SUPERSLUG: Deconstructing sediment superslugs as a legacy of extreme flows

SUPERSLUG：解构沉积物超级段塞作为极端流动的遗产

• 批准号: NE/Z00022X/1
• 负责人: Matthew Westoby
• 金额: $ 106.84万
• 依托单位: Plymouth University
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2024
• 资助国家: 英国
• 起止时间: 2024 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=NE%2FZ00022X%2F1
• 关键词: SUPERSLUG; Deconstructing; sediment; superslugs; legacy; SUPERSLUG; Deconstructing; sediment; superslugs; legacy

SUPERSLUG will push the frontiers of scientific knowledge and technical innovation to reveal new fundamental insights into the legacies of catastrophic sediment-rich flows (SRF) in mountain landscapes, such as landslides, rock-ice avalanches and glacial lake outburst floods. Catastrophic SRFs are hypothesised to become more frequent this century due to climate warming, and often affect vulnerable communities and assets in least developed countries the most. SRFs can entrain, mobilise, and deposit vast quantities of sediment, which can blanket valley floors to depths of tens of metres. The subsequent re-working and transport of these sediments by rivers can generate large-scale and fast-moving 'superslugs', which is a so-called 'legacy' impact of an SRF. Such legacy impacts are poorly understood, mostly due to observational challenges which have persisted for over a hundred years. However, improving our understanding of these impacts is of vital importance: enhanced fluvial transport of sediment following an SRF can affect flood hazard (by altering river channel bed elevation), infrastructure (e.g. by scouring bridge footings and damaging hydropower turbines), and can disrupt water quality, reducing water and energy security in regions that experience increasingly unstable and hazardous hydrological regimes. With SUPERSLUG we seek to encourage a paradigm shift framed around our argument that the landscape legacies of catastrophic SRFs should be quantified in as much detail as an initial event. To do this we will springboard from recent UKRI-funded pilot work by our international team to develop and apply a new multi-method and widely applicable suite of tools for quantifying the geomorphological evolution of SRF-affected catchments over multi-decade timeframes that are relevant for decision makers, in turn generating new insights into the fundamental behaviour, and impacts, of sediment superslugs. We will focus on a ~150 km-long exemplar system in the Indian Himalaya that has recently experienced a catastrophic SRF; the so-called 'Chamoli disaster'. This catchment arguably represents the most data-rich landscape of its type globally and sits within an otherwise extremely data-poor region. To deconstruct the evolution and impacts of sediment superslugs we will implement five work packages which will: (WP1) benchmark the geomorphological and sedimentological evolution of an SRF-affected system in space and time by using drone-derived observations to upscale from local- to catchment-wide observations using satellite remote sensing; (WP2) directly measure bedload motion in SRF-affected river channels using innovative wireless 'smart' cobbles, complemented with passive seismics; (WP3) develop an open-source toolkit for detecting and tracking fine-grained superslugs by leveraging cloud-based (Google Earth Engine) processing of free satellite imagery; and (WP4) integrate our novel observations from WP1-3 to upscale a powerful numerical landscape evolution-hydrodynamic model to simulate superslug mobility and the wider geomorphological evolution of our exemplar catchment. Our calibrated model, which will be a form of 'digital twin', will represent the largest of its kind and we will use it to explore catchment management decisions (e.g. HEP flushing schedules) for mitigating the worst superslug impacts. Underpinning these four WPs is a fifth WP, wherein we will adopt a Theory of Change-based approach for engaging closely with beneficiaries of this new knowledge and associated tools to translate our findings into practical outcomes and impact, including governance and disaster management professionals, hydropower operators and the wider international academic community.

SuperSlug将推动科学知识和技术创新的边界，以揭示对山地景观中灾难性沉积物富裕流量（SRF）遗产的新基本见解，例如山体滑坡，岩石冰雪崩和冰川湖爆炸洪水。假设灾难性的SRF由于气候变暖而变得更加频繁，并且通常会影响最不发达国家的脆弱社区和资产。 SRF可以夹带，动员和沉积大量的沉积物，这些沉积物可以覆盖山谷地板到数十米的深处。河流对这些沉积物的随后重新加工和运输可能会产生大规模和快速移动的“超级滑动”，这是SRF的所谓“遗产”影响。这种遗产的影响很差，主要是由于观察性挑战已经存在了一百年多。但是，提高对这些影响的理解至关重要：SRF后沉积物的河流运输增强会影响洪水危险（通过改变河道通道床的高度），基础设施（例如，通过搜索桥梁的基础和损坏的水力发电涡轮机），可以破坏水质，水质和能源的能源安全，并造成不稳定性的综合性。在Superslug的情况下，我们试图鼓励围绕我们的论点进行范式转变，即我们的论点是，灾难性SRF的景观遗产应与初始事件一样详细地量化。 To do this we will springboard from recent UKRI-funded pilot work by our international team to develop and apply a new multi-method and widely applicable suite of tools for quantifying the geomorphological evolution of SRF-affected catchments over multi-decade timeframes that are relevant for decision makers, in turn generating new insights into the fundamental behaviour, and impacts, of sediment superslugs.我们将重点关注印度喜马拉雅山的约150公里长的典范系统，该系统最近经历了灾难性的SRF。所谓的“ Chamoli灾难”。可以说，这个流域在全球范围内代表了其类型最丰富的景观，并且位于原本极为贫穷的地区。为了解构沉积物的进化和影响，我们将实施五个工作包：（WP1）通过使用无人机衍生的观测值对受SRF影响的系统的地貌和沉积学演化进行基于从本地到遍布集水的观察到遍布卫星的观测，从而在时间和时间上进行地貌学和沉积学演变； （WP2）使用创新的无线“智能”鹅卵石直接测量受SRF影响的河道中的床载运动，并配有被动地震。 （WP3）开发一个开源工具包，用于通过利用基于云的（Google Earth Engine）处理免费卫星图像来检测和跟踪细粒度的superslugs； （WP4）将我们从WP1-3的新颖观察结果整合到高档的一个强大的数值景观进化 - 流动力模型，以模拟SuperSlug迁移率和我们示例集水区的更广泛的地貌演化。我们的校准模型将是“数字双胞胎”的一种形式，它将代表同类产品中最大的模型，我们将使用它来探索集水管理决策（例如HEP冲洗计划）来减轻最大的超级效果。为这四个WP的支撑是第五WP，其中我们将采用一种基于变革的方法理论，以与这种新知识的受益者紧密接触，以将我们的发现转化为实际成果和影响，包括治理和灾难管理专业人员，水力发电运营商，水力发电运营商和更广泛的国际学术界。