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).
The European Centre for Medium Range Weather Forecast (ECMWF)  fifth-generation reanalysis of the global climate (ERA5) and the Climate Hazards Croup InfraRed Precipitation with Station (CHIPPS) daily measurements are used to examine extreme rainfall (1981-2022) in the contiguous U.S.A. Linear spatiotemporal trends in indicators of extreme rainfall frequency, magnitude, and duration recommended by WMO, as identified by the TheiI-Sen slope estimate and its Mann Kendall significance (p < 0.05), are calculated. Temporal trends in the annual number of days with rainfall 20 mm (R20) are most significant in the Ohio Valley and in parts of Florida (increasing), and isolated parts of Texas, Oklahoma, elsewhere in the Southwest and West (decreasing). Annual frequency of days having 10 mm (R1O) shows similar spatiotemporal patterns, but with broader areas of decreasing trends in the southern Great Plains and Southwest. Annual trends in total rainfall on the 5% of the most precipitating days (R95P) increased significantly in parts of Florida and from Louisiana to Maine and decreased significantly across much of the Southwest. Annual trends in maximum five-day rainfall (Rx5day) increased significantly in parts of the Appalachians and other isolated pockets and decreased significantly in parts of the Southwest. Annual maximum number of consecutive dry days (CDD) increased significantly in parts of California and adjacent western U.S. and decreased significantly in much of the south-central U.S. Trends in annual maximum number of consecutive wet days (CWD) changed significantly only in isolated areas, with Colorado having the most significantly decreasing trends. The area having >2.5 mm day-1 of rainfall over a given meteorological season expanded for DJF and MAM but shrunk for SON, from the 1981-1990 to 2011-2022 periods. If such trends continue, floods, landslides, and droughts may intensify.