Geochemical evolution of the Critical Zone across variable time scales informs concentration‐discharge relationships: Jemez River Basin Critical Zone Observatory

Abstract

This study investigates the influence of water, carbon, and energy fluxes on solute production and transport through the Jemez Critical Zone (CZ) and impacts on C‐Q relationships over variable spatial and temporal scales. Chemical depletion‐enrichment profiles of soils, combined with regolith thickness and groundwater data indicate the importance to stream hydrochemistry of incongruent dissolution of silicate minerals during deep bedrock weathering, which is primarily limited by water fluxes, in this highly fractured, young volcanic terrain. Under high flow conditions (e.g., spring snowmelt), wetting of soil and regolith surfaces and presence of organic acids promote mineral dissolution and provide a constant supply of base cations, Si, and DIC to soil water and groundwater. Mixing of waters from different hydrochemical reservoirs in the near stream environment during “wet” periods leads to the chemostatic behavior of DIC, base cations, and Si in stream flow. Metals transported by organic matter complexation (i.e., Ge, Al) and/or colloids (i.e., Al) during periods of soil saturation and lateral connectivity to the stream display a positive relationship with Q. Variable Si‐Q relationships, under all but the highest flow conditions, can be explained by nonconservative transport and precipitation of clay minerals, which influences long versus short‐term Si weathering fluxes. By combining measurements of the CZ obtained across different spatial and temporal scales, we were able to constrain weathering processes in different hydrological reservoirs that may be flushed to the stream during hydrologic events, thereby informing C‐Q relationships.

Distinct Source Water Chemistry Shapes Contrasting Concentration‐Discharge Patterns

“…Trostle et al () indicated that DOC complexation and colloidal transport influenced C‐Q of trace metals (e.g., Cu, Mn, and Ti) in Marshall Gulch watershed. McIntosh et al () also attributed the positive C‐Q relationships of Ge, Al, and Mn to DOC complexation in the La Jara catchment.…”

“…In the seasonally snow-covered Loch Vale watershed (CO), 4 years of stream chemistry data shows that organic complexation was likely responsible for the spring flush of trace metals and rare earth elements (e.g., Se and La;Shiller, 2010) Trostle et al (2016). indicated that DOC complexation and colloidal transport influenced C-Q of trace metals (e.g., Cu, Mn, and Ti) in Marshall Gulch watershed McIntosh et al (2017). also attributed the positive C-Q relationships of Ge, Al, and Mn to DOC complexation in the La Jara catchment.…”

Concentration‐Discharge Relations in the Critical Zone: Implications for Resolving Critical Zone Structure, Function, and Evolution

“…Several papers highlight the fact that processes controlling solute chemistry are not evident from stream chemistry and runoff analysis alone and that “opening the black box” of catchment internal CZ structure is essential to interpreting such data sets. For example, C‐Q data were interpreted in light of CZ weathering profiles to reveal the important role of clay mineral formation along deep subsurface flow paths in controlling catchment Si effluxes from weathering rhyolite (McIntosh et al, ). Similarly, time series data on groundwater chemistry showed that cation exchange reactions during water percolation into a deeply weathered argillite was superimposed with long‐residence time groundwater gave rise to chemostatic C‐Q relations (Kim et al, ).…”

Leveraging Environmental Research and Observation Networks to Advance Soil Carbon Science

“…This is an area where CZO data have contributed new insights into SOM erosion and deposition (Dialynas et al, 2016;Stacy et al, 2015) and land-water connectivity (Andrews et al, 2011). CZO research integrates across wide temporal scales, from hydrologic responses in seconds to years versus soil weathering and landscape evolution over millennia (Heidari et al, 2017;McIntosh et al, 2017;Riebe et al, 2017). Improved characterization of weathering and erosion rates and associated soil and water residence times can be used to help benchmark rates of change observed in SOM models.…”