Changes in flow and sediment load of poorly gauged Brahmaputra river basin under an extreme climate scenario
Author(s) -
Shammi Haque,
Md. Mostafa Ali,
A. K. M. Saiful Islam,
Md Jamal Uddin Khan
Publication year - 2020
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.2020.219
Subject(s) - sediment , monsoon , environmental science , hydrology (agriculture) , climate change , surface runoff , drainage basin , sedimentary budget , structural basin , sediment transport , routing (electronic design automation) , geology , climatology , oceanography , ecology , geography , geomorphology , geotechnical engineering , cartography , biology , computer network , computer science
Brahmaputra River Basin (BRB), the largest contributor of sediment load in Ganges–Brahmaputra–Meghna delta, is highly vulnerable to future climate change. Several studies assessed the effects of climate change of BRB on river flow but an assessment on sediment load has not been conducted. Changes in sediment load in the future need to be assessed to control and manage sediment flows in large catchments properly. The present study focuses on developing a hydrological and sediment routing model of BRB using the HEC-HMS model to estimate future sediment load together with the flow for the RCP 8.5 climate scenario. Modified Universal Soil Loss Equation and Engelund Hansen method of HEC-HMS have been applied for the sediment transport of BRB. The model has been calibrated using daily runoff for the period 1983–1996 and validated for the period 1997–2010, respectively. The uncertainty in the percentage change in seasonal sediment load during the pre-monsoon season is higher than that of the monsoon season. However, the contribution of the sediment load of pre-monsoon is very much lower than the monsoon season. The percentage changes in mean annual sediment load compared to the baseline period for the 2020s, 2050s and 2080s are 34, 67 and 115%, respectively.
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