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Multi-model ensemble projection of mean and extreme streamflow of Brahmaputra River Basin under the impact of climate change
Author(s) -
Sarfaraz Alam,
Md. Mostafa Ali,
Ahmmed Zulfiqar Rahaman,
Zahidul Islam
Publication year - 2021
Publication title -
journal of water and climate change
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.421
H-Index - 22
eISSN - 2408-9354
pISSN - 2040-2244
DOI - 10.2166/wcc.2021.286
Subject(s) - streamflow , climate change , environmental science , precipitation , climatology , drainage basin , structural basin , water resources , multivariate statistics , mean radiant temperature , hydrology (agriculture) , geography , geology , meteorology , ecology , statistics , paleontology , oceanography , cartography , mathematics , geotechnical engineering , biology
The streamflow of Brahmaputra River Basin is vital for sustainable socioeconomic development of the Ganges delta. Frequent floods and droughts in the past decades indicate the susceptibility of the region to climate variability. Although there are multiple studies investigating the basin’s future water availability, most of those are based on limited climate change scenarios despite the wide range of uncertainties in different climate model projections. This study aims to provide a better estimation of projected future streamflow for a combination of 18 climate change scenarios. We develop a hydrologic model of the basin and simulate the future water availability based on these climate change scenarios. Our results show that the simulated mean annual, mean seasonal and annual maximum streamflow of the basin is expected to increase in future. By the end of the 21st century, the projected increase in mean annual, mean dry season, mean wet season, and annual maximum streamflow is about 25, 178, 11, and 22%, respectively. We also demonstrate that this projected streamflow can be expressed as a multivariate linear regression of projected changes in temperature and precipitation in the basin and would be very useful for policy makers to make informed decision regarding climate change adaptation.

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