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Sea level rise induced impacts on coastal areas of Bangladesh and local-led community-based adaptation
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Resumo(s)
Bangladesh is as a low-lying country, susceptible to various Sea Level Rise (SLR) induced impacts.
Previous studies have separately explored SLR effects on Bangladesh’s coastal ecosystems and
livelihoods, across multiple spatial and temporal scales. However, empirical studies acknowl-
edging local population’s perceptions on the causal factors to different SLR induced physio-
graphic impacts, their effects at societal scale and ongoing adaptation to these impacts of SLR
have not been able to establish a causal-linkage relationship between these impacts and their
potential effects. Our study explores how SLR has already impacted the lives and livelihoods of
coastal communities in Bangladesh and how these have been responded by adopting different
adaptative measures. We applied a qualitative community-based multistage sampling procedure,
using two Participatory Rural Appraisal (PRA) tools, namely Focus Group Discussions (FGDs) and
Community Meetings (CM), to collect empirical data about SLR effects on livelihoods and
implemented adaptation responses. Our study found that both man-made and natural causes are
responsible for different physiographic impacts of SLR, and which seem to vary between place
and context. Five major SLR induced impacts were identified by coastal communities, namely:
salinity increase, rising water levels, land erosion, waterlogging and the emergence of char land.
Salinity increase and land erosion are the two most severe impacts of SLR resulting in the largest
economic losses to agriculture. Our results highlight how coastal communities in Bangladesh
perceive the impacts of SLR and the benefits of different adaptation processes set in motion to
protect them, via development projects and other local interventions.
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Citação
B. Roy, G.P. Penha-Lopes, M.S. Uddin, M.H. Kabir, T.C. Lourenço, A. Torrejano, Sea level rise induced impacts on coastal areas of Bangladesh and local-led community based adaptation, International Journal of Disaster Risk Reduction (2022), doi: https://doi.org/10.1016/ j.ijdrr.2022.102905.
Editora
Elsevier