RAPID: Assessing Resiliency among Rural, Suburban, and Urban Communities Following the Thailand Floods Of 2011

RAPID：评估 2011 年泰国洪水后农村、郊区和城市社区的复原力

• 批准号: 1242004
• 负责人: Sudha Arlikatti
• 金额: $ 7.36万
• 依托单位: University of North Texas
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-07-15 至 2014-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1242004&HistoricalAwards=false
• 关键词: RAPID; Assessing; Resiliency; among; Rural

During the 20th century, floods were the cause of the most number of lives lost and property damage from natural disasters in the United States (US). This trend will continue in the 21st century as more Americans migrate to coastal communities and floodplains. Unfortunately there is no consensus on what makes some communities more resilient to floods than others. Generally, the term "community resiliency" refers to the capability to rebound from an adverse situation. The concept has gained widespread interest since the adoption of the Hyogo Framework for Action (2005-2015), which calls on nations to build greater community resiliency. While disaster scholars have developed numerous indicators to measure resiliency and broadly classified the dimensions as ecological, social, economic, institutional, infrastructure, and community competencies (Cutter et al., 2008; Cutter et al., 2010; Chang & Shinozuka, 2004; Manyena, 2006; Morrow, 2008), these studies have been limited to the US and to static, secondary data. The proposed project aims to fill these gaps by assessing how communities in Thailand responded to the 2011 floods. The severe floods that plagued Thailand for over eight months in 2011 were triggered by Tropical Storm Nock-ten. The storm water overflows along the Mekong and Chao Phraya River basins resulted in severe inland flooding, affecting 65 of the country's 76 provinces and over 12 million people. Our project examines the disparities in the abilities of rural (Pathum Thani), suburban (Ayutthaya), and urban (Bangkok) communities, to rebound after such prolonged flooding. It is guided by the Disaster of Place (DROP) model, proposed by Cutter et al. (2008), which used county level spatial data (in the US) to describe disaster resilience in specific geographic areas and across political boundaries. The US research team and Thai collaborators will interview key participants from 45-50 public, private, and non-profit organizations, using semi-structured interviews. We will document the earliest processes, programs, and policies used to address the needs of the populace as they transitioned from short-term to long-term recovery. Ephemeral data will be collected documenting how decisions were initially made and/or changed by organizations serving rural, suburban and urban flood victims. These data will be used to understand ad hoc policies and fluid governance mechanisms that are likely to explain variations in community resiliency to floods across jurisdictions and geographic units. Upon return to the US, an e-survey will be sent to 300 other organizations in Thailand to gather information from a larger sample. This research makes theoretical and practical contributions by, 1) Helping to validate the DROP model and testing its applicability in an international setting, 2) Augmenting or modifying the indicators used in the DROP model with real-time data gathered at the organizational level in flood impacted communities, 3) Emphasizing the attributes of multi-sector organizations in building community resiliency during the transition from short-term to long term recovery and, 4) Allowing for cross cultural understanding, and international knowledge exchange that supports the broader efforts of NSF and disaster scholars from around the world.This award was jointly funded by the Division of Civil, Mechanical and Manufacturing Innovation and the Office of International Science and Engineering's Global Venture Fund.

在20世纪，洪水是丧生数量最多的原因，在美国（美国）造成自然灾害的财产损害。随着越来越多的美国人迁移到沿海社区和洪泛区，这种趋势将在21世纪持续。不幸的是，关于使某些社区比其他社区更适合洪水的原因尚无共识。通常，“社区弹性”一词是指在不利情况中反弹的能力。 自从采用了Action for Action框架（2005-2015）以来，该概念引起了广泛的兴趣，该概念呼吁各国建立更大的社区弹性。尽管灾难学者已经制定了许多指标来衡量弹性并将其范围归类为生态，社会，经济，机构，基础设施和社区能力（Cutter等，2008; Cutter等，2010; Chang＆Shinozuka，2004; Manyena，2006; Morory，2006; Morrows; Morore，2008; Many＆Shinozuka; Many＆Morrow，2008; Many ,， 2008年），这些研究已被限制为STICATIC，STACTIC STICATIAN STACTIC Static Static Static Static Static Static Static Static Static Static Static Static Static Static Static Static Static。 拟议的项目旨在通过评估泰国的社区如何应对2011年洪水，以填补这些空白。 在2011年困扰泰国八个月以上的严重洪水是由热带风暴nock-ten引发的。湄公河和乔·菲拉河盆地沿线的雨水溢出导致严重的内陆洪水，影响了该国76个省份中的65个和超过1200万人。我们的项目研究了农村（Pathum Thani），郊区（Ayutthaya）和Urban（Bangkok）社区的能力差异，在如此长时间的洪水泛滥之后反弹。 Cutter等人提出的位置（Drop）模型的灾难（Drop）模型为指导。 （2008年），它使用县级空间数据（在美国）描述特定地理区域和跨政治边界的灾难弹性。美国研究团队和泰国合作者将使用半结构化访谈采访45-50个公共，私人和非营利组织的主要参与者。我们将记录最早的过程，程序和政策，以满足民众从短期恢复过渡到长期恢复的需求。将收集短暂的数据，以记录为农村，郊区和城市洪水受害者提供决定最初和/或改变决策的方式。这些数据将用于理解临时政策和流体治理机制，这些机制可能解释了社区弹性对跨司法管辖区和地理单位洪水的弹性的差异。返回美国后，将向泰国其他300个组织发送电子调查，以从更大的样本中收集信息。 这项研究通过，1）通过，1）帮助验证掉落模型并在国际环境中测试其适用性，2）增强或修改Drop模型中使用的指标，实时数据在受洪水影响社区的组织水平上收集到的实时数据，3）强调在社区中及时在社区中恢复的远程恢复，并强调在跨越的属性中，以便在跨越的属性中恢复，并在4个属性中恢复了4个，并且能够恢复4个，并允许4个属性，并且可以在4号范围内恢复，并在4这支持了世界各地的NSF和灾难学者的更广泛努力。该奖项由民用，机械和制造创新部以及国际科学与工程的全球风险投资基金会共同资助。