Inundation modelling for Bangladeshi coasts using downscaled and bias-corrected temperature

Author(s)
Hasan, Md Kamrul
Kumar, Lalit
Gopalakrishnan, Tharani
Publication Date
2020
Abstract
Coastal areas in Bangladesh are at severe risk of inundation by sea-level rise (SLR). Effective adaptation plan requires information about extent and level of projected inundation, which is yet to be localized for Bangladeshi coasts. We used downscaled and bias-corrected temperatures from 28 global climate models to predict SLR around Bangladesh. Based on the extended semi-empirical approach to SLR modelling, this study shows that by 2100, temperature will increase by 1.7 °C (RCP4.5) to 4.4 °C (RCP8.5) relative to 1986–2005 (25.89 °C) and corresponding sea-level will rise by 0.77 m (RCP4.5) to 1.15 m (RCP8.5). The sensitivity of SLR to temperature over 1980–2100 is 2.13 to 3.75 mm/year/°C. Consequently, 2098 km2 of Bangladesh is likely to be inundated under 1 m SLR, affecting the coast and river-banks with potential for significant indirect effects, including increased soil and water salinity and underground water contamination. This study provides modelled projection of SLR and inundation for the 21st century, and thus, it should provide useful information for adaptation planning and SLR preparedness in Bangladesh.
Citation
Climate Risk Management, v.27, p. 1-15
ISSN
2212-0963
Link
Publisher
Elsevier BV
Rights
Attribution-NonCommercial-NoDerivatives 4.0 International
Title
Inundation modelling for Bangladeshi coasts using downscaled and bias-corrected temperature
Type of document
Journal Article
Entity Type
Publication

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