Rock and Roll: Passive and automated sensing of fluvial sediment and wood transport

河流河床作用是粗质泥沙在河流作用下通过地貌转移的一个基本过程。大木材是许多河流的主要组成部分，但人们对其对河床输运的影响知之甚少。在过去的十年里，由于山松甲虫对森林的侵扰，美国西部的河流目前正在经历木材负荷的增加。该项目将调查受感染森林内河流中木材负荷增加对河床泥沙运输动力学的影响。该项目将采用被动无线电示踪技术，其中单个颗粒/木片被被动综合应答器（PIT）标记，以跟踪床载和木材运输。使用这项技术的研究表明，床上颗粒的运动就像随机游走模型，间歇性运动之后是长时间的休息（Bradley和Tucker， 2012）。该项目将首次获得关于木材对床粒休息间隔和移动距离的影响的数据。其次，该项目将应用和开发无人驾驶飞行器（uav），以量化木材负荷对溪流和河道地貌的变化。特别是，它将开发技术，以帮助无人机在森林环境中使用狭窄的飞行走廊。该学生将参加在美国科罗拉多州弗雷泽实验森林（FEF）的一条高山溪流圣路易斯溪进行的大规模深坑示踪剂河床泥沙运输实验。2016年8月，G. Bennett和S. Ryan在溪流中播种了1000块标有PIT标记的岩石。一年后的初步调查发现了90%的岩石，其中30%的岩石显示出从最初的种子位置沿河床移动了100米。该学生将更新和分析一个不断增长的沉积物运输和木材吸收数据库-来自FEF的种子地点和其他子流域（例如，Ryan等人，2015）。该学生将比较所获得的泥沙输移数据与水流数据，以便建立泥沙输移的水文控制。此外，他们将使用无人驾驶飞行器（UAV）来评估木材装载到溪流的变化，通道地貌和颗粒运动的结构控制。该学生将与东英吉利大学计算机科学专业的Gerard Parr及其同事合作，开发无人机防碰撞技术，用于飞越森林集水区（例如Luo等人，2013年）。布拉德利，d.e.，塔克，g.e., 2012。用无源放射性示踪剂测量山间河流中的砾石输送和分散。地球表面过程和地形，DOI: 10.1002/esp。3223Ryan, s.e., Bishop, e.l.和Daniels， J.M. 2014。大木材对山源溪流河道形态和泥沙储存量的影响，弗雷泽实验森林，科罗拉多州。地貌学217:73 - 88。C. Luo， S. I. McClean， G. Parr， L. Teacy和R. De Nardi，“基于扩展卡尔曼滤波的无人机位置估计和避碰”，《IEEE车辆技术学报》，vol. 62, no. 10。6, pp. 2749-2762, 2013年7月。doi: 10.1109 / TVT.2013.2243480

Fluvial bedload is a fundamental process by which coarse sediment is transferred through landscapes by fluvial action. Large wood is a major component of many rivers, but its influence on bedload transport is poorly understood. Rivers across the western USA are currently experiencing increased wood loading due to infestation of forests by the mountain pine beetle over the past decade. This project will investigate the impact of increased wood loading on bedload sediment transport dynamics in a stream within an infected forest. The project will apply passive radio tracer technology in which individual grains/wood pieces are tagged with Passive Integrative Transponders (PIT) to track bedload and wood transport. Studies using this technology have shown that bed- particles move like a random walk model with intermittent periods of movement followed by long periods of rest (Bradley and Tucker, 2012). The project will acquire data on the impact of wood on bed-particle rest intervals and travel distances for the first time. Secondly, the project will apply and develop unmanned aerial vehicles (UAVs) to quantify changes in wood loading to the stream and channel geomorphology. It particular, it will develop technology to aid the use of UAVs in forested environments with tight flying corridors.The student will be part of a large scale PIT tracer experiment of bedload sediment transport in St Louis Creek, an alpine stream in Fraser Experimental Forest (FEF), Colorado, USA. In August 2016, G. Bennett and S. Ryan seeded 1000 PIT tagged rocks in the stream. An initial survey one year later found 90% of the rocks, with 30% of these showing movement from their initial seed location to up to 100 m along the river bed. The student will update and analyze a growing database of sediment transport and wood recruitment - from the seeded site and other subwatersheds at FEF (e.g., Ryan et al. 2015). The student will compare data acquired on sediment transport with flow data in order to establish hydrologic controls on sediment transport. Furthermore, they will use an Unmanned Aerial Vehicle (UAV) to assess changes in wood loading to the stream, channel geomorphology and structural controls on particle movement. The student will work with Gerard Parr and colleagues in Computer Sciences at UEA to develop UAV anti-collision technology for flying through forested catchments (e.g. Luo et al., 2013).Bradley, D.E., and Tucker, G.E., 2012. Measuring gravel transport and dispersion in a mountain river using passive radio tracers. Earth Surface Processes and Landforms, DOI: 10.1002/esp.3223Ryan, S.E., Bishop, E.L., and Daniels, J.M. 2014. Influence of large wood on channel morphology and sediment storage in headwater mountain streams, Fraser Experimental Forest, Colorado. Geomorphology 217:73-88. doi:10.1016/j.geomorph.2014.03.046 C. Luo, S. I. McClean, G. Parr, L. Teacy and R. De Nardi, "UAV Position Estimation and Collision Avoidance Using the Extended Kalman Filter," in IEEE Transactions on Vehicular Technology, vol. 62, no. 6, pp. 2749-2762, July 2013.doi: 10.1109/TVT.2013.2243480