Abstract Headwater catchments provide essential water and nutrients to downstream ecosystems. The timing and evolution of their transport is shaped in part by the “invisible” subsurface structure but have been largely unexplored at the watershed scale. This raises a fundamental question: how and to what extent does subsurface structure influence streamflow and solute transport in montane watersheds? Here, we test controls of three‐dimensionally resolved subsurface structure on solute transport, which reflects source waters and water residence time. We integrate the geophysically mapped architecture of Coal Creek, a headwater catchment in the Colorado River Basin, into numerical flow‐transport models. Our results reveal greater vertical connectivity elongates flow paths and enhances deep groundwater contributions to streams, therefore substantially influencing the timing and magnitude of solute transport. In contrast, watershed‐integrated outlet discharge can be predicted without high‐resolution subsurface information. These findings demonstrate incorporating subsurface architecture is critical for predicting ecosystem health and contaminant transport.

Stem water content is a fundamental parameter governing key plant physiological processes, including transpiration, stomatal conductance, sap flow, and hydraulic capacitance. Although extensively studied in the context of timber, construction, and engineering, its physiological significance in living plants remains comparatively underdeveloped. This review synthesises the physiological literature to provide a clear and consistent definition of stem water content, partitioning it into bark, phloem, sapwood, and heartwood components, with particular emphasis on sapwood water content. A theoretical framework is developed to define the maximum and minimum bounds of sapwood water content based on porosity, basic wood density, and the fibre saturation point. These bounds are supported by measurements compiled from the published literature including 3395 samples across 742 species. The diel range of sapwood water content is further examined in relation to wood density, hydraulic capacitance, atmospheric vapour pressure deficit, and species-specific stomatal regulation (isohydric versus anisohydric behaviour). Measurement techniques, including wood sampling, dielectric sensors, heat-pulse methods, and multiple tomographic techniques, are critically evaluated with respect to their underlying principles, advantages, and limitations. This review provides a unified conceptual framework for sapwood water content, improving clarity, comparability, and application in plant physiological research.

Abstract Logjams in streams create complex morphologic features such as pools, bars, and branching channels that enhance stream water storage and force water through the streambed. We examine how these features alter solute retention in stream corridors as discharge increases, backwaters expand, new channels activate, and jams become more submerged. Using numerical experiments informed by a well‐studied field site (Little Beaver Creek, Colorado, USA), we simulate coupled surface water and groundwater flow in stream reaches with logjams. Model results indicate that solute retention declines with increasing stream discharge, although the magnitude of decline depends on the metric used to quantify retention. We do not observe threshold‐like changes when dry channels reactivate but only modest deviations from the overall trend, suggesting that reactivation does not produce strong threshold‐like changes in retention behavior in already complex reaches. As discharge increases, backwater pools enlarge and hyporheic exchange volumes increase, but backwaters comprise a diminishing fraction of total channel storage, leading to reduced overall retention. Hyporheic zone volume and the turnover length both increase with discharge, indicating a larger but weakly connected hyporheic zone. Taken together, we expect substantially greater biogeochemical transformation at low flows in complex mountain streams. This research offers new insights into potential reach‐scale changes in solute transport through complex mountain streams as streamflow changes, which can be expected with the loss of snowpack under a warming climate.

Abstract Droughts have been extensively studied at small to large scales, yet limited work has integrated the mountain‐range and tree‐level perspectives to explain tree drought response at the intra‐catchment scale where management decisions are made. Here, we investigated tree response to drought in terms of resistance—the ability of a forest to continue transpiring during drought—and resilience—the ability to rebound post‐drought. We estimated resistance and resilience using Landsat‐derived normalized difference vegetation index (NDVI) over a 0.5 km 2 catchment of the Southern Sierra Critical Zone Observatory. At the catchment‐wide scale, we fitted generalized additive models with eight remotely sensed predictors to explain 51% of the variance in resistance and 59% in resilience. Topography and baseline greenness were the strongest predictors and exhibited opposite effects on resistance versus resilience, underscoring the need to distinguish their drivers. Aspect and snow depth were significant for resilience only, further highlighting that resistance and resilience are governed using partially distinct processes. Slope and elevation effects contradicted regional‐scale patterns, whereas canopy height effects were consistent across scales. Remote sensing revealed spatial patterns of drought response, while in situ ecohydrological, meteorological, and geophysical (electrical resistivity) data from six stations offered process‐based insights into the conditions underlying them: valley‐bottom hydrologic refugia, inferred reliance on internal sapwood water stores, and consistently low atmospheric demand were all associated with locations that experienced greater drought resistance. This work demonstrates that forest vulnerability emerges from coupled, scale‐dependent interactions among hydrology, vegetation structure, and topography.

