My research group develops and applies systems methods to merge multi-scale field measurements and remotely sensed datasets with numerical models that simulate surface water and ground water flow processes and their interactions. Particular attention is given to predictions in poorly gauged and ungauged basins. Due to limited/non-existent ground-based observations at these locations, possibility of improved predictions highly depends on our ability to utilize systems methods and numerical models to advance physical process understanding. Diagnostic model evaluation, utilizing powerful techniques to extract process relevant information from the available observations, provides a meaningful approach to constrain structure/parameters of surface water and ground water flow models. My research group also focuses on integrating remotely sensed observations with predictive models. Satellite-based remote sensing products provide critical information in regard to physical characteristics (i.e. vegetation pattern, topography) as well as input (i.e. rainfall) and dynamic response characteristics (i.e. inundation maps) of the watersheds. Recent work in my research group expands in the broad area of potential impacts of global change, including climate and land surface variability, in water resources. Sustainable management of water resources necessitates an integrated strategy that harmonizes knowledge of watershed physical processes, modelling techniques, systems methods and their integration with newly available technology.