Smart Rivers: Instrumenting watercourses to measure transport processes and assess risk

智能河流：对水道进行测量以测量运输过程并评估风险

• 批准号: RGPIN-2016-04426
• 负责人: MacVicar, Bruce
• 金额: $ 2.26万
• 依托单位: University of Waterloo
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2016
• 资助国家: 加拿大
• 起止时间: 2016-01-01 至 2017-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=615055
• 关键词: Smart; Rivers; Instrumenting; watercourses; measure

River hydraulics is an active area of research for a number of reasons including: pressures from urbanization and climate change on surface water networks; limitations in experimental and numerical approaches to longstanding problems like sediment transport; and technical advances that open up new possibilities. The proposed research aims to exploit new techniques to gain better information about how and when the building blocks of river structure, i.e. the stored wood and sediment, move in rivers. The rationale is that this information could be exploited to better assess risk. For instance, when wood and sediment move during floods, scour is occurring, bed elevations are changing, and the risk of wood jams or instability at built infrastructure such as bridges and sewers is elevated. Measuring movement and communicating that information in a timely manner could be used to facilitate rapid response. At time scales of years or decades, trends in sediment and wood movement underpin structural imbalances in river networks that can result from external forces such as urbanization and climate change. Network modelling tools are needed to put the right information into the hands of land-use planners and practicing engineers. Over the next five years, my research group will advance the use of cutting-edge techniques, such as Radio Frequency Identification (RFID), for sediment tracking and video analysis for sediment and wood transport measurement. We will develop ‘easy’ software that is accessible from common Geographic Information System interfaces and that allows integration with different types of information so that urban designers and planners can incorporate risks and costs associated with surface stream networks. Particular examples will include high-risk creeks in Southern Ontario and the Don River in Toronto, where the estuary is expected to be re-naturalized over the next decade. We will address knowledge gaps in the fundamentals of sediment transport research using advanced computational fluid dynamics capabilities and a purpose built CFI funded facility to model sediment transport in rivers. The proposed work is significant because smart rivers and the associated technologies will reduce risk associated with flooding and channel instability. The research will allow for a smoother climate change adaptation and assist with city planning for future growth and ongoing restoration needs. The results will also improve stream restoration designs and our understanding of sediment and wood transport processes in rivers.

河流水力学是一个活跃的研究领域，原因包括：城市化和气候变化对地表水网络的压力;实验和数值方法对沉积物输运等长期问题的限制;以及开辟新可能性的技术进步。拟议的研究旨在利用新技术来获得有关河流结构的组成部分（即储存的木材和沉积物）如何以及何时在河流中移动的更好信息。理由是，可以利用这一信息更好地评估风险。例如，当木材和沉积物在洪水期间移动时，冲刷正在发生，河床高程正在变化，木材堵塞或桥梁和下水道等建筑基础设施不稳定的风险增加。可以利用及时测量移动情况和通报这一信息来促进快速反应。在几年或几十年的时间尺度上，沉积物和木材流动的趋势是城市化和气候变化等外部力量造成的河流网络结构不平衡的基础。需要网络建模工具，以便将正确的信息提供给土地使用规划者和执业工程师。 在接下来的五年里，我的研究小组将推进尖端技术的使用，如射频识别（RFID），用于沉积物跟踪和沉积物和木材运输测量的视频分析。我们将开发“简单”的软件，可以从通用的地理信息系统接口访问，并允许与不同类型的信息集成，使城市设计师和规划师可以考虑与地面流网络相关的风险和成本。具体的例子将包括安大略南部的高风险小溪和多伦多的顿河，那里的河口预计将在未来十年内重新归化。我们将利用先进的计算流体动力学能力和专门建造的CFI资助的设施来模拟河流中的泥沙输运，以解决泥沙输运研究的基础知识差距。 拟议的工作意义重大，因为智能河流和相关技术将减少与洪水和河道不稳定相关的风险。该研究将使适应气候变化更加顺利，并有助于城市规划未来的增长和持续的恢复需求。研究结果还将改善河流恢复设计和我们对河流中沉积物和木材运输过程的理解。