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.

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:

The western U.S. is experiencing shifts in recharge due to climate change, and it is currently unclear how hydrologic shifts will impact geochemical weathering and stream concentration-discharge (C-Q) patterns. Hydrologists often use C-Q analyses to assess feedbacks between stream discharge and geochemistry, given abundant stream discharge and chemistry data. Chemostasis is commonly observed, indicating that geochemical controls, rather than changes in discharge, are shaping stream C-Q patterns. However, few C-Q studies investigate how geochemical reactions evolve along groundwater flowpaths before groundwater contributes to streamflow, resulting in potential omission of important C-Q controls such as coupled mineral dissolution and clay precipitation and subsequent cation exchange. Here, we use field observations-including groundwater age, stream discharge, and stream and groundwater chemistry-to analyse C-Q relations in the Manitou Experimental Forest in the Colorado Front Range, USA, a site where chemostasis is observed. We combine field data with laboratory analyses of whole rock and clay x-ray diffraction and soil cation-extraction experiments to investigate the role that clays play in influencing stream chemistry. We use Geochemist's Workbench to identify geochemical reactions driving stream chemistry and subsequently suggest how climate change will impact stream C-Q trends. We show that as groundwater age increases, C-Q slope and stream solute response are not impacted. Instead, primary mineral dissolution and subsequent clay precipitation drive strong chemostasis for silica and aluminium and enable cation exchange that buffers calcium and magnesium concentrations, leading to weak chemostatic behaviour for divalent cations. The influence of clays on stream C-Q highlights the importance of delineating geochemical controls along flowpaths, as upgradient mineral dissolution and clay precipitation enable downgradient cation exchange. Our results suggest that geochemical reactions will not be impacted by future decreasing flows, and thus where chemostasis currently exists, it will continue to persist despite changes in recharge.

Using hydrochemical and isotopic compositions of springs and wells, we trace carbon from critical zone carbon dioxide (CO2) into groundwater of the semi-arid Reynolds Creek Experimental Watershed - Critical Zone Observatory, southwestern Idaho, USA. Dissolved inorganic carbon (DIC) concentrations, pH and stable isotope tracers of carbon for DIC (δ13CDIC), are used to show that most groundwater evolves under open system conditions, moving carbon into the groundwater and acting as a carbon sink. However, one sample (−10.94‰ δ13CDIC, 6,350 14C years before present (yrs. BP)) may have evolved under closed system conditions with a higher partial pressure of critical zone CO2 than present-day soils. By characterizing the carbon cycle, we show that (1) carbon evolution is primarily under open-system conditions, (2) shallow groundwater samples are generally less mixed and more recent (10 to 70 3H yrs. BP) than deeper groundwater samples (1,469 to 6,350 14C yrs. BP), and (3) the older portion of the groundwater may be even older than the calculated 14C ages, as indicated by the mixing of age tracers in intermediate wells. Our global conception of the deep critical zone should include carbon cycling of critical zone CO2 in old groundwater. Characterizing the deep critical zone in a semi-arid weathered silicate watershed improves our global understanding of carbon, nutrient and water cycling.

Stream dissolved organic matter (DOM) is a globally important carbon flux and a locally important control on stream ecosystems, and therefore understanding controls on stream DOM fluxes and dynamics is crucial at both local and global scales. However, attributing process controls is challenging because both hydrological and biological controls on DOM are integrated and may vary over time and throughout stream networks. Our objective was to assess the patterns and corresponding controls of diel DOM cycles through a seasonal flow recession by using reach-scale in situ sensors in a non-perennial stream network. We identified five characteristic diel variations in DOM with differing phase and amplitude. During snowmelt flows, diel variations in DOM were consistent among sites and reflected diel flowpath shifts and photodegradation. Evapotranspiration-driven diel stage oscillations emerged at two upstream sites, shaping diel DOM patterns indirectly, by creating conditions for instream DOM processing. At a spring-fed site, minimal diel variation was observed throughout the summer whereas at an intermittent reach, daily drying and rewetting created biogeochemical hot moments. This research demonstrates that controls on DOM vary over time and space, even in close proximity, generating asynchronous fDOM patterns during low flows, illuminating shifts in biogeochemical processes and flowpaths.

