Agent-Based Modeling for Planning Emergency Response to Contamination Emergencies in Water Utilities

基于主体的建模，用于规划水务公司污染紧急情况的应急响应

• 批准号: 0927739
• 负责人: James Brumbelow
• 金额: --
• 依托单位: Texas A&M Engineering Experiment Station
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-01 至 2012-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0927739&HistoricalAwards=false
• 关键词: Agent; Based; Modeling; Planning; Emergency

This research project bridges the disciplines of hydraulic engineering and social science to provide answers to the questions a water utility manager faces in a contamination event, "What do I need to know and what tools can I use to effectively minimize sickness and deaths from this event?" Approximately 90 percent of the U.S. population receives water from one of 170,000 public water utilities. Despite the ubiquity of this infrastructure and its importance for public health, many aspects of emergency management for water systems remain at an undeveloped stage. Accidental contaminants in the water distribution system erode public trust and result in sickness and death, and malicious contamination may cause even more destructive results. As a contamination event unfolds, water utility managers need to make decisions in an extraordinarily difficult environment: information that they receive is incomplete and subject to great error; the water distribution system is dynamic and extremely complex; and consumer reactions are uncertain and affect the operation of the water system, making the dynamics of the system even more complex and uncertain. Throughout an event, consumers may reduce their water consumption based on official notices, such as boil water notices, or informal (peer-initiated) warnings, and the actions of consumers in response to these alerts will change hydraulic conditions in the network. Thus, any further decisions by water utility managers should take into account the fluctuations of the contaminant plume. The project addresses several unknown facets of the water distribution threat management problem. This research will collect data needed to empirically model consumers' decision-making process and compliance rates to protective action recommendations. Empirical models of consumer behavior and hydraulic simulation of water distribution networks will be coupled through an agent-based modeling (ABM) framework. The simulation framework will be coupled with optimization algorithms to evaluate large sets of response options and develop effective emergency response plans that account for uncertainty and the dynamic nature of population-infrastructure interactions. Project results will be used to develop a protocol for responding to contamination events for municipalities and water utilities.While intentional contamination is a realistic threat to U.S. water utility infrastructure, little research literature exists on the complex interactions of emergency warnings, public response, and management effectiveness for water utilities. The Environmental Protection Agency has published documents to provide some guidance for responding to a water distribution event, but can recommend only very generic actions, as the best response for a utility depends on the hydraulic characteristics of the system, the characteristics of the contaminant release, and the interactions of the public, media, and decision makers. This framework will allow a specific water utility to identify response options for a range of events based on its particular characteristics, thus preparing and equipping public officials and water utility operators to better protect public health. When a utility uses the framework, a set of documents and flowcharts will be produced that can later be used to guide management actions in real-time as a contaminant event unfolds and the characteristics of the event are understood as information is gathered.

这项研究项目在水利工程和社会科学之间架起了桥梁，为水务经理在污染事件中面临的问题提供了答案：我需要知道什么，我可以使用什么工具来有效地将这一事件造成的疾病和死亡人数降至最低。大约90%的美国人口从17万家公共水务公司中的一家获得水。尽管这一基础设施无处不在，而且对公共卫生很重要，但供水系统应急管理的许多方面仍处于不发达阶段。供水系统中的意外污染物侵蚀公众信任，导致疾病和死亡，恶意污染可能会造成更具破坏性的后果。随着污染事件的发生，自来水公司管理者需要在一个异常困难的环境中做出决定：他们收到的信息不完整，容易出现巨大错误；供水系统是动态的，极其复杂；用户的反应不确定，会影响供水系统的运行，使系统的动态更加复杂和不确定。在整个活动中，用户可以根据官方通知(如开水通知)或非正式(同行发起的)警告来减少用水量，用户对这些警报的响应将改变网络中的水力条件。因此，自来水公司管理者的任何进一步决定都应考虑到污染物羽流的波动。该项目解决了水分配威胁管理问题的几个未知方面。这项研究将收集所需的数据，对消费者的决策过程和对保护行动建议的遵从率进行实证建模。用户行为的经验模型和供水管网的水力模拟将通过基于主体的建模(ABM)框架耦合。模拟框架将与优化算法相结合，以评估大量的应对方案，并制定有效的应急计划，以应对人口-基础设施相互作用的不确定性和动态性质。项目成果将被用于为市政当局和自来水公司制定应对污染事件的协议。虽然故意污染是对美国自来水公司基础设施的现实威胁，但关于自来水公司的紧急警告、公共响应和管理有效性之间复杂交互作用的研究文献很少。美国环境保护局已经发布了一些文件，为应对配水事件提供了一些指导，但只能建议非常一般性的行动，因为公用事业的最佳反应取决于系统的水力特性、污染物释放的特性以及公众、媒体和决策者的互动。这一框架将使特定的自来水公司能够根据其特殊特点确定一系列事件的应对方案，从而为公共官员和自来水公司经营者做好准备和装备，以更好地保护公众健康。当公用事业公司使用该框架时，将产生一组文件和流程图，这些文件和流程图稍后可用于在污染物事件展开时实时指导管理行动，并在收集信息时了解事件的特征。