Resolving Deep Critical Zone Architecture in Complex Volcanic Terrain

Abstract

Critical zone (CZ) structure, including the spatial distribution of minerals, elements, and fluid-filled pores, evolves on geologic time scales resulting from both top-down climatic forcing and bottom-up geologic controls. Climate and lithology may be imprinted in subsurface structure as depth-dependent trends in geophysical, geochemical, mineralogical, and biological datasets. As the weathering profile is as much (or more) a product of past environmental conditions, development of predictive models requires understanding the relative roles of climatic forcing and the geologic template on which CZ processes evolve. Doing so in complex volcanic terrains with high initial bedrock porosity and distinct depositional and hydrothermal alteration histories is particularly challenging. To resolve CZ structure in a rhyolitic catchment in the Valles Caldera National Preserve (NM, USA), this study combined geophysics, drilling, and laboratory analyses to produce depth-resolved porosity, geochemistry, and mineralogy datasets to >40 m in depth. Quantitative X-ray diffraction analysis showed that local mineral transformations control complex chemical enrichment/depletion (τ) patterns. Using linear discriminant analysis, key variables enabled separation of complex-layered geology into discrete zones. Contemporary, matrix-dominated weathering processes and modern hydrologic fluxes occur dominantly within the top 15 m of the weathering profile. This zone is convoluted by incomplete primary mineral weathering and overprinted by post-eruption weathering and metasomatism. Matrix weathering transitions to fracture surface weathering driven by deep percolation of slower moving, longer residence time meteoric waters at depth. By altering initial conditions and weathering trajectory, geologic legacy is a critical factor in how this subsurface landscape evolved and functions.

Hydrogeophysical Inversion of Time‐Lapse ERT Data to Determine Hillslope Subsurface Hydraulic Properties

“…The $$w(h)$$ relationship (Figure 3b) described a sandy loam texture representative of mountain field sites in southeastern Wyoming, USA (e.g., Carey & Paige, 2016; Carey et al., 2017; Fullhart et al., 2018, 2019; Kotikian et al., 2019; Ren et al., 2018, 2019). The assigned layer 2 $${d}_{\text{FE}}$$ value resulted in $${\theta }_{\mathrm{s}}$$ = 0.17, which is within the range of porosities expected for weathered bedrock in mountain environments across the USA (e.g., Flinchum et al., 2018; Graham et al., 1997; Klos et al., 2018; McGuffy, 2017; Moravec et al., 2020). The van Genuchten–Mualem hydraulic parameters were uniform within each model layer.…”

Vadose Zone Thickness Limits Pore‐Fluid Pressure Rise in a Large, Slow‐Moving Earthflow

“…Recent research shows that there are predictable, lithologically controlled bedrock weathering patterns across landscapes (Riebe et al., 2017). Considerable research efforts have been directed toward quantifying these patterns in recent years, particularly as part of the U.S.‐based, NSF‐funded Critical Zone Observatories program and its successor the Critical Zone Collaborative Network (e.g., Callahan et al., 2020; Flinchum et al., 2018; Hahm et al., 2019; Holbrook et al., 2014; Leone et al., 2020; Moravec et al., 2020. ; Pedrazas et al., 2021).…”

What Do P-Wave Velocities Tell Us About the Critical Zone?

“…Geophysical methods are a tool for exploring deep CZ structure at landscape (1,000s of m) and watershed (10s−100s of m) scales. Near-surface geophysical methods have variable resolution and depth penetration and have been successfully used to quantify lateral and vertical variability in CZ structure (Befus et al, 2011;Leopold et al, 2013;Orlando et al, 2016), estimate bedrock fracture density (Clarke and Burbank, 2011;Golebiowski et al, 2016;Novitsky et al, 2018), and estimate the depth to bedrock (Nyquist et al, 1996;Yaede et al, 2015;Flinchum et al, 2018b;Moravec et al, 2020). Given the diversity of near-surface geophysical methods (e.g., Parsekian et al, 2015), it is critical to select the appropriate geophysical tool to test a given scientific hypothesis.…”

“…et Olyphant et al, 2016;Callahan et al, 2020;Moravec et al, 2020). Seismic refraction uses elastic energy to produce 2D images of P-wave velocity on the order of 10s−100s of meters per deployment.…”