Silicate weathering can induce calcite precipitation from groundwater, enabling carbon dioxide (CO2) sequestration in the critical zone (CZ), which acts as a net carbon sink with significant implications for the global carbon budget. In weathered silicates, secondary calcite dissolution accompanies precipitation-dissolution reactions, and it is unclear how calcite dissolution affects CO2 consumption in natural settings. At the Reynolds Creek Experimental Watershed- Critical Zone Observatory (RCEW-CZO), southwestern Idaho, USA, we estimate in-situ carbon sequestration rates in a semi-arid weathered silicate aquifer using hydrochemical compositions and age tracers from 6 springs and 10 wells. We delineate water-rock interactions by using observed groundwater chemistry to model open system carbon evolution, evapoconcentration in wells, silicate weathering, and formation of clays along groundwater flowpaths. We suggest carbonate precipitation under closed system conditions in deep groundwater, as calcite saturation is reached and CZ CO2 drops to just 41 % of initial concentrations in older waters. In a closed system, we estimate approximately 9 % of CZ CO2 would precipitate, indicating that on-going water-rock interactions in our weathered silicate system appear to drive continued carbon sequestration. Carbon sequestration rates via silicate weathering may help to explain a missing C sink observed at the RCEW-CZO and in other weathered silicate basins.

Geologic, geomorphic, and climatic factors have been hypothesized to influence where streams dry, but hydrologists struggle to explain the temporal drivers of drying. Few hydrologists have isolated the role that vegetation plays in controlling the timing and location of stream drying in headwater streams. We present a distributed, fine-scale water balance through the seasonal recession and onset of stream drying by combining spatiotemporal observations and modeling of flow presence/absence, evapotranspiration, and groundwater inputs. Surface flow presence/absence was collected at fine spatial (~80 m) and temporal (15-min) scales at 25 locations in a headwater stream in southwestern Idaho, USA. Evapotranspiration losses were modeled at the same locations using the Simultaneous Heat and Water (SHAW) model. Groundwater inputs were estimated at four of the locations using a mixing model approach. In addition, we compared high-frequency, fine-resolution riparian normalized vegetation difference index (NDVI) with stream flow status. We found that the stream wetted and dried on a daily basis before seasonally drying, and daily drying occurred when evapotranspiration outputs exceeded groundwater inputs, typically during the hours of peak evapotranspiration. Riparian NDVI decreased when the stream dried, with a ~2-week lag between stream drying and response. Stream diel drying cycles reflect the groundwater and evapotranspiration balance, and riparian NDVI may improve stream drying predictions for groundwater-supported headwater streams.

Non‐perennial streams are receiving increased attention from researchers, however, suitable methods for measuring their hydrologic connectivity remain scarce. To address this deficiency, we developed Bayesian statistical approaches for measuring both average active stream length, and a new metric called average communication distance. Average communication distance is a theoretical increased effective distance that stream‐borne materials must travel, given non‐continuous streamflow. Because it is the product of the inverse probability of surface water presence and stream length, the average communication distance of a non‐perennial stream segment will be greater than its actual physical length. As an application we considered Murphy Creek, a simple non‐perennial stream network in southwestern Idaho, USA. We used surface water presence/absence data obtained in 2019, and priors for the probability of surface water, based on predictions from an existing regional United States Geological Survey model. Average communication distance posterior distributions revealed locations where effective stream lengths increased dramatically due to flow rarity. We also found strong seasonal (spring, summer, fall) differences in network‐level posterior distributions of both average stream length and average communication distance. Our work demonstrates the unique perspectives concerning network drying provided by communication distance, and demonstrates the general usefulness of Bayesian approaches in the analysis of non‐perennial streams.

