The shallow and deep hypothesis suggests that stream concentration‐discharge (CQ) relationships are shaped by distinct source waters from different depths. Under this hypothesis, baseflows are typically dominated by groundwater and mostly reflect groundwater chemistry, whereas high flows are typically dominated by shallow soil water and mostly reflect soil water chemistry. Aspects of this hypothesis draw on applications like end member mixing analyses and hydrograph separation, yet direct data support for the hypothesis remains scarce. This work tests the shallow and deep hypothesis using co‐located measurements of soil water, groundwater, and streamwater chemistry at two intensively monitored sites, the W‐9 catchment at Sleepers River (Vermont, United States) and the Hafren catchment at Plynlimon (Wales). At both sites, depth profiles of subsurface water chemistry and stream CQ relationships for the 10 solutes analyzed are broadly consistent with the hypothesis. Solutes that are more abundant at depth (e.g., calcium) exhibit dilution patterns (concentration decreases with increasing discharge). Conversely, solutes enriched in shallow soils (e.g., nitrate) generally exhibit flushing patterns (concentration increases with increasing discharge). The hypothesis may hold broadly true for catchments that share such biogeochemical stratifications in the subsurface. Soil water and groundwater chemistries were estimated from high‐ and low‐flow stream chemistries with average relative errors ranging from 24% to 82%. This indicates that streams mirror subsurface waters: stream chemistry can be used to infer scarcely measured subsurface water chemistry, especially where there are distinct shallow and deep end members.

Rivers host a myriad of invisible chemical solutes that define the baseline quality of life-sustaining flowing waters. River chemistry reflects the response of Earth's Critical Zone, the zone from the tree top to the bottom of groundwater, to external climate forcing and human perturbations (Brantley et al., 2017). River water originates from precipitation, most of which infiltrates and flows via subsurface and river corridors (Figure 1). Along its journey, water mobilizes solutes by interacting with roots, microbes, soils, sediments, and rocks. As it eventually exits at river outlets, it carries the chemical signature of its interactions along its flow paths, and reflect the relative magnitude of biogeochemical reactions that produce solutes and export processes that transport solutes (Li et al., 2021).River chemistry is essential in regulating carbon-climate feedbacks, water quality, and aquatic ecosystem health. Solutes such as dissolved organic and inorganic carbon (DOC and DIC) and nutrients readily transform in rivers and emit greenhouse gases including CO 2 , N 2 O, and CH 4 (

The evasion of CO2 from inland waters, a major carbon source to the atmosphere, depends on dissolved inorganic carbon (DIC) concentrations. Our understanding of DIC dynamics across gradients of climate, geology, and vegetation conditions however have remained elusive. To understand its large‐scale patterns and drivers, we collated instantaneous and mean (multiyear average) DIC concentrations from about 100 rivers draining minimally‐impacted watersheds in the contiguous United States. Within individual sites, instantaneous concentrations (C) measured at daily to seasonal scales exhibit a near‐universal response to changes in river discharge (Q) in a negative power law form. High concentrations occur at low discharge when DIC‐enriched groundwater dominates river discharge; low concentrations occur under high flow when relatively DIC‐poor shallow soil water predominates river discharge. Such patterns echo the widely observed increase of soil CO2 and DIC with depth and the shallow‐and‐deep hypothesis that emphasizes the importance of flow paths and source water chemistry. Across sites, mean concentrations (Cm) decrease with increasing mean discharge (Qm), a long‐term climate measure, and reachs maxima at around 200 mm/yr. A parsimonious model reveals that high mean DIC arises from soil CO2 accumulation when rates of DIC‐generating reactions are relatively high compared to its export fluxes in arid climates. Although instantaneous and mean DIC concentrations similarly decrease with increasing discharge, results here highlight their distinct drivers: daily to seasonal‐scale instantaneous concentration variations (C) are controlled by subsurface CO2 distribution over depth (from below), whereas long‐term mean concentrations (Cm) are regulated by climate (from above). The results emphasize the significance of land‐river connectivity via subsurface flow paths. They also underscore the importance of characterizing subsurface CO2 distribution to illuminate belowground processes in order to project the future of water and carbon cycles in a warming climate.

