coarse clasts. However, sorting by selective deposition has never been studied systematically under controlled conditions. The absence of a set of reference data on downstream sorting is even more striking in light of the number of theories that have been advanced recently to explain it. The main goal of the proposed project is to carry out a series of basic experiments on selective transport and deposition in poorly sorted gravelly sediments. Most of the experiments will be conducted in a large channel at the St. Anthony Falls Hydraulic Laboratory. There we will produce deposits from a poorly sorted sand-gravel mix over a distance of about 50 m. The main variables will be rate of sediment feed (and hence deposition), and channel form (straight, weakly sinuous, braided). In addition we will make detailed measurements of sediment transport and surface texture in a smaller flume at Johns Hopkins University. These data will be used to develop surface-based transport formulas that will be used in modeling the sorting observed in the large flume.

最近，从各种现场观察中可以清楚地看出，河流系统的下游尺寸减小很大程度上是由于粗碎屑的选择性沉积造成的。 然而，从未在受控条件下系统地研究过通过选择性沉积进行的分选。 考虑到最近提出的解释下游排序的理论数量，缺乏一组有关下游排序的参考数据更加引人注目。 该项目的主要目标是在分选不良的砾石沉积物中进行一系列选择性迁移和沉积的基础实验。 大部分实验将在圣安东尼瀑布水利实验室的一个大通道中进行。 在那里，我们将从约 50 m 距离内分类不良的砂砾石混合物中产生沉积物。 主要变量是沉积物供给速率（以及沉积）和河道形式（直的、弱蜿蜒的、辫状的）。 此外，我们还将在约翰·霍普金斯大学的一个较小水槽中对沉积物迁移和表面纹理进行详细测量。 这些数据将用于开发基于表面的传输公式，该公式将用于对大型水槽中观察到的分选进行建模。