The western U.S. is experiencing increasing rain to snow ratios due to climate change, and scientists are uncertain how changing recharge patterns will affect future groundwater‐surface water connection. We examined how watershed topography and streambed hydraulic conductivity impact groundwater age and stream discharge at eight sites along a headwater stream within the Manitou Experimental Forest, CO USA. To do so, we measured: (a) continuous stream and groundwater discharge/level and specific conductivity from April to November 2021; (b) biweekly stream and groundwater chemistry; (c) groundwater chlorofluorocarbons and tritium in spring and fall; (d) streambed hydraulic conductivity; and (e) local slope. We used the chemistry data to calculate fluorite saturation states that were used to inform end‐member mixing analysis of streamflow source. We then combined chlorofluorocarbon and tritium data to estimate the age composition of riparian groundwater. Our data suggest that future stream drying is more probable where local slope is steep and streambed hydraulic conductivity is high. In these areas, groundwater source shifted seasonally, as indicated by age increases, and we observed a high fraction of groundwater in streamflow, primarily interflow from adjacent hillslopes. In contrast, where local slope is flat and streambed hydraulic conductivity is low, streamflow is more likely to persist as groundwater age was seasonally constant and buffered by storage in alluvial sediments. Groundwater age and streamflow paired with characterization of watershed topography and subsurface characteristics enabled identification of likely controls on future stream drying patterns.

Many conventional stream network metrics are poorly suited to non-perennial streams, which can vary substantially in space and time. To address this issue, we considered non-perennial stream networks as directed acyclic graphs (DAGs). DAG metrics allow: 1) summarization of important non-perennial stream characteristics (e.g., complexity, connectedness, and nestedness) from both local (individual segment) and global stream network perspectives, and 2) tracking of these features as networks expand and contract. We review a large number of graph theoretic metrics, and introduce a new R package, streamDAG that codifies approaches we feel are most useful. The streamDAG package contains procedures for handling water presence data, and functions for both local and global analyses of both unweighted and weighted stream DAGs. We demonstrate streamDAG using two North American non-perennial streams: Murphy Creek, a simple drainage system in the Owyhee Mountains of southwestern Idaho, and Konza Prairie, a relatively complex network in central Kansas.

Montane ecoregions are important vehicles for downstream hydrologic function, but their dynamics are relatively understudied compared to alpine and subalpine catchments in the western United States. Montane catchments experience shifts in precipitation inputs seasonally, which results in spatiotemporal differences in source area contributions to the stream. We collected hydrometric and geochemical data between 2018 and 2021 from a 2.65 km2 semi-arid headwater catchment in the Front Range of Colorado, USA. Using a combined approach of hydrometric monitoring, geochemical characterization, and end-member mixing analysis (EMMA), we assess hydrologic connectivity between areas with high upslope accumulation and the stream. Within our study area, high upslope accumulation area corresponded to alluvial/ colluvial fans wherein we focused instrumentation and water sample collection. Using observed rainfall, and multiyear measurements of groundwater levels, soil moisture, and streamflow, we observed distinct hydrologic seasons within our catchment characterized by snowmelt during the spring, rainstorms during the summer, and a return to baseflow during the fall. Within this framework, we found that source areas to streamflow shift with longitudinal distance downstream, and among hydrologic seasons. Notably, our EMMA results indicate that contributions from upstream source areas become less important than lateral inputs from spring snowmelt into the fall return to baseflow. This was most pronounced at the upper catchment where upstream contributions to streamflow decreased up to 33.3% between spring and fall. These results suggest that streamflow is maintained by local source areas contributing laterally and vertically. Our results reflect dynamic shifts in hydrologic connectivity in space and in time, which are increasingly important to land and water resource management given rapid climate changes within the western United States.

We developed Bayesian statistical approaches to assess non-perennial stream network connectivity. Our new methods allow: 1) consideration of changes to both local (stream segment) and global (stream network) connectivity over time, 2) incorporation of prior information from different data sources, and 3) straightforward computation of the posterior distributions of both active stream length and a new metric called communication distance. Communication distance measures the effective stream length for the movement of materials, including water and solutes, from upstream to downstream sites. Communication distance posteriors require the inverse-beta probability density function whose form had not been previously derived. The inverse-beta distribution can be used to represent the rarity of surface water presence compared to a perennial stream, thus clarifying bottlenecking propensities for stream segments. As an application, we considered Murphy Creek, a simple stream network in southwestern Idaho, USA. Our models used surface water presence/absence data from 2019, and priors based on existing regional USGS model predictions for surface water. Murphy Creek probabilities for surface water presence were heterogeneous in space and time, and were likely driven by fine-scale spatial variations in shallow subsurface hydraulic conductivity. Strong seasonal (spring, summer, fall) temporal differences were evident in network-level posterior distributions of both stream length and communication distance. Specifically, stream lengths were shorter and more variable in the summer and fall than in the spring. The novel communication distance posteriors were multimodal, platykurtic, and negatively skewed for spring, summer and fall, respectively, revealing bottlenecking effects that varied over time.

