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

合作研究：分离河道的气候和天气：表征粗粒度河道对跨尺度扰动响应的动态

• 批准号: 2220505
• 负责人: Colin Phillips
• 金额: $ 29.52万
• 依托单位: Utah State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-07-01 至 2025-06-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2220505&HistoricalAwards=false
• 关键词: Collaborative; Research; Separating; Climate; Weather

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.

山河作为将沉积物和养分从山区到低地的主要代理人，作为美国西部的关键淡水来源区域以及重要的水生栖息地，发挥了独特的作用。然而，山河极易受到全球气候变化和变化降水模式带来的复合危害。 降雨强度的增加会导致更频繁的洪水和陆地滑落，而干旱严重程度增加会增强野火，植被损失和极端侵蚀风险的威胁。该项目旨在开发一种物理模型，以评估山河频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流渠道容易发生重大变化，并指导管理和工程实践缓解和可持续恢复。项目的结果将直接支持服务不足和少数民族高中，并在项目大学的动手学习和研究茎的经验中本科生。这项研究旨在对山脉河道的几何形状如何动态地响应洪水和其他流域扰动的方式发展了解。这项研究是围绕分离河流反应的核心问题进行组织的，这是由于与流域内存在的固有自然变异性的扰动。将变化的信号与变异性分开涉及三个组成部分：一种基于物理的模型，用于自然强迫下的预期河流条件，量化整个河床和到达量表内河道系统内固有的自然变异性，以及一个物理描述，具有量化的调整时间，用于跨这些量表的河流响应。这项研究将通过以下方式完成所有三个组件：（1）利用高分辨率激光雷达地形和沉积物传输数据，以建立可变性的基线水平以及对气候和地质因素的可变性规模的依赖； （2）在液压扰动，河流平面不稳定性和通过高分辨率实验室实验的沉积物传输支撑的阈值过程之间建立物理联系； （3）在有记录的扰动已经破坏了该系统或似乎已经被河流过程缓冲的站点上的一个信号噪声框架。预期的结果将帮助研究人员和工程师确定由于气候和景观的变化而容易受到侵蚀的影响，并为在下一代河流洪水危害预测模型中动态治疗河流提供了基础。这项奖项反映了NSF的法规任务，并被认为是通过基金会的智力综述和宽广的Impactia的评估来进行评估，这是值得通过评估的。