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.
Following the Great Thailand Floods of 2011, researchers from University of North Texas traveled to three provinces within the flood inundation zone: Bangkok (urban), Pathum Thani (suburban), and Ayutthaya (rural). They found that public, private and nongovernmental organizations (NGOs) that provided short-term response in the rural province of Ayutthaya were more resilient than organizations in the suburban and urban provinces. Those organizations that provided resources and assistance to flood survivors and affected communities, on average, reported a higher level of organizational resiliency compared to those that did not. In addition, private companies and NGOs were generally more resilient than public sector organizations, highlighting the importance of gaining local support through grassroots organizations during disaster response. The team also examined the validity of using community resiliency indicators developed in the USA to different cultural and geographical settings in an international context i.e. Thailand. Using the Thai Census data and GIS they created an overall resiliency index for Thailand. This index suggests that the provinces with a greater percentage of residents living in municipal (urban) areas are generally more resilient than the rural areas. Additionally, spatial clustering showed that eleven provinces in the vicinity of Bangkok (the capital) had higher disaster resilience due to availability of resources, while rural areas in the Northwestern section of the country had the lowest levels of resiliency. However, this was contrary to results from the interviews and social networks analysis which suggest that organizations in the rural province demonstrated a greater degree of resilience to the flood than the more urban provinces. This suggests that an underlying sub-culture of disaster may not be well-reflected when macro-level studies using aggregated data at a provincial level are used. Oftentimes even though indicators of lower standard of living may suggest higher physical vulnerability and lower resilience to disaster, in areas that have integrated recurrent threats like floods as part of their normal life routines this may not be the case. While this study advances knowledge related to measuring community resiliency in an international context there is a need to explore the applicability of resilience models using pre and post disaster data across geographic units and scales to help policy makers, planners, emergency managers and civic society be better prepared against future threats. Through this study the team of researchers from the University of North Texas and Thammasat University (Thailand) provided insights on the short term recovery efforts in three flood impacted provinces using semi-structure interviews, social networks analysis, and spatial modeling. Their findings suggest the need to develop emergency preparedness and mitigation programs that are tailored to rural, suburban and urban settings to help facilitate the creation of disaster resilient communities. Such programs should underscore the importance of local neighborhood organizations, the private sector and the role of culture and religion in enhancing social networks.
