Data-driven climate change risk assessment for heritage in England

不断变化的气候正在影响支撑社会的基础设施、经济和资源使用以及福祉的弹性。遗产在历史建筑环境中和作为考古遗址，在解决这些方面的每一个方面都可以发挥重要作用。风险评估是我们理解气候变化影响的基础。在此，我们建议使用政府间气候变化专门委员会目前使用的风险框架，该框架确定了风险的三个组成部分：危险--一种潜在的破坏性物理现象，暴露--对社区重要并可能受到危险影响的[遗产]资产的位置、属性和价值，以及脆弱性--资产在暴露于危险中时受到影响/损坏/摧毁的可能性。到目前为止，大多数关于气候变化和遗产的风险评估都侧重于风险评估，包括测绘和传达发生频率和/或严重程度的变化，以及对脆弱性的定性表示，这包括历史英格兰自己与英国遗产合作伙伴合作绘制影响遗产的气候危害地图。因此，我们对英国气候变化风险最大地区的看法是由那些危害变化最显著的地区提供信息的。然而，这忽略了这样一个事实，即只有一小部分遗产、某些类型的遗产或对特定社区具有重要意义的遗产可能位于仅通过危险评估确定的这些地区，或者具有容易受到这些危险影响的价值。由于英格兰丰富的遗产的多样性和规模(英格兰国家遗产名录上约有360,000项遗产资产，是当地历史环境记录中的许多倍，并作为未列入名录的遗产存在)，这需要一种数据驱动的方法。该项目将进行一项统计气候变化风险评估，其中包括英格兰遗产的危险、脆弱性和暴露情况。该项目将使用数据驱动的空间分析和传播来提供统计上可靠的气候变化-遗产风险评估，将气候影响驱动因素(灾害)与遗产脆弱性和风险暴露结合起来。这将首先回顾遗产组织中存在的相关文献和学科专门知识，并为NHLE开展一个试点项目。该项目的大部分将致力于制定国家规模的风险和传播/传播结果的表述。该项目将确定气候遗产复原力研究、实践和政策方面现有方法的局限性。通过将这些方法与其理论基础联系起来，它将确定改进气候遗产复原力的统计方法的机会，特别是在物质损失、社会和经济背景以及可持续资源利用的情况下，更密切地调整历史上不同的影响和应对措施。在该领域探索创新的统计方法将为研究气候遗产复原力开辟新的方向，并产生新的证据，为政策和实践提供信息。这项工作将为在遗产背景下有力和动态地应对气候变化奠定基础，这将使学生处于遗产部门新兴领域的前沿，同时还将使他们掌握全面的数据科学技能，这些技能可以更广泛地应用。

A changing climate is impacting the resilience of the infrastructure, economy and resource use, and wellbeing that underpin society. Heritage, within the historic built environment and as archaeological sites, has an important role to play in addressing each of these aspects. Underpinning our understanding of the impacts of climate change is risk assessment. Herein we propose to use the risk framework currently used by the Intergovernmental Panel on Climate Change, which identifies three components of risk: hazard - a potentially destructive physical phenomenon, exposure - the location, attributes, and value of [heritage] assets that are important to communities and that could be affected by a hazard, and vulnerability - the likelihood that assets will be affected/damaged/destroyed when exposed to a hazard. Most risk assessment to date on climate change and heritage has focused on hazard assessment, including mapping, and communicating changes in frequency of occurrence and/or severity, combined with a qualitative representation of the vulnerability, this includes Historic England's own collaboration with UK heritage partners to map the climate hazards affecting heritage. Thus, our perception of areas that are prone to the greatest level of risk to climate change in the UK is informed by those with the most significant changes in hazards. However, this overlooks the fact only a small fraction of heritage, certain types of heritage, or heritage with significance to particular communities, may lie within these areas as identified through hazard assessment alone, or have values that are vulnerable to those hazards.Drawing on the IPCC framework above, a more accurate understanding of climate change related risks for heritage needs to incorporate vulnerability and exposure. Due to the diversity and scale of England's rich heritage (there are about 360,000 heritage assets on the National Heritage list for England and many times that on local Historic Environment Records and existent as unlisted heritage), this requires a data-driven approach. This project will undertake a statistical climate change risk assessment that incorporates hazard, vulnerability, and exposure for England's heritage. This project will use data-driven spatial analysis and communication to provide statistically robust climate change-heritage risk assessment that combine climatic impact drivers (hazards) with heritage vulnerability and exposure. This will begin with a review of the relevant literature and subject expertise present in heritage organisations and a pilot project for the NHLE. The bulk of the project will be devoted to developing representations of national-scale risk and communication/dissemination outputs.This project would identify the limitations of existing approaches within climate heritage resilience research, practice, and policy. By relating these approaches to their theoretical basis, it would identify opportunities to improve statistical approaches to climate heritage resilience, especially to align historically disparate impacts and responses more closely to climate change within material loss, social and economic contexts, and sustainable resource use. The exploration of innovative statistical methods within the field will develop new directions for research climate heritage resilience and produce new evidence to inform policy and practice. This work will lay the foundation for robust and dynamic responses to climate change in a heritage context, which would establish the student at the front of an emerging area of the heritage sector while also equipping them with comprehensive data science skills that could be applied more widely.