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Abstract Riverine dissolved silicon (DSi) dynamics reflect integrated geologic, hydrologic, climatic, and ecological controls. We compiled annual DSi data for 337 rivers across four continents and trained interpretable machine‐learning models to predict concentrations and yields from 28 watershed variables. Both models reproduced testing data (R² = 0.85 for concentration and 0.96 for yield) and withheld‐site validation (R² = 0.91 and 0.93). Lithology, especially volcanic rock fraction, strongly controlled DSi while subsurface storage, topography, and land cover further shaped DSi dynamics. DSi concentrations and yields exhibited nonlinear responses to basin slope, recession‐curve slope, proportion of open‐water cover, and nutrient availability. Concentrations showed sharper threshold responses to hydrologic and biotic variables, whereas yields varied more gradually with climate and lithology. These results provide a framework for forecasting DSi under land cover and climate change and for embedding realistic, nonlinear processes in mechanistic models. 

Abstract Riverine silicon (Si) plays a vital role in governing primary production, water quality, and carbon cycling. Climate and land cover change have altered how dissolved Si (DSi) is processed on land, transported to rivers, and cycled through aquatic ecosystems. The Global Aggregation of Stream Silica (GlASS) database was constructed to assess changes in river Si concentrations and fluxes, their relationship to other nutrients (nitrogen (N) and phosphorus (P)), and to evaluate mechanisms driving the availability of Si. GlASS includes concentrations of DSi, dissolved inorganic N (NO₃, NO_x, and NH₄), and dissolved inorganic P (as soluble reactive P or PO₄-P) at daily to quarterly time steps from 1963 to 2024; daily discharge; and watershed characteristics for 421 rivers spanning eight climate zones. Original data sources are cited, data quality assurance workflows are public, and input files to a common load model are provided. GlASS offers critical data to address questions about patterns, controls, and trajectories of global river Si biogeochemistry and stoichiometry. 

ABSTRACT Dynamic water storage is the water that remains for enough time in watersheds to influence streamflow generation, chemically weather rock and drive the release of solutes, breakdown organic carbon (C) through microbial activity, and sustain vegetation between periods of precipitation. The amount and connectivity of dynamic water stores control critical zone processes, including evapotranspiration, vegetation productivity and mortality, streamflow, weathering and solute transport. Here, we present recent advances and identify frontiers in the study of dynamic water storage in the critical zone, focusing on observational techniques for quantifying dynamic storage, advances in conceptual and numerical models that capture dynamic storage, and emerging hypotheses that drive dynamic storage evolution. We specifically identify and focus on four primary dynamic water storages: snow, plant‐accessible water, groundwater, and surface water. While we use semi‐arid mountain environments as an exemplar of dynamic storage controls on critical zone processes, this work offers implications for a broad range of geoclimatic settings. 

Abstract Preferential flow (PF) in soil causes the rapid transport of water, nutrients, and contaminants into the subsurface, influencing groundwater recharge and streamflow. Data scarcity has hindered the quantification of PF occurrence and the identification of its drivers across diverse ecoregions. We address this gap by analyzing high‐frequency, multi‐depth soil moisture data across 17 ecoregions in the USA, using ∼1,500 sensors at 40 sites. We discovered that PF is widespread, with sites experiencing PF in up to 60% of rainfall events ≥2 mm. Multiple approaches consistently show that PF is more likely to occur with increased peak rainfall intensity, finer textured material, low soil moisture variability, humid climate, and higher net primary productivity. This suggests that PF patterns could shift with projected climate changes, increasing uncertainty in predictions of groundwater recharge, water quality, and streamflow generation. 

