Dynamics of Urban Disaster Risk Paradigm: Looking Through the Perceived Lens of the Residents of Informal Settlements in Khulna City, Bangladesh

Abstract

The integration of sustainability principles into disaster management research suggests a shift from traditional expert-driven assessment to a more community-driven process. However, most studies have focused on a generalized and regional assessment of perceived risk. Only a few of them have focused on informal settlements which belong to the most vulnerable communities facing the compound impacts of multiple disasters in urban areas. This raises concerns over the generalization of existing findings as informal settlements may add to spatial heterogeneity in disaster risk assessment. In order to contribute to this knowledge gap, we have surveyed 1,122 households of 93 slums of Khulna city in Bangladesh. We have investigated informal settlers’ perceptions of local and citywide hazard risks and their vulnerabilities from natural and anthropogenic hazards. It is found that low-income households are more concerned about the day-to-day inconvenience (e.g., waterlogging) rather than extreme weather events (e.g., cyclone and storm surge). This is mainly due to the degraded local environment and poor built form of their living places. The mapping of survey responses displays a spatial segregation of perceived disaster risk. The study highlights the importance of adopting spatial and risk-specific disaster preparedness policies and interventions. The results of the study would also be useful for tailoring appropriate disaster management policies to improve community resilience for poverty-stricken areas in developing countries.

Measuring urban expansion pattern using spatial matrices in Khulna City, Bangladesh

“…Khulna district is a disaster-prone region. Residents of the city's outskirts face cyclone and flood every year [ 42 ]. The Rupsa and Vairab rivers formed the boundary of Khulna city.…”

Bangladesh's vulnerability to cyclonic coastal flooding

“…Vulnerability is also stressed by intensive, potentially hazardous and poorly paid working conditions, especially for women (Ito, 2002;Paul and Vogl, 2011). Nonetheless, specific populations such as the ones living in slums or Rohingya refugees are underrepresented in our study Swapan et al, 2020). In the same way, it should be noted that there are a lot of new proxies in social, environmental and economic datasets (social networks, mobile phones and satellites) that would allow for the estimation of the SSVI over finer geographical resolution to better represent the cyclone flooding vulnerability.…”

“…Compared to recent studies on vulnerability assessment, our approach differs in several aspects. First, our study is intended to be general in scope, considering the entire population and territories affected by the cyclonic flooding, in contrast to studies that target either a category of the population Swapan et al, 2020) or a particular site, at the village scale, for example in . These highly localized studies have the advantage of being more detailed and enriched with qualitative observations on the perception and representation of natural hazards, although A.…”

Assessing Urban Poor Resilience to Natural Disasters Using Analytic Hierarchy Process-Based Model: A Case Study on Khulna City

“…It is always frequented by climatic hazards due to its low elevation (Haque et al, 2014) and the flat land of the city is approximately 2.5 meters above the mean sea level (Linkon & Khan, 2019). Khulna city is particularly at climate risk due to several reasons including a higher level of population density; increasing number of populations living in the urban informal settlements; spontaneous spatial growth that created natural drainage disruption; and sporadic development of urban slums particularly at risky sites (Haque et al, 2014;Pelling, 2003;Swapan et al, 2020aSwapan et al, , 2020b. All urban residents are not vulnerable equally to climate change and climate extremes and climate change-induced shocks will disproportionately affect urban poor (Pelling, 2003;Jabeen et al, 2010;Satterthwaite et al, 2007).…”