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.

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.

The conversion of grasslands to shrublands, known as woody encroachment, has increased vegetation water use, particularly in mesic systems. However, declines in soil moisture due to woody encroachment have not been extensively explored. This study examines the impacts of woody encroachment on the depth and degree of soil drying in a mesic tallgrass prairie in Kansas, USA. We compared soil drying beneath roughleaf dogwood (Cornus drummondii) and non-encroached tallgrass prairie using half-hourly measurements of soil moisture from 2021 to 2024 (event scale), electrical resistivity in June and October of 2022 (seasonal scale), and neutron probe measurements collected monthly between 1984 and 2021(decadal scale). Across all time scales, we found increased soil drying beneath shrubs compared to grasses, particularly in deeper layers. Soil moisture declined up to 20

Here, we explore how differences in morphologic heterogeneity due to logjams and secondary channels drive transient storage across discharge in two stream reaches within the Front Range of Colorado, USA. During three tracer tests conducted from baseflow to near-peak snowmelt, we collected instream fluid conductivity measurements and conducted electrical resistivity surveys to characterize tracer movement in the surface and subsurface of the stream system. The reach with two logjams and an intermittent secondary channel exhibited greater heterogeneity in surface transient storage, driving heterogeneity in hyporheic exchange flows, compared to the reach with a single logjam and a perennial secondary channel. As discharge increased, (a) backwater pools created by logjams increased in size in both systems, (b) channel complexity increased as logjams forced flow into secondary channels, and (c) subsurface flowpath distribution increased. Various transient storage indices provide some insight on solute retention but compressing data from this system into simple values was unintuitive given the noise in breakthrough-curve tails and secondary peaks in concentration. While subsurface exchange increases with discharge in both reaches, retention may not. Flushing of subsurface tracers is highest at medium discharge as interpreted from the electrical resistivity inversions in both reaches, perhaps because of a tradeoff between the increasing extent of subsurface flowpaths with discharge and larger pressure gradients for driving flow. This work is one of the first to explore controls on exchange and retention in stream systems with multiple logjams and evolving channel planform using geophysical data to constrain the subsurface movement of solutes.

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.

In the Anthropocene—a period marked by rapid environmental change—understanding the critical zone (CZ), the Earth's outer layer where rock, soil, water, air, and living organisms interact, is crucial. This review emphasizes data-model integration, the process of combining observational data (collected from field and laboratory settings) with computational models (representations of processes) to enhance understanding of coupled systems, validate model predictions, and improve simulation accuracy in response to natural and anthropogenic drivers. We propose a three-tiered framework for data-model integration in CZ science. Tier 1 incorporates observational data into model inputs to test hypotheses and explore processes where understanding is limited, providing insights into CZ functions over long timescales or in data-scarce areas. Tier 2 compares model outputs with observations and focuses on validation and calibration. Tier 3 involves iterative data-model integration, in which models are continuously refined through feedback from new data and evolving scientific questions. While rare in CZ science, this approach holds promise for guiding new data collection, improving predictive accuracy and enabling hindcasts and earthcasts. We illustrate each tier with curated examples and discuss how the tiers reflect varying levels of knowledge about CZ function and may guide knowledge transfer to understudied areas. Finally, we identify key challenges and future directions, including scale integration, non-stationarity, model limitations, and the need for transparent sharing of data-model integration processes. This article is categorized under:

