Design and Development of a Near Real-Time Community Crowdsourced Resilience Information System for Enhancing Community Resilience in the Face of Flooding and other Extreme Events

沿海沿着社区越来越容易受到极端天气事件和海平面上升造成的洪水等沿海灾害的影响。仅在美国，就有40%的人口居住在沿海城市，面临着更高的此类灾害风险。随着全球变暖，这些社区发生洪水事件的可能性也在增加。拟议项目将设计一个社区规模的社区抗灾信息系统（CRIS-HAZARD），利用公民科学和社区参与，实现实时数据驱动的决策，使社区更能抵御洪水。CRIS-HAZARD将支持社区、研究科学家和决策者之间频繁的双向信息流动。其目标是开发一个平台，通过让不同社区参与进来，改善所有公民的生活，特别是那些被边缘化的人的生活，促进智能和互联城市框架。 该项目在佛罗里达中西部墨西哥湾沿岸坦帕湾地区的佛罗里达皮内拉斯县进行试点。该地区的地理位置和低海拔使其特别容易受到气候变化引发的极端天气事件（如洪水）的影响。与以往整合数据和模型来预测洪水事件的尝试不同，CRIS-HAZARD的方法与众不同，因为这项研究率先整合了用户提供的数据（众包和社交媒体）与实时洪水预测模型和不确定性分析技术，预计将促进我们对面临持续洪水事件的沿海社区的风险和复原力的理解。该倡议整合了研究机构、政府机构（应急管理办公室）、当地利益攸关方和社区参与网络的专业知识，以加强基于社区的规划和政策决策，促进社区复原力。此外，该项目还在社区一级促进定制的复原力规划，让公民科学家作为合作伙伴参与进来。该奖项符合美国国家科学基金会的使命，即提供透明和可访问的风险和脆弱性信息，为全国范围内智能和弹性社区的发展做出贡献。该奖项反映了NSF的法定使命，并被认为值得通过使用基金会的知识价值和更广泛的影响审查标准进行评估来支持。

Communities along the coast are increasingly vulnerable to coastal hazards such as flooding due to extreme weather events and sea level rise. In the US alone, 40% of the population lives in coastal cities and subjected to elevated risks of such hazards. The probability of a flooding event in these communities is also increasing with global warming. The proposed project will design a neighborhood-scale Community Resilience Information System (CRIS-HAZARD) by leveraging citizen science and community participation for enabling real-time data-driven decision-making to make communities more resilient to flooding. CRIS-HAZARD will support frequent bi-directional flow of information among communities, research scientists, and decision-makers. The objective is to develop a platform that facilitates the smart and connected city framework by engaging diverse communities to improve the lives of all citizens, especially those who are marginalized. The project is piloted in Pinellas County, Florida, in the Tampa Bay region on the Gulf Coast of west-central Florida. This region’s geography and low elevation make it especially vulnerable to climate change-induced extreme weather events like flooding.Unlike previous attempts at integrating data and models to predict flooding events, the approach of CRIS-HAZARD is distinctive as this research pioneers the integration of user-supplied data (crowd-sourced and social media) with real-time flood prediction models and uncertainty analysis techniques, which is expected to advance our understanding of risk and resilience in coastal communities facing persistent flooding events. The initiative integrates the expertise of research institutions, government agencies (Office of Emergency Management or OEM), local stakeholders, and community engagement networks to enhance community-based planning and policy decisions, promoting community resilience. Furthermore, the project fosters customized resiliency planning at the neighborhood level engaging citizen scientists as partners. It aligns with the National Science Foundation's mission to provide transparent and accessible information on risks and vulnerability, contributing to the development of smart and resilient communities nationwide.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.