Abstract Critical Zone (CZ) scientists have advanced understanding of Earth's surface through process‐based research that quantifies water, energy, and mass fluxes in predominantly undisturbed systems. However, the CZ is being increasingly altered by humans through climate and land use change. Expanding the scope of CZ science to include both human‐ and non‐human controls on the CZ is important for understanding anthropogenic impacts to Earth's surface processes and ecosystem services. Here, we share perspectives from predominantly U.S.‐based, early career CZ scientists centered around broadening the scope of CZ science to focus on societally relevant science through a transdisciplinary science framework. We call for increased training on transdisciplinary methods and collaboration opportunities across disciplines and with stakeholders to foster a scientific community that values transdisciplinary science alongside physical science. Here, we build on existing transdisciplinary research frameworks by highlighting the need for institutional support to include and educate graduate students throughout the research processes. We also call for graduate‐student‐led initiatives to increase their own exposure to transdisciplinary science through activities such as transdisciplinary‐focused seminars and symposiums, volunteering with local conservation groups, and participating in internships outside academia. 

ABSTRACT The importance of subsurface water dynamics, such as water storage and flow partitioning, is well recognised. Yet, our understanding of their drivers and links to streamflow generation has remained elusive, especially in small headwater streams that are often data‐limited but crucial for downstream water quantity and quality. Large‐scale analyses have focused on streamflow characteristics across rivers with varying drainage areas, often overlooking the subsurface water dynamics that shape streamflow behaviour. Here we ask the question:What are the climate and landscape characteristics that regulate subsurface dynamic storage, flow path partitioning, and dynamics of streamflow generation in headwater streams?To answer this question, we used streamflow data and a widely‐used hydrological model (HBV) for 15 headwater catchments across the contiguous United States. Results show that climate characteristics such as aridity and precipitation phase (snow or rain) and land attributes such as topography and soil texture are key drivers of streamflow generation dynamics. In particular, steeper slopes generally promoted more streamflow, regardless of aridity. Streams in flat, rainy sites (< 30% precipitation as snow) with finer soils exhibited flashier regimes than those in snowy sites (> 30% precipitation as snow) or sites with coarse soils and deeper flow paths. In snowy sites, less weathered, thinner soils promoted shallower flow paths such that discharge was more sensitive to changes in storage, but snow dampened streamflow flashiness overall. Results here indicate that land characteristics such as steepness and soil texture modify subsurface water storage and shallow and deep flow partitioning, ultimately regulating streamflow response to climate forcing. As climate change increases uncertainty in water availability, understanding the interacting climate and landscape features that regulate streamflow will be essential to predict hydrological shifts in headwater catchments and improve water resources management. 

Abstract Root distributions are typically based on root mass per soil volume. This plant‐focused approach masks the biogeochemical influence of fine roots, which weigh little. We assert that centimeter‐scale root presence‐absence data from soil profiles provide a more soil‐focused approach for probing depth distributions of root‐regolith interfaces, where microsite‐scale processes drive whole‐ecosystem functioning. In 75 soil pits across the continental USA, Puerto Rico, and the Alps, we quantified fine and coarse root presence as deep as 2 m. In 70 of these pits we estimated root mass and created standardized metrics of both data sets to compare their depth distributions. We addressed whether: (a) depth distributions of root presence‐absence data differ from root mass data, thus implying different degrees of root‐regolith interactions with depth; and (b) if root presence or any depth‐dependent differences between these data sets vary predictably with environmental conditions. Presence of fine roots exhibited diverse depth‐dependent patterns; root mass generally declined with depth. In B and C horizons, standardized root presence was greater than standardized root mass; random forest analyses suggest these discrepancies are greater in B horizons with increasing mean annual precipitation and in C horizons with increasing mean annual temperature. Our work suggests that deep in the subsurface, biogeochemical and reactive transport processes result from more numerous root‐regolith interfaces than mass data suggest. We present a new paradigm for discerning patterns in depth distributions of root‐regolith interfaces across multiple biomes and land uses that promotes understanding of the roles of those interfaces in driving key critical zone processes. 

