Collaborative Research: Household Response to Wildfire – Integrating Behavioral Science and Evacuation Modeling to Improve Community Wildfire Resilience

合作研究：家庭对野火的反应 — 整合行为科学和疏散模型以提高社区野火的抵御能力

• 批准号: 2230595
• 负责人: Haizhong Wang
• 金额: $ 25万
• 依托单位: Oregon State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-08-01 至 2026-07-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2230595&HistoricalAwards=false
• 关键词: Collaborative; Research; Household; Response; Wildfire

The past four decades have seen a significant increase in wildfire frequency, magnitude, and resulting human and economic losses as driven by climate change and rapid population growth into the wildland-urban interface (WUI, where homes and infrastructure meet the wildland). Wildfire risk can be significantly reduced by three types of pre-event household hazard adjustments—mitigation, preparedness to stay, defend, and survive, and readiness to evacuate. However, the factors that influence the adoption of these hazard adjustments remain poorly understood. Existing wildfire evacuation models rarely consider fire spread dynamics; lack trilateral integration of people, fire hazard, and traffic components; and are based on limited social-behavioral data. To address these knowledge gaps, this project will integrate behavioral data with active learning and goal-setting techniques for increasing WUI residents’ adoption of pre-event hazard adjustments. In addition, social-behavioral data will be infused into transportation engineering models to create more accurate and actionable agent-based models (ABMs) for evacuation. To achieve these objectives, the researchers will collaborate with four WUI communities in three states to (1) identify factors influencing households’ pre-event hazard adjustment adoption and evacuation decision-making for wildfire hazard, and (2) integrate social-behavioral data into wildfire evacuation scenarios using ABMs to evaluate alternative evacuation strategies. Regional planners and emergency managers will be engaged to test and evaluate evacuation protocols and educational programs. This project will expand and strengthen the capability of the Protection Action Decision Model (PADM) to explain complex decision-making processes related to wildfire mitigation, stay/defend/survive preparedness, and evacuation readiness. Specifically, this project’s results will advance our knowledge in pre-event risk messaging about wildfire hazards and address the urgent need for incorporating multidimensional datasets in wildfire evacuation models. The study of four different WUI communities will allow assessment of the cross-population generalizability within and beyond the project’s study areas. The outcomes will lead to best practices for motivating households’ protective actions, assessments of community-informed evidence-based strategies for wildfire evacuation modeling, testing of alternative wildfire warning messaging strategies, and, ultimately, reduction in wildfire risk to residents and businesses. The diverse project team includes early-career scientists, students, and researchers from underrepresented groups. The project will build upon previous collaborations with community stakeholders to co-produce and share knowledge throughout the research process, ensuring that the work will promote data-driven policies and resource allocation.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

在过去的四十年中，由于气候变化和荒地与城市交界处（WUI，房屋和基础设施与荒地交汇处）人口的快速增长，野火的频率、规模以及由此造成的人员和经济损失显着增加。通过三种类型的事前家庭危险调整（缓解、停留、防御和生存准备以及撤离准备）可以显着减少火灾风险。然而，影响这些危险调整的因素仍然知之甚少。疏散模型很少考虑火灾蔓延动态；缺乏人员、火灾危险和交通组成部分的三方整合；并且基于有限的社会行为数据。为了解决这些知识差距，该项目将把行为数据与主动学习和目标设定相结合。此外，社会行为数据将被纳入交通工程模型中，以创建更准确且可操作的基于代理的疏散模型（ABM）。研究人员将与三个州的四个 WUI 社区合作，(1) 确定影响家庭针对野火危险采取灾前危险调整和疏散决策的因素，以及 (2) 使用 ABM 将社会行为数据整合到野火疏散场景中，以进行评估区域规划者和应急管理人员将参与测试和评估疏散方案和教育计划，该项目将扩展和加强保护行动决策模型（PADM）的能力，以解释与相关问题相关的复杂决策过程。具体来说，该项目的结果将提高我们对野火危险的事前风险信息传递的了解，并解决将多维数据集纳入野火疏散模型的迫切需要。不同的 WUI 社区将允许评估项目研究区域内外的跨人群普遍性，其结果将产生激励家庭保护行动的最佳实践，以及对社区知情的评估。该项目的多元化项目团队包括来自代表性不足群体的早期职业科学家、学生和研究人员。将建立在之前与社区利益相关者合作的基础上，在整个研究过程中共同创造和分享知识，确保这项工作能够促进数据驱动的政策和资源分配。该奖项反映了 NSF 的法定使命，并通过使用评估结果被认为值得支持基金会的智力价值和更广泛的影响审查标准。