Investment Planning for Regional Natural Disaster Mitigation

区域自然灾害减灾投资规划

• 批准号: 0555738
• 负责人: Linda Nozick
• 金额: --
• 依托单位: Cornell University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-07-15 至 2010-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0555738&HistoricalAwards=false
• 关键词: Investment; Planning; Regional; Natural; Disaster

Abstract CMS-0555738 (Davidson) Investment Planning for Regional Natural Disaster Mitigation This project will develop a set of models to: help guide an optimal expenditure of regional natural disaster mitigation funds, and provide insight into the many factors that interact to determine the best mix of mitigation strategies. Focusing on earthquakes and hurricanes, the regional natural disaster mitigation analysis models will help an at-risk region with a limited budget decide how much to spend on pre-event mitigation that aims to reduce future losses versus post-event recovery, and which of the many possible pre-event mitigation activities to fund so as to meet the region?s objectives, The proposed set of models will advance knowledge about natural disaster risk management and the simultaneous planning for multiple hazards. While it is widely thought that pre-disaster mitigation is desirable, and a lot has been done to develop structural and other techniques for disaster mitigation, the circumstances in which it is desirable to implement different mitigation measures are not well understood. This project will merge optimization and loss estimation modeling to provide new insights into resource allocation decisions for mitigation. The findings may be generalizable to other hazards and to risk managers in other contexts.

摘要CMS-0555738（戴维森）区域自然灾害减灾的投资规划本项目将开发一套模型，以：帮助指导区域自然灾害减灾基金的最佳支出，并提供深入了解许多因素相互作用，以确定最佳的减灾战略组合。以地震和飓风为重点，区域自然灾害减灾分析模型将帮助预算有限的风险区域决定在旨在减少未来损失的灾前减灾与灾后恢复方面花费多少，以及为许多可能的灾前减灾活动中的哪一项提供资金，以满足该区域的需求？的目标，拟议的一套模型将推进知识的自然灾害风险管理和同时规划的多个危险。虽然人们普遍认为灾前减灾是可取的，而且已经做了很多工作来发展减灾的结构技术和其他技术，但人们并不十分了解在何种情况下需要执行不同的减灾措施。该项目将合并优化和损失估计建模，为缓解资源分配决策提供新的见解。研究结果可能是一般化的其他危害和风险管理人员在其他情况下。