Models and remotely-sensed observations are essential tools in the study of the terrestrial water cycle while data assimilation allows to systematically merge those observations to yield an estimate superior to either alone. The collective use of these techniques helps bridge spatiotemporal scales as well as limitation gaps between observations and models. This session presents latest developments in hydrologic and land surface modeling, remote sensing, and data assimilation to better understand the spatial and temporal dynamics of the terrestrial water cycle and freshwater resources. We invite multi-scale, multi-variable, and multi-sensor studies that aim to assess spatiotemporal variability in water resources, improve errors and uncertainty estimation, and those that integrate models with observations across a range of spatial and temporal scales. A particular focus is given to ground-based, airborne, and space-based hydrology missions such as AirMOSS, AMSR2, AIRS/AMSU, ECOSTRESS GCOM-W, GPM, GRACE-FO, NISAR, MetOp, GPM, TOPEX, SMAP, SMOS, SnowEx, SWOT, CYGNSS, Copernicus-ESA.