Collaborative Research: The Effects of Hydrodynamic and Granular Controls on Bed Load Flux Intermittency: Application to Steep Mountain Streams

了解水流如何驱动河流中的泥沙输运，对于预测侵蚀和景观演变、管理河流基础设施以及保护和促进鱼类栖息地至关重要。推移质输运--沉积物与河底频繁接触的运动--尽管进行了近世纪的定量研究，但仍然是出了名的不可预测。这个问题是特别严重的陡峭的山溪运输发生接近运动的阈值，并由此产生的大幅度推移质负荷脉冲不能使用现有的数学模型进行预测。我们将在这里研究山溪的两个独特方面：（1）产生大规模流体湍流结构的大型，很少移动的巨石的存在;（2）高能量的颗粒-颗粒碰撞，导致许多粒子的协调运动。我们将进行两组平行的实验室实验，以研究这两个因素对颗粒床结构的形成和破碎的影响。将使用粒子图像测速技术绘制流量图，而声学传感器将量化推移质输运，压力传感器将测量流体应力，激光诱导荧光将用于对颗粒床进行成像。这些测量将使我们能够确定流体和颗粒应力的推移质输运的相对贡献，并制定一个完善的推移质输运方程，更适合于预测在山区溪流。我们将测试最近在软物质物理学中发展起来的一个框架，它统一了对广泛的一类无序系统中的输运的描述，是否有助于理解河流中泥沙输运的统计力学。洪水侵蚀河岸，冲垮桥梁，用泥沙填满水库。在陡峭的山溪中，巨大的巨石形成天然大坝，在暴雨期间会突然坍塌，向下游发送灾难性的沉积物脉冲，危及财产和生命。这些事件很少发生，因此很难获得理解物理过程和建立预测模型所需的测量结果。在这项研究中，我们将使用一组缩放的实验室实验，这使我们能够通过缩小尺寸来有效地加快时间，以了解驱动山间溪流中巨石运动的物理过程。我们将在严格控制的条件下，测量流动的水施加在巨石上的力，以及巨石之间相互碰撞时的力。然后，我们将建立一个数学模型，利用这种物理理解来预测巨石在不同量级的洪水中何时移动以及移动多少。这个模型将帮助地球科学家研究侵蚀景观的长期演变。研究结果也将有助于工程师和管理人员负责保护和维护基础设施，恢复自然河流的功能，在山区设置。此外，这笔赠款将为未来的科学家提供重要的培训，因为实验将由一名博士生和博士后研究人员领导，并涉及几名本科生。

Understanding how fluid flow drives sediment transport in a river is fundamental for predicting erosion and landscape evolution, managing river infrastructure, and protecting and promoting fish habitat. Bed load transport - the movement of sediment in frequent contact with the river bottom - remains notoriously unpredictable, despite almost a century of quantitative research. The problem is particularly acute in steep mountain streams where transport occurs close to the threshold of motion, and the resulting large-magnitude bed load pulses cannot be predicted using existing mathematical models. There are two unique aspects of mountain streams that we will examine here: (1) the presence of large, rarely-mobile boulders that generate large-scale fluid turbulence structures; and (2) highly energetic grain-grain collisions that cause coordinated motion of many particles. We will perform two parallel sets of laboratory experiments to examine the influence of these two factors on the formation and breakup of granular bed structures. Flow will be mapped using particle image velocimetry, while acoustic sensors will quantify bed load transport, pressure sensors will measure fluid stresses, and laser-induced fluorescence will be used to image the granular bed. These measurements will allow us to determine the relative contributions of fluid and granular stresses to bed load transport, and to develop a refined bed load transport equation that is better suited for prediction in mountain streams. We will test whether a recent framework developed in soft-matter physics, which unites the description of transport in a wide class of disordered systems, can be useful for understanding the statistical mechanics of sediment transport in rivers.Floods erode streambanks, take out bridges and fill reservoirs with sediment. In steep mountain streams, large boulders form natural dams that can suddenly give way during a rain storm, sending catastrophic pulses of sediment downstream that endanger property and lives. These events occur infrequently, making it difficult to obtain the measurements required to understand the physical processes and to build predictive models. In this study we will use a set of scaled laboratory experiments, which allow us to effectively speed up time by scaling down size, to understand the physical processes driving the movement of boulders in mountain streams. We will measure the forces exerted on boulders by the moving water, and among boulders as they collide with each other, under carefully controlled conditions. We will then build a mathematical model that uses this physical understanding to predict when, and how much, boulders will move in floods of different magnitudes. This model will help Earth scientists studying the long-timescale evolution of eroding landscapes. Results will also be useful for engineers and managers charged with protecting and maintaining infrastructure, and restoring natural river function, in mountain settings. In addition, this grant will provide important training for future scientists, as the experiments will be led by a doctoral student and post-doctoral researcher, and also involve several undergraduate students.