Community flood resilience assessment of Saadi neighborhood, Shiraz, Iran

Abstract

Flash floods have recently become a recurrent phenomenon with devastating impacts on different cities, particularly vulnerable communities in Iran. Community resilience is a relatively recent approach to resilience, increasingly used in the natural hazards and climate change literature. This study aims to assess the community resilience of a flood-prone district, the Saadi neighborhood, in Shiraz, Iran. Based on an extensive literature review, an indicator-based framework was outlined to measure community resilience to flash floods using five dimensions: social, community capital, economic, institutional, and infrastructural and housing resilience. The primary data on community flood resilience assessment was collected through a survey using questionnaires. Using simple random sampling, 374 individuals from the residents of the study area were selected. The data were ranked and analyzed through qualification methods, descriptive statistics and expert panel weighting system. The overall composite community resilience and the community resilience indices’ scores were .56 out of 1 for the selected community, indicating a moderate level of resilience. The findings showed that institutional and infrastructure/housing conditions had a limited impact on community resilience. However, social trust and community capital were crucial for aiding the community’s rapid recovery from a flood disaster and preparing for future floods. Policymakers and resilience planners, thus, should focus on the lessons that can be learnt from the past floods, particularly in terms of infrastructure and institutional resilience, as these have a significant impact on the overall resilience of local communities.

Keywords:

• Resilience assessment
• frontline communities
• flash flood
• learning capacity
• Shiraz

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

1 Data accessibility and applicability are two main filters for choosing indicators since many indicators that are commonly used in developed countries may not be accessible or applicable in the global south, including Iran, due to a lack of data availability. For example, formal census centers in Iran may not produce certain indicators. Additionally, some indicators such as social security, which are applicable in some countries, may not be relevant for Iranian people as the government provides basic social security coverage for all citizens.

2 Provincial headquarters of Urban Regeneration Corporation of Fars Province.

3 We used an online calculation website to compute sample size. The Cochran’s formula was $n=\frac{\frac{z^2\mathit{\text{pq}}}{d^2}}{1+\frac{1}{N}\left[\frac{z^2\mathit{\text{pq}}}{d^2}-1\right]}$