Satellite-derived Water Storage
Characterizing the amount of available freshwater is of paramount importance to freshwater resource management. Recent advances in satellite-based remote sensing enable the measurement of the anomalies in the Earth's gravitational field. These measurements can be used to better quantify the amount (or mass) of water stored as snow, ice, lakes, soil moisture, and groundwater.
Downwelling shortwave (SW) and longwave (LW) radiation are the dominant energetic inputs to the land surface. Our research involves the use of geostationary and polar-orbiting satellite platforms to characterize the keys modes of variability in the land surface energy forcing, which drives much of the variability in the latent heat and sensible heat fluxes eminating from the terrestrial environment.
Passive Microwave Prediction
More than one billion people globally are dependent on freshwater runoff that originates as snow and ice. Space-based measurements of microwave radiation emitted from snowpack provide an important information source that can be used to improve our knowledge of the mass of snow within a snowpack, and hence improve our understanding of available freshwater resources.
Hydrologic Data Assimilation
Data assimilation is a general technique where model estimates are merged with measurements to ultimately yield an estimate that is superior to the model or measurements alone. In the context of hydrology, this technique can be applied to satellite-derived estimates of soil moisture, water surface elevation, vegetation growth, snow depth, and groundwater storage.
Machine Learning Applications
Artificial intelligence applications, including neural networks and support vector machines, provide unique capabilities in the prediction of nonlinear processes. The skill and efficiency of these predictions enhance our knowledge of hydrologic processes operating at regional and continental scales. Examples include the prediction of satellite-based measurements related to snow and soil moisture state estimation.
High Performance Computing
Application and development of advanced computer models utilizing satellite-derived measurements requires advanced computing techniques such as parallel processing and "big data" storage. The massively parallel Deepthought supercomputer at UMD employs >3000 CPUs and provides the computing power necessary to study hydrologic processes operating at continental and global scales.