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，由于气候变化以及人口迅速增长，野火频率，幅度以及造成的人类和经济损失有显着增加，到野生世界界面（WUI，房屋和基础设施在这里遇到野生世界）。野火风险可以通过三种类型的事件前的家庭危害调整大大降低，即防备工作，准备，保留，捍卫和生存，并准备撤离。但是，影响采用这些危害调整的因素仍然鲜为人知。现有的野火疏散模型很少考虑火灾传播动态。缺乏人，火灾危害和交通部件的三边融合；并基于有限的社会行为数据。为了解决这些知识差距，该项目将将行为数据与主动学习和目标设定技术整合在一起，以增加WUI居民采用事前危害调整。此外，社交行为数据将被注入运输工程模型中，以创建更准确和可操作的基于代理的模型（ABMS）进行撤离。为了实现这些目标，研究人员将与三个州的四个WUI社区合作（1）确定影响家庭事件前危险调整的采用和野火危害的疏散决策的因素，以及（2）综合的社交行为数据中的综合社会行为数据中的野火疏散现场，使用ABMS评估替代撤离策略。区域规划人员和紧急经理将聘请测试和评估疏散方案和教育计划。该项目将扩大和加强保护行动决策模型（PADM）的能力，以解释与野火缓解，停留/防御/捍卫/避免准备和疏散准备的复杂决策过程。具体而言，该项目的结果将提高我们在有关野火危害的风险消息方面的知识，并满足将多维数据集纳入野火疏散模型中的迫切需求。对四个不同WUI社区的研究将允许评估项目研究领域内外的跨种群概括性。结果将导致激励家庭的保护行动，评估社区信息循证疏散建模的策略，测试替代性野火警告消息传递策略的最佳实践，并最终减少居民和企业的野火风险。潜水员项目团队包括来自代表性不足的团体的早期科学家，学生和研究人员。该项目将基于与社区利益相关者以前的合作，以共同生产和共享整个研究过程中的知识，以确保工作将促进数据驱动的政策和资源分配。该奖项反映了NSF的法定任务，并被认为是通过基金会的知识分子优点和更广泛的影响审查标准来通过评估来获得的支持。