Collaborative Research: Measuring Social Vulnerability - Reducing Uncertainty and Validating Indicators

合作研究：衡量社会脆弱性——减少不确定性并验证指标

• 批准号: 1333190
• 负责人: Eric Tate
• 金额: $ 16.68万
• 依托单位: University of Iowa
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-08-15 至 2017-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1333190&HistoricalAwards=false
• 关键词: Collaborative; Research; Measuring; Social; Vulnerability

The objective of this collaborative research study is to improve the reliability of social vulnerability indicators by reducing uncertainties in input data and methods, and validating output metrics. Social vulnerability has been receiving increasing attention by disaster planners at local, state, and federal levels as they seek to reduce adverse impacts of natural hazards. Yet far too little is currently understood about the robustness of the leading vulnerability indicators, both in terms of the approaches used to build them and their ability to adequately represent real world conditions. There is a critical need for methodological advancements to improve the precision and accuracy of social vulnerability indicators. Without such advancements, the use of social vulnerability indicators in disaster mitigation, preparedness, and recovery could mislead decision-making. Based on a study area of the Southeast U.S., the project will develop novel regionalization routines and apply global sensitivity analysis and multiple regression to census data inputs and output vulnerability indicators. The research is expected to generate new understanding of the critical inputs and decision points in social vulnerability modeling, the level of agreement of resultant indicators with observed disaster outcomes, and the influence of uncertainty in social vulnerability modeling. By narrowing the existing gap between vulnerability models and real-world practice, improved social vulnerability indicators will allow for better disaster planning and interventions that account for the most vulnerable populations.The project has great potential to transform dominant approaches for the measurement of social vulnerability to hazards. The finalized methodology will be made widely accessible to both researchers and the public through an internet-GIS application that generates user-customizable vulnerability indices. The improved vulnerability metrics will also be shared with state and federal disaster planners through existing relationships with the research team. The study contributes to training the next generation of hazards researchers through the direct involvement of graduate and undergraduate students, including those from groups historically underrepresented in graduate research and education. The project findings will be integrated into the classroom through the development of learning modules for existing courses that explore urban geography and interactions between hazards and society.

这项合作研究的目的是通过减少输入数据和方法的不确定性，并验证输出指标，提高社会脆弱性指标的可靠性。 社会脆弱性越来越受到地方、州和联邦各级灾害规划人员的关注，因为他们试图减少自然灾害的不利影响。 然而，目前对主要脆弱性指标的可靠性了解甚少，无论是在建立这些指标的方法方面，还是在这些指标充分反映真实的世界状况的能力方面。 迫切需要在方法上取得进展，以提高社会脆弱性指标的精确度和准确性。 如果没有这些进展，在减灾、备灾和灾后恢复中使用社会脆弱性指标可能会误导决策。 基于美国东南部的一个研究区域，该项目将开发新的区域化程序，并将全球敏感性分析和多元回归应用于普查数据的投入和产出脆弱性指标。 这项研究预计将产生新的理解的关键投入和决策点在社会脆弱性建模，所产生的指标与观测到的灾害结果的协议水平，以及社会脆弱性建模的不确定性的影响。 通过缩小脆弱性模型与现实世界做法之间的现有差距，改进社会脆弱性指标将有助于更好地进行灾害规划和干预，考虑到最脆弱的人口，该项目具有改变衡量社会易受危害程度的主要方法的巨大潜力。 最后确定的方法将通过因特网地理信息系统应用程序向研究人员和公众广泛提供，该应用程序生成用户可定制的脆弱性指数。 改进后的脆弱性指标也将通过与研究小组的现有关系与州和联邦灾害规划人员分享。 这项研究有助于通过研究生和本科生的直接参与，包括那些来自历史上在研究生研究和教育中代表性不足的群体，培养下一代危害研究人员。 将通过为探索城市地理和灾害与社会之间的相互作用的现有课程开发学习模块，将项目结果纳入课堂。

项目成果

Social vulnerability to floods: Review of case studies and implications for measurement

• DOI: 10.1016/j.ijdrr.2015.09.013
• 发表时间: 2015-12-01
• 期刊: INTERNATIONAL JOURNAL OF DISASTER RISK REDUCTION
• 影响因子: 5
• 作者: Rufat, Samuel;Tate, Eric;Maroof, Abu Sayeed
• 通讯作者: Maroof, Abu Sayeed

Flood recovery and property acquisition in Cedar Rapids, Iowa

爱荷华州锡达拉皮兹的洪水恢复和财产收购

• DOI: 10.1007/s11069-015-2060-8
• 发表时间: 2016
• 期刊: Natural Hazards
• 影响因子: 3.7
• 作者: Tate, Eric;Strong, Aaron;Kraus, Travis;Xiong, Haoyi
• 通讯作者: Xiong, Haoyi