TY - JOUR
T1 - Impacts on river systems under 2 °C warming
T2 - Bangladesh Case Study
AU - Zaman, A.M.
AU - Molla, M.K.
AU - Pervin, I.A.
AU - Mahbubur Rahman, S.M.
AU - Haider, A.S.
AU - Ludwig, F.
AU - Franssen, W.
PY - 2017
Y1 - 2017
N2 - Bangladesh is particularly vulnerable due to the combined impacts of sea level rise, rainfall and runoff variability, and changes in cyclone patterns. This paper presents the application of an integrated modelling framework used to investigate climate change impacts when global averaged surface temperature increases by 2. C from pre-industrial level. The modelling framework consists of four model types: Regional climate model (RCM), Ganges-Brahmaputra-Meghna (GBM) Basin model, Southwest Region Hydrodynamic and Salinity models. Bias corrected climate results (temperature, precipitation and evapotranspiration) from SMHI-RCA and CNRM-ARPEGE RCMs for (Representative Concentration Pathway) RCP 8.5 scenario were used. The uniqueness of this research study was that the same GCM (General Circulation Model)/RCM results were used across the whole modelling chain. In Bagerhat District, it was found that river salinity can increase by about 0.5 to 2 PPT (parts per thousand). Also, the duration of river salinity above 1 PPT can double in some locations. In Kushtia District, in the months of November and December river flows may increase but not sufficiently in other months due to lack of connectivity to the Ganges River. In the flood-prone Shariatpur District, average wet season water level increases up to 0.2 to 0.5. m. Also, duration of flood levels above the established danger level can double in some locations. Finally, this study found that dredging of the mouth of the Gorai River (in Kushtia District) is an effective adaptation measure. The dredging ensures connectivity to the Ganges River, which allows freshwater to enter the Southwest region of Bangladesh, which not only alleviates drought conditions in Kushtia Distract but also helps push back saline intrusion.
AB - Bangladesh is particularly vulnerable due to the combined impacts of sea level rise, rainfall and runoff variability, and changes in cyclone patterns. This paper presents the application of an integrated modelling framework used to investigate climate change impacts when global averaged surface temperature increases by 2. C from pre-industrial level. The modelling framework consists of four model types: Regional climate model (RCM), Ganges-Brahmaputra-Meghna (GBM) Basin model, Southwest Region Hydrodynamic and Salinity models. Bias corrected climate results (temperature, precipitation and evapotranspiration) from SMHI-RCA and CNRM-ARPEGE RCMs for (Representative Concentration Pathway) RCP 8.5 scenario were used. The uniqueness of this research study was that the same GCM (General Circulation Model)/RCM results were used across the whole modelling chain. In Bagerhat District, it was found that river salinity can increase by about 0.5 to 2 PPT (parts per thousand). Also, the duration of river salinity above 1 PPT can double in some locations. In Kushtia District, in the months of November and December river flows may increase but not sufficiently in other months due to lack of connectivity to the Ganges River. In the flood-prone Shariatpur District, average wet season water level increases up to 0.2 to 0.5. m. Also, duration of flood levels above the established danger level can double in some locations. Finally, this study found that dredging of the mouth of the Gorai River (in Kushtia District) is an effective adaptation measure. The dredging ensures connectivity to the Ganges River, which allows freshwater to enter the Southwest region of Bangladesh, which not only alleviates drought conditions in Kushtia Distract but also helps push back saline intrusion.
KW - Bangladesh
KW - Basin model
KW - Climate change
KW - Hydrodynamic model
KW - Regional Climatic Model (RCM)
KW - Salinity intrusion
KW - Sea level rise
U2 - 10.1016/j.cliser.2016.10.002
DO - 10.1016/j.cliser.2016.10.002
M3 - Article
AN - SCOPUS:85005893660
SN - 2405-8807
VL - 7
SP - 96
EP - 114
JO - Climate Services
JF - Climate Services
ER -
