Projected changes in area of the Sundarban mangrove forest in Bangladesh due to SLR by 2100
|Title||Projected changes in area of the Sundarban mangrove forest in Bangladesh due to SLR by 2100|
|Publication Type||Journal Article|
|Year of Publication||2016|
|Authors||Payo, A, Mukhopadhyay, A, Hazra, S, Ghosh, T, Ghosh, S, Brown, S, Nicholls, RJ)[, Bricheno, L, Wolf, J, Kay, S|
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 km(2), 111-376 km(2) and 583-1393 km(2) 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 (< 10 % of present day area) and significantly smaller than previous research has suggested. Our simulations also suggest that erosion rather than inundation may remain the dominant loss driver to 2100 under certain scenarios of sea-level rise and net subsidence. Only under the highest scenarios does inundation due to sea-level rise become the dominant loss process.