High-resolution gridded streamflow for Ganges-Brahmaputra-Meghna (Bangladesh), 1951-2023
9-km daily gridded naturalized streamflow for the Ganges-Brahmaputra-Meghna basins over Bangladesh (1951-2023) generated with the VIC-RRM model, plus S2S-based forecast streamflow. Published with a 2025 Scientific Data paper and freely downloadable from Harvard Dataverse.
dataverse.harvard.edu
At a glance
- Region
- Bangladesh (Asia)
- Coverage
- Ganges-Brahmaputra-Meghna basins, Bangladesh
- Access
- Free
- Category
- Academic
- Last updated
- 2025
What's inside
- Streamflow
- Discharge
- Modeled hydrology
Terms explained
What you can do with it
Typical work that data of this type supports.
- 01
Design flows
Estimate 1-in-50 and 1-in-100 year floods for bridges, culverts and spillways.
Because it has: Streamflow
- 02
Low flows
Set environmental flows and check what is left in the river in a dry year.
- 03
Model calibration
Calibrate and test catchment models against observed flow.
Where AI adds value
Ideas for machine learning and AI agents built on this kind of data.
- 01
Flow forecasting
Train LSTM-style models on past records to forecast river levels and flow days ahead.
- 02
Ungauged basins
Combine with catchment data to estimate flow where there is no gauge.
- 03
Automatic QC
Flag gauge errors, shifts and gaps before they reach a report.
Related water data
- Bangladesh Flood Forecasting & Warning Centre (FFWC)Asia | Free
- Bangladesh Hydroinformatics and Flood Forecasting CircleAsia | Free
- Bangladesh Rivers (Watercourses) - HDXAsia | Free
- Bangladesh Waterbodies - HDXAsia | Free
- China Hydrology Data Project (Oberlin College)Asia | Free
- GUARDIAN / IIT Roorkee Hydrology Department Scientific Data RepositoryAsia | Free
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