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This dataset contains the codes and data used in the manuscript “Influence of Subsurface Critical Zone Structure on Hydrological Partitioning in Mountainous Headwater Catchments” submitted to Geophysical Research Letters. The software requirement are summarized in requirement.txt; hydrologic modeling input data are in the folder TLnewtest2sfb2; the observation data used in the simulation are indicated as comments in the python scripts. Note that the hydrologic modeling was run in HPC (Linux system) with parallel computing. Below are the abstract of the manuscript: “Headwater catchments play a vital role in regional water supply and ecohydrology, and a quantitative understanding of the hydrological partitioning in these catchments is critically needed, particularly under a changing climate. Recent studies have highlighted the importance of subsurface critical zone (CZ) structure in modulating the partitioning of precipitation in mountainous catchments; however, few existing studies have explicitly taken into account the 3D subsurface CZ structure. In this study, we designed realistic synthetic catchment models based on seismic velocity-estimated 3D subsurface CZ structures. Integrated hydrologic modeling is then used to study the effect of the shape of the weathered bedrock bottom on various hydrologic fluxes and storages in mountainous headwater catchments. Numerical results show that the shape of the weathered bedrock bottom not only affects the magnitude but also the peak time of both streamflow and subsurface dynamic storage.” 

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 The size and spatial distribution of soil structural macropores impact the infiltration, percolation, and retention of soil water. Despite the assumption often made in hydrologic flux equations that these macropores are rigid, highly structured soils can respond quickly to moisture variability‐induced shrink‐swell processes altering the size distribution of these pores. In this study, we use a high‐resolution (180 m) laser imaging technique to measure the average width of interpedal, planar macropores from intact cross sections and relate it to matrix water content. We also develop an expression for unsaturated hydraulic conductivity that accounts for dynamic macropore geometries and propose a method for partitioning sensor soil water content data into matrix and macropore water contents. The model was applied to a soil in northeastern Kansas where soil monoliths had been imaged to quantify macropore properties and continuous water content data were collected at three depths. Model‐predicted macropore width showed significant sensitivity to matrix water content resulting in changes of 15%–50% of maximum width over the 15‐month period of record. Transient saturated hydraulic conductivity predicted from the model compared favorably to a previously developed model accounting for moisture‐induced changes to structural unit porosity. Following periods of low soil moisture, infiltrating meteoric water filled highly conductive macropores increasing by several orders of magnitude which subsequently decreased as water was absorbed into the matrix and macropores drained. This model offers a means by which to combine measurable morphological data with soil moisture sensors to monitor dynamic hydraulic properties of soils susceptible to shrink‐swell processes. 

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 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. 

Abstract Rooting depth is an ecosystem trait that determines the extent of soil development and carbon (C) and water cycling. Recent hypotheses propose that human‐induced changes to Earth's biogeochemical cycles propagate deeply into Earth's subsurface due to rooting depth changes from agricultural and climate‐induced land cover changes. Yet, the lack of a global‐scale quantification of rooting depth responses to human activity limits knowledge of hydrosphere‐atmosphere‐lithosphere feedbacks in the Anthropocene. Here we use land cover data sets to demonstrate that root depth distributions are changing globally as a consequence of agricultural expansion truncating depths above which 99% of root biomass occurs (D99) by ∼60 cm, and woody encroachment linked to anthropogenic climate change extending D99 in other regions by ∼38 cm. The net result of these two opposing drivers is a global reduction of D99 by 5%, or ∼8 cm, representing a loss of ∼11,600 km³of rooted volume. Projected land cover scenarios in 2100 suggest additional future D99 shallowing of up to 30 cm, generating further losses of rooted volume of ∼43,500 km³, values exceeding root losses experienced to date and suggesting that the pace of root shallowing will quicken in the coming century. Losses of Earth's deepest roots—soil‐forming agents—suggest unanticipated changes in fluxes of water, solutes, and C. Two important messages emerge from our analyses: dynamic, human‐modified root distributions should be incorporated into earth systems models, and a significant gap in deep root research inhibits accurate projections of future root distributions and their biogeochemical consequences. 

Abstract Understanding soil organic carbon (SOC) response to global change has been hindered by an inability to map SOC at horizon scales relevant to coupled hydrologic and biogeochemical processes. Standard SOC measurements rely on homogenized samples taken from distinct depth intervals. Such sampling prevents an examination of fine‐scale SOC distribution within a soil horizon. Visible near‐infrared hyperspectral imaging (HSI) has been applied to intact monoliths and split cores surfaces to overcome this limitation. However, the roughness of these surfaces can influence HSI spectra by scattering reflected light in different directions posing challenges to fine‐scale SOC mapping. Here, we examine the influence of prescribed surface orientation on reflected spectra, develop a method for correcting topographic effects, and calibrate a partial least squares regression (PLSR) model for SOC prediction. Two empirical models that account for surface slope, aspect, and wavelength and two theoretical models that account for the geometry of the spectrometer were compared using 681 homogenized soil samples from across the United States that were packed into sample wells and presented to the spectrometer at 91 orientations. The empirical approach outperformed the more complex geometric models in correcting spectra taken at non‐flat configurations. Topographically corrected spectra reduced bias and error in SOC predicted by PLSR, particularly at slope angles greater than 30°. Our approach clears the way for investigating the spatial distributions of multiple soil properties on rough intact soil samples.