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Projected changes in area of the Sundarban mangrove forest in Bangladesh due to SLR by 2100

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  • Andres Payo

    (University of Southampton)

  • Anirban Mukhopadhyay

    (Jadavpur University)

  • Sugata Hazra

    (Jadavpur University)

  • Tuhin Ghosh

    (Jadavpur University)

  • Subhajit Ghosh

    (Jadavpur University)

  • Sally Brown

    (University of Southampton
    Tyndall Centre for Climate Change Research)

  • Robert J. Nicholls

    (University of Southampton
    Tyndall Centre for Climate Change Research)

  • Lucy Bricheno

    (National Oceanography Centre)

  • Judith Wolf

    (National Oceanography Centre)

  • Susan Kay

    (Plymouth Marine Laboratory)

  • Attila N. Lázár

    (University of Southampton)

  • Anisul Haque

    (Bangladesh University of Engineering and Technology)

Abstract

The Sundarbans mangrove ecosystem, located in India and Bangladesh, is recognized as a global priority for biodiversity conservation and is an important provider of ecosystem services such as numerous goods and protection against storm surges. With global mean sea-level rise projected as up to 0.98 m or greater by 2100 relative to the baseline period (1985–2005), the Sundarbans – mean elevation presently approximately 2 m above mean sea-level – is under threat from inundation and subsequent wetland loss; however the magnitude of loss remains unclear. We used remote and field measurements, geographic information systems and simulation modelling to investigate the potential effects of three sea-level rise scenarios on the Sundarbans within coastal Bangladesh. We illustrate how the Sea Level Affecting Marshes Model (SLAMM) is able to reproduce the observed area losses for the period 2000–2010. Using this calibrated model and assuming that mean sea-level is a better proxy than the SLAMM assumed mean lower low water for Mangrove area delineation, the estimated mangrove area net losses (relative to year 2000) are 81–178 km2, 111–376 km2 and 583–1393 km2 for relative sea-level rise scenarios to 2100 of 0.46 m, 0.75 m and 1.48 m, respectively and net subsidence of ±2.5 mm/year. These area losses are very small (

Suggested Citation

  • Andres Payo & Anirban Mukhopadhyay & Sugata Hazra & Tuhin Ghosh & Subhajit Ghosh & Sally Brown & Robert J. Nicholls & Lucy Bricheno & Judith Wolf & Susan Kay & Attila N. Lázár & Anisul Haque, 2016. "Projected changes in area of the Sundarban mangrove forest in Bangladesh due to SLR by 2100," Climatic Change, Springer, vol. 139(2), pages 279-291, November.
    • Handle: RePEc:spr:climat:v:139:y:2016:i:2:d:10.1007_s10584-016-1769-z
    DOI: 10.1007/s10584-016-1769-z
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    Cited by:

    1. Ismail Mondal & SK Ariful Hossain & Jatisankar Bandyopadhyay & Hamad Ahmed Altuwaijri & Anirjita Das & Felix Jose & Nilanjan Saha & Mukhiddin Juliev, 2025. "Potential effects of projected global sea level rise on Sundarbans mangrove wetland ecosystem: insights from SLAMM and hybrid machine learning models," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 27(6), pages 14879-14912, June.
    2. Sahadev Sharma & Rempei Suwa & Raghab Ray & Mohammad Shamim Hasan Mandal, 2022. "Successive Cyclones Attacked the World’s Largest Mangrove Forest Located in the Bay of Bengal under Pandemic," Sustainability, MDPI, vol. 14(9), pages 1-13, April.
    3. Akbar Hossain Kanan & Francesco Pirotti & Mauro Masiero & Md Masudur Rahman, 2023. "Mapping inundation from sea level rise and its interaction with land cover in the Sundarbans mangrove forest," Climatic Change, Springer, vol. 176(8), pages 1-22, August.
    4. Sèna Donalde Dolorès Marguerite Deguenon & Castro Gbêmêmali Hounmenou & Richard Adade & Oscar Teka & Ismaila Imorou Toko & Denis Worlanyo Aheto & Brice Sinsin, 2023. "Simulation of the Impacts of Sea-Level Rise on Coastal Ecosystems in Benin Using a Combined Approach of Machine Learning and the Sea Level Affecting Marshes Model," Sustainability, MDPI, vol. 15(22), pages 1-17, November.
    5. Akbar Hossain Kanan & Carlo Giupponi, 2024. "Coastal Socio-Ecological Systems Adapting to Climate Change: A Global Overview," Sustainability, MDPI, vol. 16(22), pages 1-23, November.

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