ABSTRACT Hydrologic connectivity is defined as the connection among stores of water within a watershed and controls the flux of water and solutes from the subsurface to the stream. Hydrologic connectivity is difficult to quantify because it is goverened by heterogeniety in subsurface storage and permeability and responds to seasonal changes in precipitation inputs and subsurface moisture conditions. How interannual climate variability impacts hydrologic connectivity, and thus stream flow generation and chemistry, remains unclear. Using a rare, four‐year synoptic stream chemistry dataset, we evaluated shifts in stream chemistry and stream flow source of Coal Creek, a montane, headwater tributary of the Upper Colorado River. We leveraged compositional principal component analysis and end‐member mixing to evaluate how seasonal and interannual variation in subsurface moisture conditions impacts stream chemistry. Overall, three main findings emerged from this work. First, three geochemically distinct end members were identified that constrained stream flow chemistry: reach inflows, and quick and slow flow groundwater contributions. Reach inflows were impacted by historic base and precious metal mine inputs. Bedrock fractures facilitated much of the transport of quick flow groundwater and higher‐storage subsurface features (e.g., alluvial fans) facilitated the transport of slow flow groundwater. Second, the contributions of different end members to the stream changed over the summer. In early summer, stream flow was composed of all three end members, while in late summer, it was composed predominantly of reach inflows and slow flow groundwater. Finally, we observed minimal differences in proportional composition in stream chemistry across all four years, indicating seasonal variability in subsurface moisture and spatial heterogeneity in landscape and geologic features had a greater influence than interannual climate fluctuation on hydrologic connectivity and stream water chemistry. These findings indicate that mechanisms controlling solute transport (e.g., hydrologic connectivity and flow path activation) may be resilient (i.e., able to rebound after perturbations) to predicted increases in climate variability. By establishing a framework for assessing compositional stream chemistry across variable hydrologic and subsurface moisture conditions, our study offers a method to evaluate watershed biogeochemical resilience to variations in hydrometeorological conditions. 

Abstract The seasonal behavior of fluvial dissolved silica (DSi) concentrations, termedDSi regime, mediates the timing of DSi delivery to downstream waters and thus governs river biogeochemical function and aquatic community condition. Previous work identified five distinct DSi regimes across rivers spanning the Northern Hemisphere, with many rivers exhibiting multiple DSi regimes over time. Several potential drivers of DSi regime behavior have been identified at small scales, including climate, land cover, and lithology, and yet the large‐scale spatiotemporal controls on DSi regimes have not been identified. We evaluate the role of environmental variables on the behavior of DSi regimes in nearly 200 rivers across the Northern Hemisphere using random forest models. Our models aim to elucidate the controls that give rise to (a) average DSi regime behavior, (b) interannual variability in DSi regime behavior (i.e., Annual DSi regime), and (c) controls on DSi regime shape (i.e., minimum and maximum DSi concentrations). Average DSi regime behavior across the period of record was classified accurately 59% of the time, whereas Annual DSi regime behavior was classified accurately 80% of the time. Climate and primary productivity variables were important in predicting Average DSi regime behavior, whereas climate and hydrologic variables were important in predicting Annual DSi regime behavior. Median nitrogen and phosphorus concentrations were important drivers of minimum and maximum DSi concentrations, indicating that these macronutrients may be important for seasonal DSi drawdown and rebound. Our findings demonstrate that fluctuations in climate, hydrology, and nutrient availability of rivers shape the temporal availability of fluvial DSi. 

Abstract Fluvial silicon (Si) plays a critical role in controlling primary production, water quality, and carbon sequestration through supporting freshwater and marine diatom communities. Geological, biogeochemical, and hydrological processes, as well as climate and land use, dictate the amount of Si exported by streams. Understanding Si regimes—the seasonal patterns of Si concentrations—can help identify processes driving Si export. We analyzed Si concentrations from over 200 stream sites across the Northern Hemisphere to establish distinct Si regimes and evaluated how often sites moved among regimes over their period of record. We observed five distinct regimes across diverse stream sites, with nearly 60% of sites exhibiting multiple regime types over time. Our results indicate greater spatial and interannual variability in Si seasonality than previously recognized and highlight the need to characterize the watershed and climate variables that affect Si cycling across diverse ecosystems.