Many conventional stream network metrics are time-invariant and/or do not consider the importance of individual stream locations to network functionality. As a result, they are not well-suited to non-perennial streams, in which hydrologic status (flowing vs. pooled vs. dry) can vary substantially in space and time. To help address this issue, we consider non-perennial streams as directed acyclic graphs (DAGs). DAG metrics allow: 1) summarization of important network characteristics (e.g., centrality, complexity, connectedness, and nestedness) of both particular (local) stream network locations and entire (global) stream networks, and 2) tracking of these characteristics as non-perennial stream networks expand and shrink. We review a large number of graph-theoretic procedures for their utility in the analysis of non-perennial stream DAGs. Approaches we find useful are codified in a new publicly available R-package, streamDAG, which allows straightforward igraph representations of stream networks and easy modification of non-perennial stream DAG topologies based on water presence/absence data. The streamDAG package includes a wide variety of local and global measures for both unweighted and weighted stream digraphs, and provides procedures for generating Bayesian posterior distributions of the probability and the reciprocal probability of surface water presence. We demonstrate streamDAG algorithms using two North American non-perennial streams: Murphy Creek, a simple drainage system in the Owyhee Mountains of southwestern Idaho, and Konza Prairie, a relatively complex stream network in central Kansas.

Abstract The Reynolds Creek Experimental Watershed (RCEW) and Critical Zone Observatory (CZO), located south of the western Snake River Plain in the Intermountain West of the United States, is the site of over 60 years of research aimed at understanding integrated earth processes in a semi‐arid climate to aid sustainable use of environmental resources. Meteoric water lines (MWLs) are used to interpret hydrologic processes, though equilibrium and nonequilibrium processes affect the linear function and can reveal seasonal and climatological effects, necessitating the development of local meteoric water lines (LMWLs). At RCEW‐CZO, an RCEW LMWL was developed using non‐volume‐weighted, orthogonal regression with assumed error in both predictor and response variables from several years of precipitation (2015, 2017, 2019, 2020, and 2021) primarily at three different elevations (1203, 1585, and 2043 m). As most precipitation is evaporated or intercepted by vegetation in the driest months, an RCEW LMWL for groundwater recharge (RCEW LMWL‐GWR) was also developed using precipitation from the wettest months (November through April). The RCEW LMWL (δ2H = 7.41 × δ18O – 3.09) is different from the RCEW LMWL‐GWR (δ2H = 8.21 × δ18O + 9.95) and compares favorably to other LMWLs developed for the region and climate. Comparative surface, spring, and subsurface water datasets within the RCEW‐CZO are more similar to precipitation during the wettest months than dry months, illustrating that some semi‐arid hydrologic systems may most appropriately be compared to MWLs developed from precipitation only from the wettest season.

High-alpine environments are particularly sensitive to changes driven by climate change and experience more dramatic shifts in vegetation, snowmelt timing, and the relative ratio of rain to snow compared to other lower-elevation environments. These shifts drive changes in stream discharge and solute concentrations, long-term records of which may be archived in publicly available databases. Here, we use three decades of discharge and water quality data from two alpine watersheds along the Continental Divide in the Rocky Mountains of Colorado, USA, to quantify temporal trends in solute concentration and solute mass flux, which serve as integrators of watershed processes and are used to identify controls on how these watersheds respond to climate change over decadal timescales. By analyzing both solute concentrations and mass flux we are able to remove the effects of seasonal changes in discharge and separate hydrologic and geochemical drivers of changes in solute export from these two watersheds. While we find that concentrations of calcium, bicarbonate, and sulfate increase through time in both watersheds, increasing solute mass flux is found in one watershed but not the other, despite similar watershed characteristics such as elevation, precipitation, average temperature, and bedrock geology. We identify different dominant weathering mechanisms as the cause for the differences in watershed response to climate change. In one watershed, sulfide oxidation was the dominant weathering mechanism at the beginning of the record and stayed dominant through the three-decade period of data. This consistency in weathering mechanism likely controls why the solute flux did not change significantly. In contrast, in the other watershed, solute flux increased and water chemistry shows that the dominant weathering mechanism shifted from dominantly CO2-driven to more influence from sulfide-oxidation driven weathering. This shift in weathering mechanism is accompanied by significantly increasing solute fluxes. This study demonstrates the importance of quantifying geological weathering in watershed response to climate change where two similar watersheds exhibit different responses--one hydrological and one combined hydrological and geochemical--that could not have been predicted from a simple analysis of the watershed characteristics. Such analyses are needed on a large scale to quantify the type and magnitude of watershed changes in water quality and quantity to climate change, and suggest that weathering mechanisms, in particular weathering driven by oxidation of trace sulfide minerals, plays an important role in the geochemical response of watersheds to climate change.