Deep soils represent a dynamic interface between surface soils and saprolite or bedrock, influencing water flow, solute and gas exchange, and mineral and organic matter transformations from local to global scales. Root architecture reflects land cover and soil heterogeneity, enabling vegetation access to resources that vary temporally and spatially while shaping soil structure and formation. However, how land use can influence roots and soil structure relatively deep in the subsurface (>30 cm) remains poorly understood. We investigate how cropland-related land use and subsequent vegetation recovery alter rooting dynamics and soil structure in deeper horizons. Using a large-scale data set representing multiple land uses as a means of varying root abundance across four soil orders, we demonstrate that B horizon root loss and regeneration are linked to changes in multiple soil structural attributes deep within soil profiles. Our findings further suggest that the degree of soil development modulates the extent of structural transformations, with less-developed soils showing greater susceptibility to root-associated structural shifts. The greatest change in structural development and distinctness was observed in Inceptisols, while Ultisols exhibited the least change. Such soil structural changes affect water flowpaths, carbon retention, and nutrient transport throughout the subsurface. This work thus underscores the need for Earth system models to capture dynamic soil structural attributes that respond to land-use change. We suggest that changes in deep-rooting abundance, such as those accelerating in the Anthropocene, may be an important agent of subsurface structural change with meaningful implications for contemporary and future ecosystem feedbacks to climate. Plain Language Summary Deep soil modulates how water, gases, and nutrients move through ecosystems and interact with plants, animals, and the atmosphere. Roots provide plants with water and nutrients and adapt their structures to the complex and varying nature of soils. This relationship is two-sided: as roots grow, they also change soil structure, influencing how it holds and moves water, carbon, and nutrients. We examined how deep soil structure changes with root abundance by leveraging root and soil data representing land-use transitions from natural vegetation to croplands to restored natural vegetation. Using data from across the United States, we found that areas where crops replaced more deeply-rooted vegetation exhibit different soil structures-well below the plow line-compared to areas less disturbed or with regenerating vegetation. These changes were dependent on soil type and how soil properties and environmental factors changed over time. Deep soil structure was especially sensitive to root removal and regrowth in less well-developed soils. Such changes in soil structure can impact water flow, carbon storage, and nutrient movement underground. This work highlights the need to consider dynamic deep soil structure, especially given rapid land use and climate changes, in climate and ecosystem models.

Forests cover almost one third of the Earth's land area and are central in the carbon and water cycles. Soil water availability is one of the most important factors regulating transpiration, biomass production and plant species distribution in ecosystems. The carbon and water cycles are closely linked and so understanding the functioning and evolution of forest environments and their relation to subsurface structure and water availability is essential to improve understanding of the water cycle under a changing climate. Studying the forest subsurface is a challenge because of its heterogeneous nature and difficult accessibility. Traditional approaches used by ecologists are also often point measurements that have a low spatial representativity. Near-surface geophysics offers a wide range of methods to characterize the spatial and temporal variability of subsurface properties and associated processes in a non-destructive and integrative way. Geophysical methods allow us to obtain new information that complements ecophysiological methods to better understand ecosystem functioning, and in particular processes linked to ecohydrology. The use of geophysical methods in forests is growing, both by geophysicists seeking to apply their tools to more complex environments, and by ecologists seeking to better characterize their experimental sites. One of the major applications and assets of geophysics in forests is to quantify and monitor water stocks and dynamics. For example, geoelectrical monitoring can be used to assess the distribution and spatial variations of water content in the subsoil. In this work, we show the example of a recently developed ensemble approach to quantitatively relate electrical conductivity monitoring and the distribution and dynamic of water in forest soils. We believe that such interdisciplinary advances can help us improving the quantitative assessment of forest responses to the environment and their adaptation to climate change.

Woody encroachment-the expansion of woody shrubs into grasslands-is a widely documented phenomenon with global significance for the water cycle. However, its effects on watershed hydrology, including streamflow and groundwater recharge, remain poorly understood. A key challenge is the limited understanding of how changes to root abundance, size and distribution across soil depths influence infiltration and preferential flow. We hypothesised that woody shrubs would increase and deepen coarse-root abundance and effective soil porosity, thus promoting deeper soil water infiltration and increasing soil water flow velocities. To test this hypothesis, we conducted a study at the Konza Prairie Biological Station in Kansas, where roughleaf dogwood (Cornus drummondii) is the predominant woody shrub encroaching into native tallgrass prairie. We quantified the distribution of coarse and fine roots and leveraged soil moisture time series and electrical resistivity imaging to analyse soil water flow beneath shrubs and grasses. We observed a greater fraction of coarse roots beneath shrubs compared to grasses, which was concurrent with greater saturated hydraulic conductivity and effective porosity. Half-hourly rainfall and soil moisture data show that the average soil water flow through macropores was 135% greater beneath shrubs than grasses at the deepest B horizon, consistent with greater saturated hydraulic conductivity. Soil-moisture time series and electrical resistivity imaging also indicated that large rainfall events and greater antecedent wetness promoted more flow in the deeper layers beneath shrubs than beneath grasses. These findings suggest that woody encroachment alters soil hydrologic processes with cascading consequences for ecohydrological processes, including increased vertical connectivity and potential groundwater recharge.