Abstract. Watersheds are the fundamental Earth surface functioning units that connect the land to aquatic systems. Many watershed-scale models represent hydrological processes but not biogeochemical reactive transport processes. This has limited our capability to understand and predict solute export, water chemistry and quality, and Earth system response to changing climate and anthropogenic conditions. Here we present a recently developed BioRT-Flux-PIHM (BioRT hereafter) v1.0, a watershed-scale biogeochemical reactive transport model. The model augments the previously developed RT-Flux-PIHM that integrates land-surface interactions, surface hydrology, and abiotic geochemical reactions. It enables the simulation of (1) shallow and deep-water partitioning to represent surface runoff, shallow soil water, and deeper groundwater and of (2) biotic processes including plant uptake, soil respiration, and nutrient transformation. The reactive transport part of the code has been verified against the widely used reactive transport code CrunchTope. BioRT-Flux-PIHM v1.0 has recently been applied in multiple watersheds under diverse climate, vegetation, and geological conditions. This paper briefly introduces the governing equations and model structure with a focus on new aspects of the model. It also showcases one hydrology example that simulates shallow and deep-water interactions and two biogeochemical examples relevant to nitrate and dissolved organic carbon (DOC). These examples are illustrated in two simulation modes of complexity. One is the spatially lumped mode (i.e., two land cells connected by one river segment) that focuses on processes and average behavior of a watershed. Another is the spatially distributed mode (i.e., hundreds of cells) that includes details of topography, land cover, and soil properties. Whereas the spatially lumped mode represents averaged properties and processes and temporal variations, the spatially distributed mode can be used to understand the impacts of spatial structure and identify hot spots of biogeochemical reactions. The model can be used to mechanistically understand coupled hydrological and biogeochemical processes under gradients of climate, vegetation, geology, and land use conditions.

Understanding and predicting catchment responses to a regional disturbance is difficult because catchments are spatially heterogeneous systems that exhibit unique moderating characteristics. Changes in precipitation composition in the Northeastern U.S. is one prominent example, where reduction in wet and dry deposition is hypothesized to have caused increased dissolved organic carbon (DOC) export from many northern hemisphere forested catchments; however, findings from different locations contradict each other. Using shifts in acid deposition as a test case, we illustrate an iterative “process and pattern” approach to investigate the role of catchment characteristics in modulating the steam DOC response. We use a novel dataset that integrates regional and catchment-scale atmospheric deposition data, catchment characteristics and co-located stream Q and stream chemistry data. We use these data to investigate opportunities and limitations of a pattern-to-process approach where we explore regional patterns of reduced acid deposition, catchment characteristics and stream DOC response and specific soil processes at select locations. For pattern investigation, we quantify long-term trends of flow-adjusted DOC concentrations in stream water, along with wet deposition trends in sulfate, for USGS headwater catchments using Seasonal Kendall tests and then compare trend results to catchment attributes. Our investigation of climatic, topographic, and hydrologic catchment attributes vs. directionality of DOC trends suggests soil depth and catchment connectivity as possible modulating factors for DOC concentrations. This informed our process-to-pattern investigation, in which we experimentally simulated increased and decreased acid deposition on soil cores from catchments of contrasting long-term DOC response [Sleepers River Research Watershed (SRRW) for long-term increases in DOC and the Susquehanna Shale Hills Critical Zone Observatory (SSHCZO) for long-term decreases in DOC]. SRRW soils generally released more DOC than SSHCZO soils and losses into recovery solutions were higher. Scanning electron microscope imaging indicates a significant DOC contribution from destabilizing soil aggregates mostly from hydrologically disconnected landscape positions. Results from this work illustrate the value of an iterative process and pattern approach to understand catchment-scale response to regional disturbance and suggest opportunities for further investigations.