Dynamic Risks for Cascading Himalayan Hazards

喜马拉雅山级联灾害的动态风险

• 批准号: NE/Z503526/1
• 负责人: Mark Naylor
• 金额: $ 108.36万
• 依托单位: University of Edinburgh
• 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%2FZ503526%2F1
• 关键词: Dynamic; Risks; Cascading; Himalayan; Hazards

There are a wide range of natural hazards that impact communities living within, and at the edge of the Himalayan mountains; these are dominated by earthquakes, landslides and floods. In order to reduce the risk from landslides and floods, communities have developed early warning systems to downstream villages and towns, enabling pre-planned responses. Early warning systems require local authorities to be aware of potential dangers. For example, a steep hillslope that is known to be unstable with evidence of past landslides should be monitored, particularly during periods of heavy rainfall. However, in order for the local District Disaster Management Authorities (DDMAs) to know where to monitor, medium-term forecasts of the likely risk from different hazards need to be known. For example, certain areas are more prone to earthquakes, and others to landslides and flashfloods. If these risks from different hazards remain constant through time, then the forecasts and monitoring for each community remains steady. However, hazards do not act in isolation, but form cascades, each event triggering another. As a result, the risk from multiple hazards is not stable, but dynamic, and changes in response to upstream triggers. For example a landslide, that leads to a dam that breaks out to form a debris flow that then increases subsequent risk to floods due to choking of river channels with sand and gravel.This project aims to provide the first fully quantitative forecasts of multihazard cascades using a range of new modelling techniques constrained by a history of field observations from the Garwhal Himalaya, Uttarakhand. This area has been devastated by recent landslides and flashfloods such as the Kedarnath disaster in 2013 and the Chomli landslide in 2021. Thick accumulations of sediment in these steep mountain valleys are known as 'sediment bombs' as they pose a danger to downstream communities; such sediment bombs may form where glaciers retreat or where landslides block valleys. In this project, the Indian and UK teams will combine to integrate new methodologies from digital topography, remote sensing, computer models and field monitoring to understand how sediment yield from glaciers and landslides initiate sediment bombs, and how these accumulations are then mobilised to form debris flows, flash floods and downstream flooding. Through understanding the distribution and rates involved in these processes, we will generate medium term forecasts that feed into early warning systems developed in the communities of the Alaknanda Valley.The approach as outlined above suggests that the physical science models will be the sole input into consideration of dynamic risk; but it can't be as simple as that. The communities that live with this risk, and the DDMAs that manage the early warning systems have to be involved in the generation and iteration of the scientific methodology. Consequently, we are working with social scientists in the UK and India who have experience working with communities in the Himalaya through workshops and interviews that respect the diverse cultural, ethnic and gender-based perspectives. By the end of the project, we will have generated a decisional workflow for district authorities that integrates dynamic risk into their medium term forecasts in response to cascading hazards. Having demonstrated this process in the Garwhal Himalaya, we intend to work with the National Disaster Management Authorities in India and Nepal to promote national strategies for dynamic risk assessment.

有各种各样的自然灾害影响着生活在喜马拉雅山脉内部和边缘的社区;这些灾害主要是地震、山体滑坡和洪水。为了减少山体滑坡和洪水的风险，社区为下游村庄和城镇建立了预警系统，以便能够预先规划应对措施。预警系统要求地方当局了解潜在的危险。例如，应监测一个已知不稳定的陡峭山坡，并有证据表明过去曾发生过山体滑坡，特别是在大雨期间。然而，为了使当地的地区灾害管理局（DDMA）知道在哪里进行监测，需要知道不同灾害可能造成的风险的中期预测。例如，某些地区更容易发生地震，其他地区更容易发生山体滑坡和山洪暴发。如果这些来自不同灾害的风险随着时间的推移保持不变，那么对每个社区的预测和监测就保持稳定。然而，危害并不是孤立地发生作用，而是形成级联，每一个事件都会引发另一个事件。因此，多种危害的风险不是稳定的，而是动态的，并随着上游触发因素的变化而变化。例如，一次滑坡，导致一座大坝爆发，形成泥石流，然后由于河道被砂石堵塞，增加了随后发生洪水的风险，该项目旨在利用一系列新的建模技术，对多重灾害级联进行首次全面定量预测，这些技术受到北阿坎德Garwhal Himalaya实地观察历史的限制。该地区最近受到山体滑坡和山洪暴发的破坏，如2013年的Kedarnath灾难和2021年的Chomli山体滑坡。在这些陡峭的山谷中堆积的厚厚的沉积物被称为“沉积物炸弹”，因为它们对下游社区构成危险;这种沉积物炸弹可能在冰川退缩或山体滑坡阻塞山谷的地方形成。在这个项目中，印度和英国的团队将联合收割机整合数字地形学、遥感、计算机模型和实地监测的新方法，以了解冰川和山体滑坡产生的沉积物如何引发沉积物炸弹，以及这些沉积物如何被动员起来形成泥石流、山洪暴发和下游洪水。通过了解这些过程中的分布和速率，我们将生成中期预测，并将其输入到Alaknanda Valley社区开发的早期预警系统中。上述方法表明，物理科学模型将是考虑动态风险的唯一输入;但它不可能这么简单。面临这种风险的社区和管理预警系统的地区灾害管理机构必须参与科学方法的制定和重复。因此，我们正在与英国和印度的社会科学家合作，他们通过尊重不同文化，种族和基于性别的观点的研讨会和访谈与喜马拉雅社区合作。到项目结束时，我们将为地区当局制定一个决策工作流程，将动态风险纳入其中期预测，以应对级联灾害。我们在加尔鲸喜马拉雅山展示了这一进程，打算与印度和尼泊尔的国家灾害管理当局合作，促进动态风险评估的国家战略。