Assessment of Social Vulnerability to Flood in Urban Côte d’Ivoire Using the MOVE Framework

Abstract

Abstract:Coupled with poor urban development, the increasing urban population of many Sub-Saharan African countries is subject to recurrent severe flooding episodes. In response to these flood events, while the focus is often put on slums and precarious urban settings, the social implications of these floods affect a variety of social classes. Presenting a case study of Cocody, a district of Abidjan, Côte d'Ivoire, known to have the country's highest number of flood-impacted people, this paper evaluates the social vulnerability of urban Côte d'Ivoire to flooding using the MOVE framework. The MOVE framework (Method for the Improvement of Vulnerability Assessment in Europe) has successfully been used in European contexts to assess social vulnerability of urban areas to geo-environmental disasters such floods. It helped assess the major factors involved in the social vulnerability to urban flooding and to have a good appreciation of the spatial distribution of areas that are vulnerable to urban flood. By taking this framework to the local context, relevant indicators were developed and GIS applications were used to assess spatially the relative social vulnerability of Cocody sub-districts to urban flooding. The results revealed that many sub-districts of Cocody are highly vulnerable to urban floods. Exposure and susceptibility are components that are found to have high influence on vulnerability to flood hazard in the district of Cocody. Their respective indicators need to be addressed properly in order to increase residents' resilience to urban flooding. The MOVE theoretical framework can be applied in Africa by contextualizing the vulnerability by using local indicators.

Comparison of Flood Vulnerability Assessments to Climate Change by Construction Frameworks for a Composite Indicator

“…To measure the three constituent components of the flood vulnerability indicator to climate change, the three proxy variables are selected for each assessment component as shown in Table 1 in the light of previous studies on flood vulnerability assessments [15][16][17]23,24]. The selection of the nine total proxy variables is based on the simplicity of data acquisition and construction, as well as the principles of measurability, representatives, and integrity.…”

“…This study divides all data by each maximum value for normalized scores in consideration of the functional relationship between variables and vulnerability. As previous studies computed the normalized values based on each variable's positive or negative contribution to vulnerability [18,24,25], the variable that has a positive elasticity to vulnerability is normalized by Equation (1) and the variable that has a negative elasticity to vulnerability is normalized by Equation (2) as follows:…”

Measuring Social Vulnerability to Flood Disasters in China

“…The Agency for Toxic Substances and Disease Registry, as well as the University of South Carolina, also designed a set of vulnerability assessment indicators from the demographic perspective. When it comes to social vulnerability to flood, Kablan et al [5] evaluates the social vulnerability to floods using the Method for the Improvement of Vulnerability Assessment in Europe (MOVE) framework. The MOVE framework helped assess the major factors involved in the social vulnerability to floods.…”

“…Catastrophic events have shown that countries or regions can face significantly different consequences while facing similar catastrophes, and a major reason is the different social vulnerability levels [4]. Assessing social vulnerability to flood is important because it can reveal the major contributing factors in flood disaster recovery [5]. It then can help establish appropriate defensive mechanisms and enhance the ability of flood disaster recovery.…”

A Framework for Disaster Vulnerability in a Small Island in the Southwest Pacific: A Case Study of Emae Island, Vanuatu

“…The MOVE framework has thus far been applied quantitatively using a range of socioeconomic and socioecological indicators for different hazards and settings (Depietri et al 2013;Welle et al 2014;Kablan et al 2017). Our adapted MOVE framework is applied qualitatively in a small island in the South Pacific.…”