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The hydrological response of steep slopes catchments is strongly conditioned by the connectivity of subsurface preferential flows. The objective of this research is to investigate the role played by stemflow infiltration in subsurface water flow dynamics, focusing on a forested hillslope located in an Aleppo pine Mediterranean forest (Pinus halepensis, Mill.) located at Sierra Calderona, Valencia province, Spain. We combined stemflow artificial experiments with ground-penetrating radar (GPR) techniques as a non-invasive method to investigate stemflow-induced preferential flow paths activated by different trees and the related hydrological connectivity at the hillslope scale. Our observations allowed us to identify different dynamics associated with the initiation of stemflow and then lateral preferential flow, including the activation of connected preferential flow paths in soils that received stemflow water from different trees. These observations provided empirical evidence of the role of stemflow in the formation of lateral preferential flow networks. Our measurements allow estimations of flow velocities and new insight on the magnitude of stem-induced lateral preferential flow paths. The applied protocol offers a simple, repeatable and non-invasive way to conceptualize hillslope responses to rainstorms.

Sorptivity is a crucial parameter for modeling water infiltration into soils. Many works have related sorptivity to the soil hydraulic functions, i.e., the water retention and unsaturated hydraulic functions. Parlange's (1975) formulation is one of the most used to relate sorptivity to the soil hydraulic functions, allowing the direct computation of sorptivity as a function of the soil hydraulic parameters and initial and final water contents. On this basis, several works investigated the possibility of direct analytical relationships between sorptivity and the hydraulic shape and scale parameters (e.g., Lassabatere et al., 2021). So far, most of the studies have focused on single permeability soils with monomodal water retention and unsaturated hydraulic functions. However, the use of dual- or multi-permeability approaches is increasing in relation to the necessity to account for preferential flows in soils. The approach developed by (Gerke and van Genuchten, 1993) or (Pollacco et al., 2017) are examples of dual-permeability approaches and allow the modeling of preferential flows in soils. In the proposed study, we apply the formulation proposed by Parlange (1975) for the computation of sorptivity for dual-permeability soils, considering the approaches proposed by Gerke and van Genuchten (1993) and Pollacco et al. (2017). Our developments lead to a relation between the bulk sorptivity of the dual permeability soils to those of the matrix and the fast-flow compartments, plus additional terms. We end with the scaling of the proposed relation for investigating the effects of the matrix and fast-flow shape and scale parameters and the volumetric content occupied by the fast-flow compartment.ReferencesGerke, H. H. and van Genuchten, M. T.: A dual-porosity model for simulating the preferential movement of water and solutes in structured porous-media, 29, 305–319, 1993.Lassabatere, L., Peyneau, P.-E., Yilmaz, D., Pollacco, J., Fernández-Gálvez, J., Latorre, B., Moret-Fernández, D., Di Prima, S., Rahmati, M., Stewart, R. D., Abou Najm, M., Hammecker, C., and Angulo-Jaramillo, R.: Scaling procedure for straightforward computation of sorptivity, 2021, 1–33, https://doi.org/10.5194/hess-2021-150, 2021.Parlange, J.-Y.: On Solving the Flow Equation in Unsaturated Soils by Optimization: Horizontal Infiltration, 39, 415–418, 1975.Pollacco, J. A. P., Webb, T., McNeill, S., Hu, W., Carrick, S., Hewitt, A., and Lilburne, L.: Saturated hydraulic conductivity model computed from bimodal water retention curves for a range of New Zealand soils, 21, 2725–2737, https://doi.org/10.5194/hess-21-2725-2017, 2017.

Water-repellent soils usually experience water flow impedance during the early stage of a wetting process followed by progressive increase of infiltration rate. Current infiltration models are not formulated to describe this peculiar process. Similarly, simplified methods of soil hydraulic characterization (e.g., BEST) are not equipped to handle water-repellent soils. Here, we present an adaptation of the BEST method, named BEST-WR, for the hydraulic characterization of soils at any stage of water-repellency. We modified the Haverkamp explicit transient infiltration model, included in BEST for modeling infiltration data, by embedding a scaling factor describing the rate of attenuation of infiltration rate due to water repellency. The new model was validated using analytically generated data, involving soils with different texture and a dataset that included data from 60 single-ring infiltration tests. The scaling factor was used as a new index to assess soil water repellency in a Mediterranean wooded grassland, where the scattered evergreen oak trees induced more noticeable water repellency under the canopies as compared to the open spaces. The new index produced results in line with those obtained using the water drop penetration time test, which is one of the most widely test applied for quantifying soil water repellency persistence. Finally, we used BEST-WR to determine the hydraulic characteristic curves under both hydrophilic and hydrophobic conditions.

