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Abstract 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. 

Abstract. Large sample datasets are transforming the catchment sciences, but there are few off-the-shelf stream water chemistry datasets with complementary atmospheric deposition, streamflow, meteorology, and catchment physiographic attributes. The existing CAMELS (Catchment Attributes and Meteorology for Large-sample Studies) dataset includes data on topography, climate, streamflow, land cover, soil, and geology across the continental US. With CAMELS-Chem, we pair these existing attribute data for 516 catchments with atmospheric deposition data from the National Atmospheric Deposition Program and water chemistry and instantaneous discharge data from the US Geological Survey over the period from 1980 through 2018 in a relational database and corresponding dataset. The data include 18 common stream water chemistry constituents: Al, Ca, Cl, dissolved organic carbon, total organic carbon, HCO3, K, Mg, Na, total dissolved N, total organic N, NO3, dissolved oxygen, pH (field and lab), Si, SO4, and water temperature. Annual deposition loads and concentrations include hydrogen, NH4, NO3, total inorganic N, Cl, SO4, Ca, K, Mg, and Na. We demonstrate that CAMELS-Chem water chemistry data are sampled effectively across climates, seasons, and discharges for trend analysis and highlight the coincident sampling of stream constituents for process-based understanding. To motivate their use by the larger scientific community across a variety of disciplines, we show examples of how these publicly available datasets can be applied to trend detection and attribution, biogeochemical process understanding, and new hypothesis generation via data-driven techniques. 

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. 

Soil biota generate CO2 that can vertically export to the atmosphere, and dissolved organic and inorganic carbon (DOC and DIC) that can laterally export to streams and accelerate weathering. These processes are regulated by external hydroclimate forcing and internal structures (permeability distribution), the relative influences of which are rarely studied. Understanding these interactions is essential a hydrological extremes intensify in the future. Here we explore the question: How and to what extent do hydrological and permeability distribution conditions regulate soil carbon transformations and chemical weathering? We address the questions using a hillslope reactive transport model constrained by data from the Fitch Forest (Kansas, United States). Numerical experiments were used to mimic hydrological extremes and variable shallow-versus-deep permeability contrasts. Results demonstrate that under dry conditions (0.08 mm/day), long water transit times led to more mineralization of organic carbon (OC) into inorganic carbon (IC) form (>98\%). Of the IC produced, ~ 75\% was emitted upward as CO2 gas and ~ 25\% was exported laterally as DIC into the stream. Wet conditions (8.0 mm/day) resulted in less mineralization (~88\%), more DOC production (~12\%), and more lateral fluxes of IC (~50\% of produced IC). Carbonate precipitated under dry conditions and dissolved under wet conditions as the fast flow rapidly droves the reaction to disequilibrium. The results depict a conceptual hillslope model that prompts four hypotheses for our community to test. H1: Droughts enhance carbon mineralization and vertical upward carbon fluxes, whereas large hydrological events such as storms and flooding enhance subsurface vertical connectivity, reduce transit times, and promote lateral export. H2: The role of weathering as a net carbon sink or source to the atmosphere depends on the interaction between hydrologic flows and lithology: transition from droughts to storms can shift carbonate from a carbon sink (mineral precipitation) to carbon source (dissolution). H3: Permeability contrasts regulate the lateral flow partitioning via shallow flow paths versus deeper groundwater though this alter reaction rates negligibly. H4: Stream chemistry reflect flow paths and can potentially quantify water transit times: solutes enriched in shallow soils have a younger water signature; solutes abundant at depth carry older water signature. 

Abstract. Carbonate weathering is essential in regulating atmosphericCO2 and carbon cycle at the century timescale. Plant roots accelerateweathering by elevating soil CO2 via respiration. It however remainspoorly understood how and how much rooting characteristics (e.g., depth anddensity distribution) modify flow paths and weathering. We address thisknowledge gap using field data from and reactive transport numericalexperiments at the Konza Prairie Biological Station (Konza), Kansas (USA), asite where woody encroachment into grasslands is surmised to deepen roots. Results indicate that deepening roots can enhance weathering in two ways.First, deepening roots can control thermodynamic limits of carbonatedissolution by regulating how much CO2 transports vertical downward tothe deeper carbonate-rich zone. The base-case data and model from Konzareveal that concentrations of Ca and dissolved inorganic carbon (DIC) areregulated by soil pCO2 driven by the seasonal soil respiration. Thisrelationship can be encapsulated in equations derived in this workdescribing the dependence of Ca and DIC on temperature and soil CO2. The relationship can explain spring water Ca and DIC concentrations from multiple carbonate-dominated catchments. Second, numericalexperiments show that roots control weathering rates by regulating recharge(or vertical water fluxes) into the deeper carbonate zone and exportreaction products at dissolution equilibrium. The numerical experimentsexplored the potential effects of partitioning 40 % of infiltrated waterto depth in woodlands compared to 5 % in grasslands. Soil CO2 datasuggest relatively similar soil CO2distribution over depth, which in woodlands and grasslands leads only to 1 % to∼ 12 % difference inweathering rates if flow partitioning was kept the same between the two landcovers. In contrast, deepening roots can enhance weathering by ∼ 17 % to200 % as infiltration rates increased from 3.7 × 10−2 to 3.7 m/a. Weathering rates in these cases however are more than an order of magnitude higher than a case without roots atall, underscoring the essential role of roots in general. Numericalexperiments also indicate that weathering fronts in woodlands propagated> 2 times deeper compared to grasslands after 300 years at aninfiltration rate of 0.37 m/a. These differences in weathering fronts areultimately caused by the differences in the contact times of CO2-charged water with carbonate in the deep subsurface. Within the limitation of modeling exercises, these data and numerical experiments prompt the hypothesis that (1) deepening roots in woodlands can enhance carbonate weathering by promotingrecharge and CO2–carbonate contact in the deepsubsurface and (2) the hydrological impacts of rooting characteristics canbe more influential than those of soil CO2 distribution in modulatingweathering rates. We call for colocated characterizations of roots,subsurface structure, and soil CO2 levels, as well as their linkage to waterand water chemistry. These measurements will be essential to illuminatefeedback mechanisms of land cover changes, chemical weathering, globalcarbon cycle, and climate. 

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.