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\title{Water Budget Estimation of the Ganges-Brahmaputra Basin Using Remote Sensing and Land Data Assimilation System Results Conclusions}



\author[1]{Zuhayr Shahid Ishmam}%
\author[2,3]{Robert V Rohli}%
\author[4]{Rubayet Bin Mostafiz}%
\author[3,4]{Carol J Friedland}%
\affil[1]{Affiliation not available}%
\affil[2]{Department of Oceanography \& Coastal Sciences, Louisiana State University}%
\affil[3]{Coastal Studies Institute, Louisiana State University}%
\affil[4]{Department of Biological \& Agricultural Engineering, LaHouse Research \& Education Center, LSU AgCenter, Louisiana State University}%


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  \date{May 21, 2024}


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\begin{abstract}
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).%
\end{abstract}%



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