Plant hydraulic properties are critical to predicting vegetation water use as part of land-atmosphere interactions and plant responses to drought. However, current measurements of plant hydraulic properties are labor-intensive, destructive, and difficult to scale up, consequently limiting the comprehensive characterization of whole-plant hydraulic properties and hydraulic parameterization in land-surface modeling. To address these challenges, we develop a pumping-test analogue method, using sap-flow and stem water-potential data to derive whole-plant hydraulic properties, namely, maximum hydraulic conductance, effective capacitance, and Psi 50 (water potential at which 50 % loss of hydraulic conductivity occurs). Experimental trials on Allocasuarina verticillata indicate that the parameters derived over short periods (around 7 d) exhibit good representativity for predicting plant water use over at least 1 month. We applied this method to estimate near-continuous whole-plant hydraulic properties over 1 year, demonstrating its potential to supplement existing labor-intensive measurement approaches. The results reveal the seasonal plasticity of the effective plant hydraulic capacitance. They also confirm the seasonal plasticity of maximum hydraulic conductance and the hydraulic vulnerability curve, known in the plant physiology community, while neglected in the hydrology and land-surface modeling community. It is found that the seasonal plasticity of hydraulic conductance is associated with climate variables, providing a way forward to represent seasonal plasticity in models. The relationship between derived maximum hydraulic conductance and Psi 50 also suggests a trade-off between hydraulic efficiency and safety of Allocasuarina verticillata. Overall, the pumping-test analogue offers potential for better representation of plant hydraulics in hydrological modeling, benefitting land-management and land-surface process forecasting.

Electrical resistivity tomography (ERT) is widely used to monitor electrically conductive tracers. Dense data sets, while improving spatial resolution, often result in long acquisition times, causing temporal smearing of plumes, especially in highly permeable media. In such cases, rapid changes in electrical conductivity may invalidate the assumption of constant subsurface properties during data collection, reducing monitoring accuracy. Previous studies have focused on improving the spatial resolution by optimizing measurement configurations, but a comprehensive analysis of trade-offs between spatial resolution and measurement time for transport studies remains lacking. This study developed an adaptive multi-objective ERT survey-design model to consider both spatial and temporal resolution for monitoring rapidly migrating targets. By adapting the non-dominated sorting genetic algorithm II, we explored the trade-offs between these two competing objectives in a synthetic 3-D aquifer where the conductive tracer migrated approximately 15 m in 4 hr. Results show that ERT data obtained from a specific number of randomly selected and standard measurement configurations yielded limited spatial resolution. Moreover, excessive data collection hindered plume characterization due to the plume's rapid migration during the prolonged survey time. In contrast, the proposed method effectively resolved conflicts between spatial and temporal resolution, providing Pareto-optimal solutions for time-lapse ERT surveys. The Pareto front identified optimal combinations of measurement configurations that maximize spatial resolution and minimize data acquisition time, thereby enhancing real-time monitoring of fast-migrating plumes. Compared to the standard data set, the estimation accuracy of total solute mass evolution improved by up to 22%.