Sorptivity is a parameter of primary importance in the study of unsaturated flow in soils. This integral parameter is often considered for modeling the computation of water infiltration into vertical soil profiles (1D or 3D axisymmetric geometry). Sorptivity can be directly estimated from the knowledge of the soil hydraulic functions (water retention of hydraulic conductivity), using the integral formulation of Parlange (Parlange, 1975). However, it requires the prior determination of the soil hydraulic diffusivity and its numerical integration between the initial and the final saturation degrees, which may be tricky for some instances (e.g., coarse soil with diffusivity functions quasi-infinite close to saturation). In this paper, we present a specific scaling procedure for the computation of sorptivity considering slightly positive water pressure heads at the soil surface and initial dry conditions (corresponding to most water infiltration on the field). The square sorptivity is related to the square dimensionless sorptivity (referred to as cp parameter) corresponding to a unit soil (i.e., unit values of all the scaled parameters and zero residual water content) utterly dry at the initial state and saturated at the final state. The cp parameter was computed numerically and analytically for five current models: delta functions (Green and Ampt model), Brooks and Corey, van Genuchten-Mualem, van Genuchten-Burdine, and Kosugi models as a function of the shape parameters. The values are tabulated and can be easily used to determine any dimensional sorptivity value for any case. We propose brand-new analytical expressions for some of the models and validate previous formulations for the other models. Our numerical results also showed that the relation between the cp parameters and shape parameters strongly depends on the chosen model, with either increasing or decreasing trends when moving from coarse to fine soils. These results highlight the need for carefully selecting the proper model for the description of the water retention and hydraulic conductivity functions for the rigorous estimation of sorptivity. Present results show the need to understand better the hydraulic model's mathematical properties, including the links between their parameters, and, secondly, to better relate these properties to the physical processes of water infiltration into soils.

Gas diffusion is a primary driver of carbon dioxide (CO2) movement through unsaturated soils. In typical soils, high soil concentrations of CO2 caused by autotrophic and heterotrophic respiration cause the gas to primarily diffuse upward. However, karst landscapes can have subsurface CO2 sinks, both due to CaCO3 weathering and losses via underlying caves and fracture networks. In this study our objective was to quantify the magnitude and direction of CO2 fluxes in a pastured karst system located in Southwest Virginia (James Cave). Our hypotheses were: 1) the zero-flux plane, or location of maximum CO2 concentration within the soil profile, is located at deeper depths, ≥60 cm depth during warmer months of the year and located at shallower depths, ≤60 cm, during the colder months of the year, 2) the zero-flux plane will exist ˂60 cm depth at the sinkhole location more often than at the upslope locations, and 3) CO2 fluxes will be primarily upward during the growing season and primarily downward during the colder months of the year. We installed paired CO2 and soil moisture sensors at 20 cm, 40 cm, and 60 cm depths, with profiles installed in the shoulder, midslope, and bottom (i.e., sinkhole) of a hillslope adjacent to the cave entrance. The sensors recorded hourly data between 7 February 2017 and 13 September 2019. The depth of the zero-flux plane was identified by the depth of maximum CO2 concentration for each profile, while the measured concentration gradient from 20 to 60 cm was used to estimate CO2 flux with Fick’s Law. Our findings support our hypotheses that the relative location of the zero-flux plane was located more often at deeper depths during warmer months of the year and located at shallower depths, i.e. ˂60 cm, during colder months of the year. The zero-flux plane was more frequently shallow (i.e., ˂60 cm) at the sinkhole location compared to the upslope profiles. The CO2 fluxes reflected upward movement during the growing season and downward movement during the colder months of the year. We speculate that these processes reflect the influence of the underlying cave system, which may serve as a CO2 sink during colder months, when the cave becomes vented via natural convection. Altogether, these findings suggest that downward diffusion may be an important yet oft-overlooked component of carbon fluxes in karst landscapes.

