Waves, levees and impact pressures in snow avalanches

雪崩是山区的一种主要自然灾害，对世界上许多国家的人民和基础设施造成重大威胁。雪崩通常有一层稀释的粉末云，掩盖了下面的密集气流。这种密集的气流经常造成很大的损害。因此，积雪科学家花了多年时间开发GEODAR、多普勒和FMCW雷达，以及仪器化的塔架，以可视化内部密集流动力学（Köhler et al. 2016; 2018）。这些技术表明，密集的雪崩会产生浪涌和内波（图2）。3) （Sovilla et al. 2010）。此外，实地观测（图4）表明，相当大比例的雪崩形成了堤坝。这些波浪和堤坝很重要，因为(i)它们强烈增强了流动的流动性和流动（Edwards等人，2021年，Rocha等人，2019年），（ii）它们极大地集中了雪崩内部的能量，极大地放大了它们对路径上的建筑物和障碍物施加的冲击力（见图4）。尽管它们很重要，但在雪崩中引起波浪和堤坝的潜在机制尚不清楚，因此目前的模型无法很好地预测它们。该提案将密集雪崩可视化方面的突破与浅流中波浪和堤防形成的新一般理论相结合，该理论最初是在曼彻斯特为小规模干颗粒流开发的（Gray & Edwards 2014, Edwards & Gray 2015， Viroulet等人2018，Rocha等人2019，Edwards等人2021）。这一理论框架将使我们能够利用雷达观测的波幅、波长和粗化动力学，为雪崩的流变特性提供重要的约束条件，这些特性强烈依赖于温度。Köhler等人（2018）确定了七种主要的雪崩类型，本提案侧重于三种主要的密集流类型：(i)冷切变，（ii）暖切变和（iii）暖塞。冷流是无黏性的粒状流，而暖流中有一些液态水，这使得大雪球可以通过黏结力聚集（Steinkogler et al. 2015）。雪球极大地增加了平均颗粒大小，然后暖切变流有在流出区形成巨大堤坝的趋势（图4a）。这表明，这些流动可能与曼彻斯特的小规模自渠化流动非常相似（图4b），我们为此开发了一个定量模型（Rocha et al. 2019）。因此，该提案旨在为雪崩模型开发一种新的摩擦定律，该定律将捕捉波的自发形成和增长，以及在运行区域的自通道化。我们还将研究自通道化和波浪形成如何能够集中对结构的冲击力并增强跑出。

Snow avalanches are a major natural hazard in mountainous regions and pose a significant risk affecting people and infrastructure in many countries throughout the world. Avalanches typically have a dilute powder cloud that obscures the underlying dense flow beneath. This dense flow often causes much of the damage. Snow scientists have therefore spent many years developing GEODAR, Doppler and FMCW radar, as well as instrumented pylons, to visualize the internal dense flow dynamics (Köhler et al. 2016; 2018). These technologies shows that dense avalanches develop surges and internal waves (figs. 3) (Sovilla et al. 2010). In addition, field observations (fig. 4) show that a significant proportion of avalanches develop levees. These waves and levees are important because (i) they strongly enhance the mobility and run-out of the flow (Edwards et al. 2021, Rocha et al. 2019) and (ii) they vastly concentrate the energy within avalanches, dramatically magnifying the impact forces they exert on buildings and obstacles in their path (see figure 4). Despite their importance, the underlying mechanisms that cause waves and levees in snow avalanches are poorly understood, and consequently they are not well predicted by current models.This proposal combines the breakthroughs in visualisation of dense snow avalanches with a new general theory for wave and levee formation in shallow flows, originally developed in Manchester for small-scale dry granular flows (Gray & Edwards 2014, Edwards & Gray 2015, Viroulet et al. 2018, Rocha et al. 2019, Edwards et al. 2021). This theoretical framework will allow us to use the radar observations of wave amplitude, wavelength and coarsening dynamics, to provide important constraints on the rheological properties of snow avalanches, which are strongly temperature dependent. Köhler et al. (2018) identified seven main types of snow avalanche and this proposal focuses on the three main dense-flow types: (i) cold shear, (ii) warm shear and (iii) warm plug. Cold flows are cohesionless granular flows, while warm flows have some liquid water in them, which allows large snowballs to agglomerate by cohesive forces (Steinkogler et al. 2015). The snowballs dramatically increase the mean particle size, and warm-shear flows then have a tendency to form huge levees in the run-out zone (fig. 4a). This suggests that these flows may be closely analogous to the small-scale self-channelizing flows in Manchester (fig. 4b), for which we have developed a quantitative model (Rocha et al. 2019). This proposal therefore aims to develop a new friction law for snow-avalanche models, that will capture the spontaneous formation and growth of waves, as well as self-channelization in the run-out zone. We will also examine how self-channelization and wave formation are able to concentrate the impact forces on structures and enhance run out.