SCC-CIVIC-PG Track B: Helping Rural Counties to Enhance Flooding and Coastal Disaster Resilience and Adaptation

在美国，洪水是自然灾害的主要原因，国会预算办公室估计，每年的损失为540亿美元。尽管城市和农村地区都非常容易受到洪水灾害的影响，但大多数自然灾害复原力研究都集中在城市地区，往往忽视了农村社区。其中一个被忽视的领域是与五大湖接壤的许多农村社区。由于水位上升，特别是自2012年以来，这些社区正面临前所未有的挑战，这给社区带来了重大的沿海洪水危险。洪灾风险评估是支持社区确定如何减轻洪灾的关键工具；然而，当前洪灾风险建模工具中的数据差距使其对农村社区来说不准确。该项目将使用各种策略，包括传感器和众包信息，以填补改善大湖沿岸农村社区洪水灾害建模所需的关键信息缺口。该项目旨在将社区和大学合作伙伴聚集在一起，了解密歇根州北部三个县在应对洪水和沿海灾害方面的数据缺口。由于水位上升，五大湖区的农村、沿海和内陆县面临前所未有的挑战。虽然这些农村社区容易受到洪水的影响，但由于缺乏资源，他们缺乏洪水风险评估和洪水淹没地图。联邦紧急事务管理局(FEMA)和国土安全部(DHS)通常建议各县使用免费提供的工具-HAZUS来制定减灾计划，增强社区的复原力和适应能力。然而，除非用更多的数据和分析加以补充，否则农村社区对HAZUS的使用可能会有一些严重的缺陷。这些严重的缺陷是由于农村社区在分析危害方面的数据差距造成的。农村县使用标准数据集进行HAZUS分析，可能会使社区对未来重大洪水事件准备不足。拟议项目的愿景是开发利用遥感数据资源和公民参与(众包)的方法，以解决目前的数据差距，以改进洪水风险建模和可视化，并可转移到农村社区。该项目是对公民创新挑战计划的回应，B轨道-自然灾害的恢复力-是NSF和国土安全部的合作。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

In the United States, flooding is a leading cause of natural disasters, with congressional budget office estimates of $54 billion in loss each year. Although both urban and rural areas are highly vulnerable to flood hazards, most natural disaster resilience studies have focused on urban areas, often overlooking rural communities. One such area that has been overlooked are the many rural communities bordering the Great Lakes. These communities are facing unprecedented challenges due to rising water levels, particularly since 2012, which have resulted in significant coastal flood hazards to the communities. Flood hazard assessments are a critical tool that is used support communities in determining how to mitigate flooding; however, data gaps in current flood hazard modeling tools render them inaccurate for rural communities. This project will use various strategies, including sensors and crowdsourced information, to fill critical information gaps required to improve flood hazard modeling in rural communities bordering the Great Lakes.This project aims to bring together community-university partners to understand the data gaps in addressing flooding and coastal disaster in three Northern Michigan Counties. The rural coastal and inland counties in the Great Lakes states face an unprecedented challenge due to rising water levels. While these rural communities are vulnerable to flooding, they lack flood hazard assessments and inundation maps due to the lack of resources. The Federal Emergency Management Agency (FEMA) and the Department of Homeland Security (DHS) commonly recommend counties to use a freely available tool—called HAZUS to develop hazard mitigation plans and enhance community resilience and adaptation. However, the usage of HAZUS for rural communities could potentially have some serious deficiencies unless augmented with additional data and analyses. These severe deficiencies are due to the data gaps in analyzing the hazards in rural communities. The use of standard datasets for HAZUS analysis by rural counties could likely leave the communities underprepared for future flood events of significant magnitude. The proposed project’s vision is to develop methods that use remote sensing data resources and citizen engagement (crowdsourcing) to address current data gaps for improved flood hazard modeling and visualization that is transferable to rural communities. This project is in response to the Civic Innovation Challenge program, Track B—Resilience to Natural Disasters—and is a collaboration between NSF and the Department of Homeland Security.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.