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The Critical Zone Processes Team will quantify processes and properties of the surface and near subsurface, which together embody the “Critical Zone” (or CZ), where water, rock, air and life meet in a dynamic interplay that generates soils, sustains ecosystems and shapes landscapes. The proposed work is closely aligned with growing national and international initiatives in CZ research and tackles issues of water sustainability in the US West and thus is well aligned with the goals of NSF’s Science, Engineering, and Education for Sustainability (SEES) portfolio.
We will use near-surface imaging techniques to build diversely faceted, data-rich pictures of CZ architecture and thus characterize the subsurface at the Medicine Bow and Laramie Range field sites. Our images will extend from the top of the canopy (using LiDAR) to the deepest reaches of water (using NMR) and fractured rock (using waveform tomographic inversions of seismic refraction data and cores for ground-truthing). To create these images, we will mesh diverse datasets in challenging, coupled inversions, pushing the science of CZ imaging and analysis a major step forward. Subsurface geophysical images will be supplemented and compared with targeted soil and rock cores collected from the same areas, and analyzed using instruments such as the Geotek Multi-Sensor Core Logger with the capacity to measure fractional porosity and other physical and chemical characteristics. We anticipate that ours will be one of the first (and perhaps most transformative) explorations of how resistivity, seismic velocity structure, density, magnetic susceptibility, water saturation and permeability can be woven into a single, coherent image of the subsurface weathering and water storage in a mountainous landscape. One byproduct of this image will be spatially distributed estimates of depth to the base of regolith, which we will compare with topographic indices and the distribution of biomass (from LiDAR) as a test of our hypothesis about connections between surface and subsurface processes.