Streams impacted by historic mining activity are characterized by acidic pH, unique microbial communities, and abundant metal-oxide precipitation, all of which can influence groundwater-surface water exchange. We investigate how metal-oxide precipitates and hyporheic mixing mediate the composition of microbial communities in two streams receiving acid-rock and mine drainage near Silverton, Colorado, USA. A large, neutral pH hyporheic zone facilitated the precipitation of metal particles/colloids in hyporheic porewaters. A small, low pH hyporheic zone, limited by the presence of a low-permeability, iron-oxyhydroxide layer known as ferricrete, led to the formation of steep geochemical gradients and high dissolved-metal concentrations. To determine how these two hyporheic systems influence microbiome composition, we installed well clusters and deployed in situ microcosms in each stream to sample porewaters and sediments for 16S rRNA gene sequencing. Results indicated that distinct hydrogeochemical conditions were present above and below the ferricrete in the low pH system. A positive feedback loop may be present in the low pH stream where microbially mediated precipitation of iron-oxides contributes to additional clogging of hyporheic pore spaces, separating abundant, iron-oxidizing bacteria (Gallionella spp.) above the ferricrete from rare, low-abundance bacteria below the ferricrete. Metal precipitates and colloids that formed in the neutral pH hyporheic zone were associated with a more diverse phylogenetic community of nonmotile, nutrient-cycling bacteria that may be transported through hyporheic pore spaces. In summary, biogeochemical conditions influence, and are influenced by, hyporheic mixing, which mediates the distribution of micro-organisms and, thus, the cycling of metals in streams receiving acid-rock and mine drainage.IMPORTANCEIn streams receiving acid-rock and mine drainage, the abundant precipitation of iron minerals can alter how groundwater and surface water mix along streams (in what is known as the "hyporheic zone") and may shape the distribution of microbial communities. The findings presented here suggest that neutral pH streams with large, well-mixed hyporheic zones may harbor and transport diverse microorganisms attached to particles/colloids through hyporheic pore spaces. In acidic streams where metal oxides clog pore spaces and limit hyporheic exchange, iron-oxidizing bacteria may dominate and phylogenetic diversity becomes low. The abundance of iron-oxidizing bacteria in acid mine drainage streams has the potential to contribute to additional clogging of hyporheic pore spaces and the accumulation of toxic metals in the hyporheic zone. This research highlights the dynamic interplay between hydrology, geochemistry, and microbiology at the groundwater-surface water interface of acid mine drainage streams. In streams receiving acid-rock and mine drainage, the abundant precipitation of iron minerals can alter how groundwater and surface water mix along streams (in what is known as the "hyporheic zone") and may shape the distribution of microbial communities. The findings presented here suggest that neutral pH streams with large, well-mixed hyporheic zones may harbor and transport diverse microorganisms attached to particles/colloids through hyporheic pore spaces. In acidic streams where metal oxides clog pore spaces and limit hyporheic exchange, iron-oxidizing bacteria may dominate and phylogenetic diversity becomes low. The abundance of iron-oxidizing bacteria in acid mine drainage streams has the potential to contribute to additional clogging of hyporheic pore spaces and the accumulation of toxic metals in the hyporheic zone. This research highlights the dynamic interplay between hydrology, geochemistry, and microbiology at the groundwater-surface water interface of acid mine drainage streams.

Dual‐porosity models are often used to describe solute transport in heterogeneous media, but the parameters within these models (e.g., immobile porosity and mobile/immobile exchange rate coefficients) are difficult to identify experimentally or relate to measurable quantities. Here, we performed synthetic, pore‐scale millifluidics simulations that coupled fluid flow, solute transport, and electrical resistivity (ER). A conductive‐tracer test and the associated geoelectrical signatures were simulated for four flow rates in two distinct pore‐scale model scenarios: one with intergranular porosity, and a second with an intragranular porosity also defined. With these models, we explore how the effective characteristic‐length scale estimated from a best‐fit dual‐domain mass transfer (DDMT) model compares to geometric aspects of the flow field. In both model scenarios we find that: (1) mobile domains and immobile domains develop even in a system that is explicitly defined with one domain; (2) the ratio of immobile to mobile porosity is larger at faster flow rates as is the mass‐transfer rate; and (3) a comparison of length scales associated with the mass‐transfer rate ( L α ) and those associated with calculation of the Peclet number ( L Pe ) show L Pe is commonly larger than L α . These results suggest that estimated immobile porosities from a DDMT model are not only a function of physically mobile or immobile pore space, but also are a function of the average linear pore‐water velocity and physical obstructions to flow, which can drive the development of immobile porosity even in single‐porosity domains.