The seminal studies of Feth et al. (1964) and Garrels and Mackenzie (1967) describe the chemical weathering processes controlling the geochemistry of spring waters in the Sierra Nevada (CA) and provide a framework for understanding geochemical weathering processes at local groundwater scales (i.e., short distances between recharge and subsequent groundwater discharge). Here, we extend these concepts to investigate the factors controlling geochemical evolution at the intermediate, mountain-block scale (i.e., increased flowpath length, circulation depth, and rock-water interaction). We accomplish this by applying a multi-tracer approach to mountain-front springs emerging along the Sierra Nevada frontal fault zone in Owens Valley, CA. These springs emerge at a significantly lower elevation (1100–2000 mamsl) than the eastern Sierra crest (4000+ mamsl) and provide a window into the hydrogeological and hydrochemical processes occurring within the mountain block from high-elevation mountain-block recharge to low-elevation mountain-front discharge, a recognized knowledge gap in hydrogeology. We delineate approximate spring contributing areas and identify geologic units likely sourcing springflow using stable isotopes of water and dissolved noble gases. We then classify four major geochemical groups after identifying the likely geologic units sourcing springflow and subsequent analysis and modeling of spring geochemistry. Our results lead to three main conclusions: 1) geochemical evolution within the mountain block from high elevation mountain block weathering to mountain front discharge follows power-law weathering relationships and becomes increasingly dependent on the dissolution of disseminated calcite present in plutonic rocks with increasing flowpath length, 2) geologic heterogeneity (i.e., differences in plutonic compositions and the presence/absence of Paleozoic metasedimentary roof pendants) exerts a dominant control on geochemical evolution with increased flowpath length, and 3) within geochemical groups, simple metrics like TDS or mole transfers from inverse geochemical models scale with physical and isotopic indicators of groundwater circulation and flowpath length.

Stream solute concentrations are a function of both geochemical reactions that produce solutes and the magnitude of discharging

Non-perennial streams comprise over half of the global stream network and impact downstream water quality. Although aridity is a primary driver of stream drying globally, surface flow permanence varies spatially and temporally within many headwater streams, suggesting that these complex drying patterns may be driven by topographic and subsurface factors. Indeed, these factors affect shallow groundwater flows in perennial systems, but there has been only limited characterisation of shallow groundwater residence times and groundwater contributions to intermittent streams. Here, we asked how groundwater residence times, shallow groundwater contributions to streamflow, and topography interact to control stream drying in headwater streams. We evaluated this overarching question in eight semi-arid headwater catchments based on surface flow observations during the low-flow period, coupled with tracer-based groundwater residence times. For one headwater catchment, we analysed stream drying during the seasonal flow recession and rewetting period using a sensor network that was interspersed between groundwater monitoring locations, and linked drying patterns to groundwater inputs and topography. We found a poor relationship between groundwater residence times and flowing network extent (R-2 < 0.24). Although groundwater residence times indicated that old groundwater was present in all headwater streams, surface drying also occurred in each of them, suggesting old, deep flowpaths are insufficient to sustain surface flows. Indeed, the timing of stream drying at any given point typically coincided with a decrease in the contribution from near-surface sources and an increased relative contribution of groundwater to streamflow at that location, whereas the spatial pattern of drying within the stream network typically correlated with locations where groundwater inputs were most seasonally variable. Topographic metrics only explained similar to 30% of the variability in seasonal flow permanence, and surprisingly, we found no correlation with seasonal drying and down-valley subsurface storage area. Because we found complex spatial patterns, future studies should pair dense spatial observations of subsurface properties, such as hydraulic conductivity and transmissivity, to observations of seasonal flow permanence.