Work

Urban flood resilience of the coastal city of Mumbai: Frameworks and community-based mitigation strategies for long-term sustainability

Year: 2026
Type: article
Study design: Observational Study
Abstract: Mumbai, a millennium-old city situated on the west coast of India faces multifaceted challenges related to climate change. In the past two decades, annual flood events have become more frequent and severe in Mumbai, which in turn affects the livelihood strategies of the urban inhabitants during the monsoon months. This study has been objectively conducted to assess the urban flood resilience using both qualitative and quantitative data. The resilience of households is measured using 263 households. The subjective well-being technique is used to measure the resilience components of households. Factor analysis (using PCA) and the Likert scale have been used to identify resilience factors. It employs interviews, field study and focus group discussions (FGDs) to evaluate flood resilience in both urban and suburban districts. The study also examines policies, disaster management plans, committee recommendations, and legislative measures pertinent to the concept of resilience. The survey shows that households in Greater Mumbai are generally unhappy with the institutional help they receive, especially when it comes to insufficient flood warnings, subpar drainage infrastructure, and ineffective rehabilitation efforts. Based on factor analysis, the four main components of resilience—financial recovery ability, livelihood adaptation, institutional provisions, and mobility during floods-collectively account for 62.61% of the variance. Case studies illustrate the impact on livelihoods, limited access to healthcare, and extended displacements, particularly affecting low-income households in Dharavi, Bandra, and Chembur. This situation emphasizes the critical necessity for cohesive structural and non-structural flood management approaches. This underscores the imperative necessity for implementing LID-BMP techniques.
Language: English
Open Access status: hybrid
Estimated APC paid: $1,500
OpenAlex ID: W7155651061
FWCI:
Cites: 36
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