Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/30002
Title: Geospatial modelling of the inundation levels in the Sundarbans mangrove forests due to the impact of sea level rise and identification of affected species and regions
Contributor(s): Ghosh, Manoj Kumer (author); Kumar, Lalit  (author)orcid ; Kibet Langat, Philip  (author)
Publication Date: 2019-02-11
Open Access: Yes
DOI: 10.1080/19475705.2018.1564373
Handle Link: https://hdl.handle.net/1959.11/30002
Abstract: This research reveals the magnitude of mangrove area loss and future impacts on mangrove species composition and distribution due to rise in Mean Sea Level (MSL). In this study, a geospatial model of potentially inundated areas was developed using Digital Elevation Model (DEM) data to assess the potential impacts of sea level rise (SLR) on the spatial distribution of mangrove species and estimate the potential inundation and subsequent mangrove area loss. The mangrove areas of 2646 ha, 9599 ha and 74,720 ha are projected to be inundated and subsequently lost by the end of the twenty first century for the low, medium and high SLR scenarios respectively under the net subsidence rate −2.4 mm/year relative to the baseline year 2000. All the major five mangrove species of the Bangladesh Sundarbans will be affected and this can potentially contribute to a change in the present species composition and biodiversity of the forest. Results suggest that, under the extreme scenario, inundation and subsequent loss of different mangrove species will be substantial and this can bring a massive change in the species composition and their spatial distribution in the Bangladesh Sundarbans.
Publication Type: Journal Article
Source of Publication: Geomatics, Natural Hazards and Risk, 10(1), p. 1028-1046
Publisher: Taylor & Francis
Place of Publication: United Kingdom
ISSN: 1947-5713
1947-5705
Fields of Research (FoR) 2008: 040104 Climate Change Processes
050101 Ecological Impacts of Climate Change
Fields of Research (FoR) 2020: 370201 Climate change processes
410102 Ecological impacts of climate change and ecological adaptation
Socio-Economic Objective (SEO) 2008: 960305 Ecosystem Adaptation to Climate Change
Socio-Economic Objective (SEO) 2020: 190102 Ecosystem adaptation to climate change
Peer Reviewed: Yes
HERDC Category Description: C1 Refereed Article in a Scholarly Journal
Appears in Collections:Journal Article
School of Environmental and Rural Science

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