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Software for quantifying shallow landslide hazards to transportation infrastructure under changing climate and forest management

用于量化气候变化和森林管理下浅层滑坡对交通基础设施造成的危害的软件

基本信息

批准号：
NE/N01300X/1
负责人：
Simon Mudd
金额：
$ 14.94万
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：
2016
资助国家：
英国
起止时间：
2016 至无数据
项目状态：
已结题

来源：
https://gtr.ukri.org/projects?ref=NE%2FN01300X%2F1
关键词：
Software quantifying shallow landslide hazards

项目摘要

Critical infrastructure in upland landscapes can be damaged by landslides and debris flows, and managing and mitigating the risks posed to this infrastructure is a key challenge for infrastructure owners. In addition, landslides and debris flows do not respect ownership boundaries, and third party landowners can find themselves liable for mass movements originating from their land, whereas infrastructure owners have to manage hazards from beyond their holdings. In addition, transport owners and maintaining agents must be able to plan on works to be delivered at the right time and in the right place. Planning efficient spending has a number of challenges, including persistent uncertainty in how changes in climate and land use affect future landslide susceptibility and limited capability to make effective use of high resolution digital datasets (e.g. LiDAR surveys) to model landslide scenarios.This project will develop software for producing landslide hazard maps at regional scales incorporating the highest resolution topographic and land use data. It builds on previous hazard research at the University of Edinburgh and the British Geological Survey, and is built to work in a mulitcore, supercomputing environment--the software can handle big data in the form of very high resolution LiDAR surveys that provide information on slopes at the sub-metre scale: the scale at which mass movements and the hydrology that drive them operate. In addition, the software will be designed to provide scenario modelling. In particular, one of the major drivers in changes in landslide hazard is changing root cohesion from different vegetation patterns along transport corridors. The project will assimilate forestry data from Forest Research so that we can investigate the planting and harvesting schedule that minimised landslide risk, and also determine the time at which transport corridors are most threatened by landsliding. The ultimate objective of the project is to provide a software tool that land owners, infrastructure owners and maintaining agents can use to better plan mitigation and spending strategies.

高地景观中的关键基础设施可能受到山体滑坡和泥石流的破坏，管理和减轻对这一基础设施构成的风险是基础设施所有者面临的一个关键挑战。此外，滑坡和泥石流不尊重所有权边界，第三方土地所有者可能发现自己对源于其土地的群众运动负有责任，而基础设施所有者则必须管理其土地以外的危害。此外，运输业主和维护代理必须能够计划在正确的时间和正确的地点交付工程。规划高效率的支出有许多挑战，包括气候和土地使用变化如何影响未来滑坡易发性的持续不确定性，以及有效利用高分辨率数字数据集（如激光雷达调查）模拟滑坡情景的能力有限，该项目将开发软件，用于制作区域尺度的滑坡灾害地图，其中包括最高分辨率的地形和土地使用数据。它建立在爱丁堡大学和英国地质调查局以前的灾害研究基础上，并建立在多核超级计算环境中-该软件可以以非常高分辨率的激光雷达调查的形式处理大数据，提供关于亚米尺度斜坡的信息：质量运动的规模和驱动它们的水文作用。此外，软件的设计将提供情景模拟。特别是，滑坡灾害变化的主要驱动力之一是改变根的凝聚力从不同的植被模式沿着运输走廊。该项目将吸收来自森林研究的林业数据，以便我们能够调查最大限度地减少滑坡风险的种植和收获时间表，并确定运输走廊最受滑坡威胁的时间。该项目的最终目标是提供一个软件工具，供土地所有者、基础设施所有者和维护代理人使用，以更好地规划减灾和支出战略。