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Step-pool formation models and associated step spacing

机译:阶梯池形成模型和相关的阶梯间距

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Step-pool bedforms develop under conditions of high flow rates and high sediment influx and transport rates. Step setting events are capable of mobilizing and rearranging the large step-forming grain sizes. Thus, observations of the processes of step formation are limited to flume experiments. The results of laboratory experiments involving active transport of widely sorted sediment, including large grains whose deposition readily formed steps, are presented. Over 350 step formations were observed and documented, creating a large data set for detailing and evaluating step formation processes. Existing step-formation models focus on step development from antidunes, particle clusters, transverse ribs or depositional berms, or from a hydraulic regime that includes cascade How and hydraulic jumps. These models were developed using field measurements of artificial grade control structures or stable step-pool systems during low flow conditions, or degradational flume experiments where flows elucidated the step-pool bedform in the channel profile but did not create equilibrium transport of the large, step-forming clasts. This research evaluates the pre-existing formation models and proposes three new models: the rough bed, exhumation and dune models. The rough bed model was dominant throughout the experiments, followed by the exhumation model and then the dune model. A single model was not responsible for all step formations. The rough bed, exhumation and dune models all influenced step development, and every step sequence was created through a mixture of formation processes. This research generated a large data set, where each step spacing is paired with the corresponding step formation model, making it possible to identify a distinct exclusion zone length for each model. Thus, given knowledge of the step formation model, the minimum distance to the next step downstream can be predicted. From the final spacing of a step sequence, it may be possible to deduce the likely formation mechanisms active during a step resetting event. Copyright (C) 2007 John Wiley & Sons, Ltd.
机译:在高流速,高泥沙流入和高输送速率的条件下,会形成阶跃式池床。台阶设置事件能够调动和重新排列较大的台阶形成晶粒尺寸。因此,台阶形成过程的观察仅限于水槽实验。实验室实验的结果涉及主动输送广泛分类的沉积物,包括大颗粒,其沉积过程容易形成。观察并记录了350多个台阶形成情况,创建了一个大型数据集,用于详细介绍和评估台阶形成过程。现有的台阶形成模型集中于从反沙丘,颗粒团簇,横向肋骨或沉积堤道,或从包括级联流和水力跃迁的水力状态进行的步伐发展。这些模型是通过在低流量条件下使用人工坡度控制结构或稳定的阶梯池系统的现场测量,或降解水槽实验(流量在通道剖面中阐明阶梯池床形但未产生大步长的平衡输运)而开发的形成的碎屑。这项研究评估了已有的编队模型,并提出了三个新模型:粗糙床,掘尸和沙丘模型。在整个实验中,粗糙床模型占主导地位,其次是掘尸模型和沙丘模型。单个模型不负责所有步骤的形成。粗糙的床层,掘尸场和沙丘模型都影响了步骤的开发,并且每个步骤的序列都是通过混合形成过程来创建的。这项研究产生了一个大数据集,其中每个步距与相应的步形成模型配对,从而有可能为每个模型识别不同的排除区长度。因此,在了解了台阶形成模型的情况下,可以预测到下游下一步的最小距离。从一个步骤序列的最终间隔,可以推断出在步骤重置事件期间可能起作用的可能的形成机制。版权所有(C)2007 John Wiley&Sons,Ltd.

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