Our research group is focused on improving the understanding and prediction of hydrologic fluxes at a range of space and time scales. Droughts, floods, urbanization, wildfires, climate variability and an escalating global population are creating scientific challenges on scales previously not encountered. Improving the understanding and prediction of a dynamic hydrologic cycle and its interface with a growing society is critical for addressing future water security and to reduce the detrimental impacts of land-cover change and natural hazards on watershed processes. Our work centers on the development and improvement of tools to better understand the mechanisms and improve the prediction of hydrologic processes, with a special focus on semi-arid regions. Specifically, our research involves: investigating catchment response to wildfire and urbanization, hydrologic and snow process modeling, remote-sensing of land surface properties, operational flood forecasting, and optimization methods for hydrologic models.