SUPERSLUG: Deconstructing sediment superslugs as a legacy of extreme flows

Superlug将推动科学知识和技术创新的前沿，以揭示对山区景观中灾难性的富沙水流(SRF)遗留下来的新的基本见解，例如山体滑坡、岩冰雪崩和冰川湖暴发洪水。据推测，由于气候变暖，灾难性的SRF在本世纪将变得更加频繁，往往对最不发达国家的脆弱社区和资产影响最大。SRF可以携带、动员和沉积大量的沉积物，这些沉积物可以覆盖山谷底部数十米深。随后河流对这些沉积物的重新加工和运输可能会产生大规模和快速移动的“超段塞”，这就是所谓的SRF的“遗留”影响。人们对这种遗留影响知之甚少，主要是由于持续了一百多年的观测挑战。然而，提高我们对这些影响的认识是至关重要的：在SRF之后，增加河流泥沙的输送可能会影响洪水风险(通过改变河床高程)、基础设施(例如冲刷桥基和损坏水轮机)，并可能扰乱水质，降低经历日益不稳定和危险的水文制度的地区的水和能源安全。我们寻求通过超对流来鼓励一种范式转变，这种转变围绕着我们的论点，即灾难性SRF留下的景观遗产应该像最初的事件一样详细地量化。为此，我们将从我们的国际团队最近由UKRI资助的试点工作入手，开发和应用一套新的多方法和广泛适用的工具，用于量化与决策者相关的数十年时间框架内受SRF影响的流域的地貌演变，进而对沉积物超段塞的基本行为和影响产生新的见解。我们将关注印度喜马拉雅地区一个长约150公里的样本系统，该系统最近经历了一场灾难性的SRF，即所谓的“查莫里灾难”。可以说，这个集水区代表了全球同类数据最丰富的地区，而且位于一个数据极其贫乏的地区。为了解构沉积物超段塞的演变和影响，我们将实施五个工作包，这五个工作包将：(WP1)通过使用无人机衍生的观测，将受SRF影响的系统在空间和时间上的地貌和沉积学演变作为基准，利用卫星遥感将从局部观测提升到流域范围的观测；(WP2)使用创新的无线‘智能’鹅卵石，辅以被动地震，直接测量受SRF影响的河道中的推移质运动；(WP3)开发一个开源工具包，用于通过利用基于云的(谷歌地球引擎)对自由卫星图像的处理来探测和跟踪细粒度的超段塞；和(WP4)整合了我们从WP1-3获得的新观测结果，以扩大一个强大的数字景观演化-水动力学模型，以模拟超蜗牛的流动性和我们的样本流域更广泛的地貌演变。我们的校准模型将是一种“数字孪生”的形式，它将代表同类中最大的模型，我们将使用它来探索流域管理决策(例如，HEP冲洗计划)，以减轻最严重的超段塞影响。支持这四个工作计划的是第五个工作计划，在该计划中，我们将采用以变革理论为基础的方法，与这一新知识和相关工具的受益者密切接触，将我们的调查结果转化为实际成果和影响，包括治理和灾害管理专业人员、水电运营商和更广泛的国际学术界。

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.