Submitted to: Hydrology Research
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: September 26, 2011
Publication Date: July 7, 2012
Citation: Sandells, M., Flerchinger G.N., Gurney R., and Marks, D. 2012. Simulation of snow and soil water content as a basis for satellite retrievals. Hydrology Research. 43(5):720-735. Interpretive Summary: Monitoring of the water stored on the land surface as snow or soil water is crucial to optimise its use. Despite more than thirty years of data collection, using satellite-based remote sensing to estimate water equivalent of snow is not very accurate. A physically-based computer model of the snow and soil was developed to form the basis of a data assimilation system for retrieval of remotely-sensed snow mass and soil moisture. The influence of limited knowledge of the soil conditions at depth was investigated; limitations arising from limited knowledge of surface properties were discussed. In future applications, data retrievals of remotely-sensed snow mass and water equivalent can be assimilated into the computer model to update the model and improve model predictions of snow and soil water available on the land surface.
Technical Abstract: It is not yet possible to determine whether the snow has changed over time despite collection of passive microwave data for more than thirty years. Physically-based, but computationally simple snow and soil models have been coupled to form the basis of a data assimilation system for retrievals of snow mass and soil moisture from existing and future satellite observations. The model has been evaluated against observations of snow mass and soil temperature and moisture profiles from Reynolds Creek Experimental Watershed, Idaho. Simulation of snow mass was improved early in the season due to more realistic representation of soil heat flux, but led to an overestimation of snow mass later in the season. Soil temperatures were generally simulated well; freezing of the surface layers was not observed but was simulated, which affected soil water transport. Limited knowledge of the soil lower boundary conditions is acceptable for snow mass and surface soil moisture retrievals, although improvements are required for more accurate simulations of deeper soil moisture at this site. Development of a data assimilation framework to retrieve snow mass and near-surface soil moisture is discussed.