Collaborative Research: Separating the Climate and Weather of River Channels: Characterizing Dynamics of Coarse-Grained River Channel Response to Perturbations Across Scales

山间河流发挥着独特的作用，是将沉积物和营养物质从山区输送到低地的主要媒介，是美国西部重要的淡水来源地，也是重要的水生栖息地。然而，山区河流极易受到全球气候变化和降水模式变化带来的复合灾害的影响。降雨强度的增加可能导致更频繁的洪水和山体滑坡，而干旱严重程度的增加则增加了野火、植被损失和极端侵蚀风险的威胁。该项目旨在开发一个物理模型，以评估山区河道对这些气候变化及其相关危害的敏感性。这项研究将有助于确定河道易受重大变化影响的地方，并指导缓解和可持续恢复的管理和工程实践。项目成果将直接支持服务不足的少数族裔高中和本科生，让他们在项目大学获得动手参与的STEM学习和研究经验。本研究旨在了解山区河道几何形状如何动态响应洪水和其他流域扰动。该研究是围绕分离河流响应的中心问题组织的，这是由于在流域内存在固有的自然变异性的扰动。从变率中分离变化信号涉及三个组成部分：自然强迫下预期河流条件的基于物理的模型，河床和河段尺度上河道系统固有自然变异性的量化，以及河流对这些尺度上扰动响应的量化调整时间的物理描述。本研究将通过以下方式完成所有三个部分：(1)利用高分辨率激光雷达地形和沉积物输运数据建立基线变率水平以及对气候和地质因素的变率尺度的依赖；(2)通过高分辨率的实验室实验，建立了水力扰动、河面不稳定和支撑泥沙输运的阈值过程之间的物理联系；(3)在有记录的扰动破坏了系统稳定或似乎被河流过程缓冲的地点试行信号-噪声框架。预期的结果将有助于研究人员和工程师确定哪些河流系统由于气候和景观的变化而容易受到侵蚀，并为在下一代河流洪水灾害预测模型中动态处理河流提供基础。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Mountain rivers play a distinctive role as the primary agents of distributing sediment and nutrients from mountains to lowlands, as critical freshwater source areas for the Western United States, and as vital aquatic habitats. However, mountain rivers are highly susceptible to the compound hazards presented by global climate change and shifting precipitation patterns. Increasing rainfall intensity can result in more frequent flooding and landsliding while increasing drought severity enhances the threat of wildfire, vegetation loss, and extreme erosion risks. This project aims to develop a physical model to assess the sensitivity of mountain river channels to these shifts in climate and their associated hazards. This research will help to identify where river channels are susceptible to significant change and guide management and engineering practices for mitigation and sustainable restoration. Project results will directly support underserved and minority high school and undergraduates with hands-on engaging learning and research STEM experiences at project Universities.This research aims to develop an understanding of how mountain river channel geometry dynamically responds to flooding and other watershed perturbations. The research is organized around the central question of separating river response due to a perturbation from the inherent natural variability present within watersheds. Separating signals of change from variability involves three components: a physics-based model for the expected river conditions under natural forcing, quantification of the inherent natural variability within the river channel system across the riverbed and reach scale, and a physical description with quantified adjustment times for river response to perturbations across these scales. This research will accomplish all three components by: (1) leveraging high resolution lidar topography and sediment transport data to establish a baseline level of variability and the dependence on the scale of variability on climatic and geologic factors; (2) developing a physical link between hydraulic perturbations, river planform instability, and the threshold processes underpinning sediment transport through high resolution laboratory experiments; and (3) pilot a signal-to-noise framework at sites where documented perturbations have both destabilized the system or appear to have been buffered by river processes. Expected results will aid researchers and engineers in determining which river systems are vulnerable to erosion due changing climate and landscapes, and provide a foundation for treating rivers dynamically within the next-generation of river flood hazard forecasting models.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.