Resilience to EArthquake-induced landslide risk in CHina (REACH)

社区从重大灾害中“恢复过来”的能力对减贫和经济发展至关重要。这一过程被称为“抗灾能力”，在中国看来尤为重要，因为快速的经济扩张和城市化增加了中国人对一些重大灾害的敏感性，包括2008年的汶川地震。地震引发的山体滑坡是对复原力的特别挑战，因为滑坡危险性的增加可能会持续数十年。这项拟议的研究试图了解是什么控制了这种持续的山体滑坡危险，以及导致山体滑坡危及恢复的过程。为了了解恢复过程及其如何影响复原力，我们将调查“社会脆弱性”在调整对地震及其相关灾害的反应方面的作用。我们将评估社会脆弱性的潜在驱动因素以及四川省的时空差异。我们将结合我们对汶川地震后十年间滑坡灾害和社会脆弱性的估计，调查风险的空间模式以及这些模式如何随时间变化。为了实现这些目标，我们将把工作重点放在汶川地震受灾地区，成都理工学院地质灾害防治与地质环境保护国家重点实验室在那里创建了地震以来滑坡灾害的极其庞大的数据集。与卡迪夫大学可持续地点研究所的滑坡科学家和社会科学家合作，我们将通过两种方式扩展这一数据集；(1)提高滑坡危险地图的分辨率，以了解余震和降雨在控制灾害方面的相对作用，以及(2)利用当地人口普查数据，了解社会脆弱性以及社会脆弱性和滑坡灾害之间的互动在空间和时间上如何变化。我们史无前例的详细数据将使我们能够开发一个新的概率滑坡风险模型，该模型包含余震和降雨事件引起的滑坡，可以应用于地震多发的中国，甚至可以应用于全球。作为这项工作的一部分，收集的现场数据将有助于限制阈值，从而有助于支持四川滑坡预警系统的建设。最后，我们将通过最先进的机器学习算法对建成环境和关键基础设施的弹性进行建模。作为我们致力于通过更好的灾害规划来改善地震多发中国的福利的证据，我们将与广泛的政府和非政府机构网络接触。从拨款的第一天起，我们将与对科学和政策感兴趣的组织接触，以实现这一目标。我们还将模拟不同人口和政策情景下的复原力，将其作为了解和沟通建立复原力社区的挑战的工具。

The ability for communities to "bounce back" from major disasters is essential for poverty alleviation and economic development. Termed "disaster resilience", this process is of particular importance in China as rapid economic expansion and urbanization has increased Chinese susceptibility to a number of major disasters, including the 2008 Wenchuan Earthquake. Earthquake-induced landslides represent a particular challenge to resilience as increased rates of landslide hazard may persist for many decades. The proposed research seeks to understand what controls this persistent landslide hazard and the processes that cause landslides to jeopardise recovery. To understand the recovery process and how it affects resilience, we will investigate the role of "social vulnerability" in modifying the response to earthquakes and their related hazards. We will assess the underlying drivers of social vulnerability and the spatio-temporal differences across Sichuan province. We will combine our estimates of landslide hazard and social vulnerability across the decade after the Wenchuan Earthquake, investigating both the spatial patterns of risk and how these change with time. To achieve these goals, we will focus our work on the areas affected by the Wenchuan Earthquake, where the Chengdu Institute of Technology-State Key Laboratory of Geohazard Prevention and Geoenvironment Protection has created an incredibly large dataset of landslide hazards since the earthquake. In collaboration with landslide scientists and social scientists at Cardiff University's Sustainable Places Research Institute, we will expand this dataset in two ways; (1) increasing the resolution of landslide hazard mapping to understand the relative role of aftershocks and rainfall in controlling hazard, and (2) using local census data to understand social vulnerability and how the interaction between social vulnerability and landslide hazards has changed in space and through time. The unprecedented detail of our data will enable us to develop a new probabilistic landslide hazard model that incorporates landslides caused by both aftershocks and rainfall events that can be applied across earthquake-prone China and perhaps even globally. Field data collected as part of this effort will help to constrain threshold values and so help support the construction of a landslide early warning system for Sichan. Finally, we will model the resilience of the built environment and key infrastructure through state of the art machine learning algorithms. As evidence of our commitment to improve the welfare of earthquake-prone China through better planning for disasters we will engage with an extensive network of governmental and non-governmental institutions. From the first day of the grant we will engage with organisations with interests in both science and policy to achieve this goal. We will also model resilience under different demographic and policy scenarios, using this as a tool to understand and communicate the challenges of building resilient communities.