Debris-flow dynamics: Understanding phase separation and wave formation

泥石流动力学：了解相分离和波浪形成

基本信息

批准号：
NE/X00029X/1
负责人：
Nico Gray
金额：
$ 72.76万
依托单位：
University of Manchester
依托单位国家：
英国
项目类别：
Research Grant
财政年份：
2023
资助国家：
英国
起止时间：
2023 至无数据
项目状态：
未结题

来源：
https://gtr.ukri.org/projects?ref=NE%2FX00029X%2F1
关键词：
Debris flow dynamics Understanding phase

项目摘要

Debris flows are natural hazards that threaten people and infrastructure in mountainous terrain. They are becoming more frequent due to the increasing number of high rainfall intensity events (Petely et al., 2012, Global patterns of loss of life from landslides. Geology 40, 927-930). The destructive potential of debris flows is strongly enhanced by the development of surge waves (Fig 3 + video), which concentrate the flow into large amplitude waves that often carry large rocks and boulders. Despite nearly forty years of research there is still a lack of understanding about why these waves form, as well as a dearth of good field data sets (in-situ measurements of active flow thickness and velocity) that can be used to test models. This severely limits the accuracy of debris-flow risk analysis, because current debris-flow models are not able to capture quantitatively these waves or the particle-size segregation that concentrates the largest particles in the deepest and fastest-flowing part of the flow. This proposal aims to make a major breakthrough in our ability to predict debris-flow surge wave formation by coupling (a) new innovations (hybrid LiDAR/HD video) in environmental sensing at the Illgraben debris-flow observation station in Switzerland with (b) recent theoretical advances in modelling nonlinear wave formation and particle-size segregation made in Manchester (Gray & Edwards 2014, Gray 2018, Rocha et al. 2019). The assembled research team is uniquely suited to address this question, as it combines a diverse range of experts who have a strong theoretical background as well as expertise in laboratory and field data collection. This will enable the team to integrate state-of-the-art in-situ data currently being collected at Illgraben (and improved on as part of this proposal) into cutting-edge theoretical and numerical models in order to generate a step change in our understanding of surge waves as well as new computational tools for use by the debris-flow community in hazard risk assessment.

泥石流是威胁山区人民和基础设施的自然灾害。由于高降雨强度事件的数量不断增加，滑坡事件变得越来越频繁（Petely 等人，2012 年，山体滑坡造成生命损失的全球模式。地质学 40, 927-930）。浪涌波的发展极大地增强了泥石流的破坏潜力（图 3 + 视频），浪涌波将泥石流集中成通常携带大岩石和巨石的大幅波。尽管进行了近四十年的研究，但人们仍然对这些波形成的原因缺乏了解，也缺乏可用于测试模型的良好现场数据集（活动流厚度和速度的现场测量）。这严重限制了泥石流风险分析的准确性，因为当前的泥石流模型无法定量捕获这些波或将最大颗粒集中在泥石流最深和流速最快部分的颗粒尺寸分离。该提案旨在通过将（a）瑞士伊尔格拉本泥石流观测站环境传感方面的新创新（混合激光雷达/高清视频）与（b）相结合，在预测泥石流涌浪形成的能力方面取得重大突破曼彻斯特在非线性波形成和粒度偏析建模方面的最新理论进展（Gray & Edwards 2014、Gray 2018、Rocha 等人 2019）。组建的研究团队非常适合解决这个问题，因为它结合了各种专家，他们拥有强大的理论背景以及实验室和现场数据收集方面的专业知识。这将使团队能够将目前在 Illgraben 收集的最先进的现场数据（并作为本提案的一部分进行改进）整合到尖端的理论和数值模型中，以便在我们的了解涌浪以及泥石流社区在灾害风险评估中使用的新计算工具。