Extending the vadose zone: characterizing the role of snow for liquid water storage and transmission in streamflow generation

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For communities worldwide, valuable water resources originate from snow. Despite its importance, understanding of how meltwater moves and is stored within snow before it gets to streams and rivers is limited to knowledge gained from a few small-scale snow studies. There are pressing needs to better understand how these dynamics affect streamflow. Seasonal snow-cover is one of the fastest changing water resources under current climate trends with important yet uncertain implications on runoff production. While the concept of hydrologic connection between soils and streams has received attention, the liquid water storage and connectivity of flowpaths within a mountain snowpack at slope scales relevant to runoff generation are less understood. This is a major gap in knowledge of mountain streamflow production. Emerging capabilities in remote sensing technology, ground-based observations, and physically-based hydrologic modeling provide new opportunity to better understand snow water resources in headwater catchments. Specifically, improved understanding of the distribution of liquid water in a snowpack will transform the scientific community?s ability to monitor and predict the physical hydrological processes that occur during snowmelt. This project leverages state-of-the-science observation and numerical modeling techniques to understand the storage and transport of liquid water within a seasonal snowpack. Using newly developed in-snow liquid water mapping techniques, together with airborne-based snow depth mapping, we will track the storage and movement of meltwater across sloping terrain of a heavily monitored alpine watershed. A flexible hydrologic model will be used to assess our ability to simulate the observed processes. Results will improve scientific capabilities to: a) conceptualize and model snowmelt processes, b) understand the importance of the hydraulic properties of snow at the catchment scale, and c) constrain the potential hydrologic impacts of climate and land-cover change. In broader impacts, thos project will help students to understand fundamental concepts of hydrology and understand the various methods of study of hydrology such as modeling, field observations and remote sensing. The project will support one graduate and two undergraduate students who will be involved in numerical modeling and field work. The project will be carried out at the University of Colorado and Mountain research Stations. The project will in many diverse group of students who are first generation college students, students of color, veterans and rural students. The goal of this project is to characterize and constrain the physical mechanisms that control snowmelt delivery to streams in headwater basins. This project leverages new observation and modeling techniques to quantify and simulate the snow distribution, snowpack water holding capacity, snowmelt production, and dynamic in-snow flowpaths. This is achieved through state-of-the-science techniques including ground penetrating radar (GPR), instrumented unmanned aerial vehicles (UAVs), global positioning system (GPS) instrumentation, and a network of automated sensor nodes to intensively monitor soil moisture and snow depth, and a weir to monitor streamflow. Finally, hydrologic modeling will be conducted with the Structure for Unified Multiple Modeling Alternatives (SUMMA) model to assess the impact of modeling decisions and the ability to simulate snowmelt dynamics. The overarching research question of this project is: How do snowpack liquid water storage and through-snow hydrologic flowpaths affect hillslope-stream connectivity, and how do these processes evolve through the snowmelt season? This work will observe and simulate the spatially and temporally variable snowmelt season to complete the following project objectives: 1) Map the seasonal dynamics of catchment snow water equivalent (SWE) using UAV flights, GPR surveys, a network of sensor nodes, and manual observations. 2) Monitor the spatial and temporal progression of snowpack liquid water content and transport using combined UAV and GPR surveys, automated GPS signal attenuation, soil moisture sensors, and catchment streamflow response. 3) Evaluate the skill of hydrologic models to simulate the observed dynamics of the snowpack, soil, and streamflow response by systematically analyzing multiple model representations of hydrologic processes and scaling behavior. This research question will be investigated in a snow-dominated headwater catchment in the Rocky Mountains near Boulder, Colorado. Our work builds upon decades of local research in hydrology, biogeochemistry, and ecological processes. The Institute of Arctic and Alpine Research (INSTAAR) at the University of Colorado Boulder benefits from partnerships with the strong local scientific communities including LTER and CZO research.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.