EAGER: Wildfire Modeling and Prevention Initiative: Developing a Technical Framework for Integrating Research with Public Policy Decision Support

EAGER：野火建模和预防计划：开发将研究与公共政策决策支持相结合的技术框架

• 批准号: 1126615
• 负责人: Larry Smarr
• 金额: $ 26.24万
• 依托单位: University of California-San Diego
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-07-01 至 2012-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1126615&HistoricalAwards=false
• 关键词: EAGER; Wildfire; Modeling; Prevention; Initiative

Wildfires are increasing in both absolute number and severity in the American southwest and this trend is predicted to continue over decades to come. Therefore, the need for descriptive and predictive simulation tools to support wildfire prevention, or suppression during future wildfire events, is becoming critical. As a first step, this project aims to develop a technical framework for integrating three dimensional landscape models, real-time environmental data, and suite of simulation codes, and wildfire management protocols. This research will involve determining how best to merge elevation and ground classification datasets, couple fire propagation, atmospheric, and hydrologic simulation codes, and verify the accuracy of the coupled computations against historical wildfire data. Key components in the development of the technical framework include: 1) Identifying and obtaining access permissions to the wide variety of datasets needed to create the high-resolution digital model of the topography and landscape of San Diego County. 2) Investigating how these datasets can be seamlessly "sewn together" using GIS software systems. The integration methodology being developed will be investigated using an unburned area of the San Diego County?s Santa Margarita Ecological Reserve, which is an ideal rapid prototyping and validation site for this project. It is prone to the strong Santa Ana wind events we wish to study and is already equipped with intensive real-time wireless ground sensors connected through the NSF's High Performance Wireless Research and Education Network (HPWREN).

美国西南部的绝对数量和严重程度的野火越来越高，预计这种趋势将持续数十年来。 因此，需要描述性和预测性仿真工具支持预防野火，或者在将来的野火事件期间抑制的需求变得至关重要。作为第一步，该项目旨在开发一个技术框架，以整合三维景观模型，实时环境数据和仿真代码套件以及野火管理协议。 这项研究将涉及确定如何最好地合并高程和地面分类数据集，夫妇火灾传播，大气和水文模拟代码，并验证耦合计算对历史野火数据的准确性。 技术框架开发的关键组成部分包括：1）识别并获得对创建圣地亚哥县地形和景观高分辨率数字模型所需的各种数据集的访问权限。 2）研究如何使用GIS软件系统将这些数据集无缝“缝制”。 正在开发的集成方法将使用圣地亚哥县圣玛格丽塔酒生态储备的未燃烧区域进行研究，这是该项目的理想快速原型制作和验证地点。 它容易出现我们希望学习的强大的圣安娜风赛事，并且已经配备了通过NSF高性能无线研究和教育网络（HPWREN）连接的密集实时无线接地传感器。