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Water Budget Estimation of the Ganges-Brahmaputra Basin Using Remote Sensing and Land Data Assimilation System Results Conclusions
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  • Zuhayr Shahid Ishmam,
  • Robert V Rohli,
  • Rubayet Bin Mostafiz,
  • Carol J Friedland
Zuhayr Shahid Ishmam

Corresponding Author:[email protected]

Author Profile
Robert V Rohli
Coastal Studies Institute, Louisiana State University, Department of Oceanography & Coastal Sciences, Louisiana State University
Rubayet Bin Mostafiz
Department of Biological & Agricultural Engineering, LaHouse Research & Education Center, LSU AgCenter, Louisiana State University
Carol J Friedland
Department of Biological & Agricultural Engineering, LaHouse Research & Education Center, LSU AgCenter, Louisiana State University, Coastal Studies Institute, Louisiana State University


Monitoring the various water cycle components are instrumental in ecological preservation, disaster preparedness, and achieving sustainable water resource management. Remote sensing observations, along with Land Data Assimilation System-derived information, can aid in investigating individual components and processes within the water cycle to characterize spatiotemporal patterns in the change in water availability in large river basins. The Ganges- Brahmaputra, one of the world's largest and most densely populated river basins, covering parts of India, Bangladesh, Nepal, Bhutan, and China, yet poorly gauged for water monitoring, is the area of interest for this case study focusing on estimates of precipitation, evapotranspiration, change in terrestrial water storage, and storm surface runoff from satellite-based NASA GPM (IMERG), NASA MODIS, and NASA GRACE/GRACE FO observations, and GLDAS Catchment Land Surface Model simulations. Data on each water cycle component was analyzed to approximate the total water budget on a sub-basin level. Intra-annual (wet and dry seasons) and inter-annual variability were also quantified for the years 2004-2005, 2009-2010, 2014-2015, and 2019-2020 for the entire Ganges-Brahmaputra basin. Variation in the water budgets, as estimated in billions of cubic meters (BCM) over the analyzed time period, indicates the extent of water stress, drought severity, and flood occurrence in this study area where annual rainfall patterns are predominantly governed by the wet season (i.e., monsoon). The uncertainty of the estimates leading to the inability to close the water balance equation is possibly due to the limitations in satellite observations/model simulations and human activities (e.g., stream flow, irrigation, groundwater pumping, diversion).
04 Mar 2024Submitted to ESS Open Archive
05 Mar 2024Published in ESS Open Archive