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

社区从重大灾害中“反弹”的能力对减轻贫困和经济发展至关重要。这一过程被称为“抗灾能力”，在中国尤其重要，因为快速的经济扩张和城市化增加了中国对许多重大灾害的敏感性，包括2008年汶川地震。地震引发的滑坡对恢复能力构成了特别的挑战，因为滑坡灾害发生率的增加可能会持续数十年。拟议的研究旨在了解是什么控制了这种持续的山体滑坡危害，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对恢复力的影响，我们将研究“社会脆弱性”在改变对地震及其相关危害的反应中的作用。我们将评估四川省社会脆弱性的潜在驱动因素和时空差异。我们将把我们对汶川地震后十年的滑坡危险性和社会脆弱性的估计结合起来，调查风险的空间格局以及它们如何随时间变化。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已经建立了地震以来巨大的滑坡灾害数据集。与卡迪夫大学可持续发展研究所的滑坡科学家和社会科学家合作，我们将以两种方式扩展这个数据集；(1)提高滑坡灾害制图的分辨率，了解余震和降雨在控制灾害中的相对作用；(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与滑坡灾害之间的相互作用如何在空间和时间上发生变化。我们的数据前所未有的细节将使我们能够开发一个新的滑坡灾害概率模型，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筑环境和关键基础设施的弹性进行建模。为了证明我们致力于通过更好的灾害规划来改善中国地震多发地区的福利，我们将与广泛的政府和非政府机构网络合作。从获得资助的第一天起，我们将与对科学和政策都感兴趣的组织合作，以实现这一目标。我们还将在不同人口和政策情景下建立复原力模型，以此作为理解和沟通建设复原力社区所面临挑战的工具。

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.