Preferential flow is more the rule than the exception. Water infiltration is often led by preferential flow due to macropores, specific soil structures (e.g., aggregates, macropore networks), or lithological heterogeneity (occurrence of materials with contrasting hydraulic properties). Water infiltration in soils prone to preferential flow strongly depends on soil features below the soil surface, but also the initiation of water infiltration at the surface. When the macropore networks are not dense, with only a few macropores intercepting the soil surface, water infiltration experiments with ring size in the order of 10-15 cm diameter may overlook sampling macropore networks during some infiltration runs, minimizing the effect of macropore flow on the bulk water infiltration at the plot scale.In this study, we investigated the effect of ring size on water infiltration into soils prone to preferential flow. We used two ring sizes: small (15 cm in diameter) and large (50 cm in diameter). By doing so, we hypothesized that the large rings, sampling a more representative soil volume, will maximize the probability to intercept and activate a macropore network. In contrast, the small rings may activate the macropore network only occasionally, with other infiltration runs mainly sampling the soil matrix. Thus, the small rings are expected to provide more variable results. On the other hand, the large rings are expected to provide more homogeneous results in line with the soil's bulk infiltration capability, including all pore networks at the plot scale.Three different sites were sampled with varying types of preferential flow (macropore-induced versus lithological heterogeneity induced). The experimental plan included inserting large rings at several places in the experimental sites with a dozen small rings nearby to sample the same soil. All the rings were submitted to a similar positive constant water pressure head at the soil surface. The cumulative infiltrations were then monitored and treated with BEST algorithms to get the efficient hydraulic parameters. Note that the cumulative infiltration could not be compared directly since lateral water fluxes varied in extent and geometry between the different ring sizes. The impacts of the ring size on the magnitude of cumulative infiltration and related estimated hydraulic parameters were discussed. Our results demonstrated the impact of ring size but also the dependency of such effect on the site and the type of flow.Our results contribute to understanding preferential flow in heterogeneous soils and the complexity of its measure using regular water infiltration devices and protocols.

Time-lapse ground penetrating radar (GPR) surveys in conjunction with automated single-ring infiltration experiments can be used for non-invasive monitoring of the spatial distribution of infiltrated water and for generating 3D representations of the wetted zone. In this study we developed and tested a protocol to quantify and visualize water distribution fluxes under unsaturated and saturated conditions into layered soils. We carried out a gridded GPR survey on a 0.3-m thick sandy clay loam layer underlain by a restrictive limestone layer at the Ottava experimental station of the University of Sassari (Sardinia, IT). We firstly established a survey grid (1 m × 1 m), consisting of six horizontal and six vertical parallel survey lines with 0.2 m intervals between them. The field survey then consisted of six steps, including i) a first GPR survey, ii) a tension infiltration experiment conducted within the grid and aimed at activating only the soil matrix, iii) a second GPR survey aimed at highlighting the amplitude fluctuations between repeated GPR radargrams of the first and second surveys, due to the infiltrated water moving within the matrix flow region, iv) a single-ring infiltration experiment of the Beerkan type carried out within the grid on the same infiltration surface using a solution of brilliant blue dye (E133) and aimed to activate the whole pore network, v) a third GPR survey aimed to highlight the amplitude fluctuations between repeated GPR radargrams of the first and third surveys, due to the infiltrated water moving within the whole pore network (both matrix and fast-flow regions), and vi) the excavation of the soil to expose the wetted region. The shapes of the 3D diagrams of the wetted zones facilitated the interpretation of the infiltrometer data, allowing us to resolve water infiltration into the layered system. Finally, we used the infiltrometer data in conjunction with the Beerkan estimation of soil transfer parameter (BEST) method to determine the following capacitive indicators of soil physical quality of the upper soil layer: air capacity AC (m3 m–3), plant-available water capacity PAWC (m3 m–3), relative field capacity RFC (–), and soil macroporosity pMAC (m3 m–3). Results showed that the investigated soil was characterized by high soil aeration and macroporosity (i.e., AC and pMAC) along with low values for indicators associated with microporosity (i.e., PAWC and RFC). These findings suggest that the upper soil layer facilitates root proliferation and quickly drains excess water towards the underlying limestone layer, and, on the contrary, has limited ability to store and provide water to plant roots. In addition, the 3D diagram allowed the detection of non-uniform downward water movement through the restrictive limestone layer. The detected difference between the two layers in terms of hydraulic conductivity suggests that surface ponding and overland flow generation occurs via a saturation-excess mechanism. Indeed, percolating water may accumulate above the restrictive limestone layer and form a shallow perched water table that, in case of extreme rainfall events, could rise causing the complete saturation of the soil profile.

Increasing frequency of wildfire in humid hardwood forests make it necessary to understand the occurrence and origin of soil water repellency in these systems, as wildfire-induced soil water repellency has been observed to severely impact many biophysical processes in other forest types. In this project, we studied two sites in the Appalachian Mountains, United States, (at Mount Pleasant Wildlife Refuge, Virginia, and Chimney Rock State Park, North Carolina) where wildfires occurred in late 2016. In each site, burned and unburned soils were evaluated for actual (in the field) and potential (in the laboratory) water repellency using the water drop penetration time method. In addition, samples were analyzed for organic carbon content (measured using C/N analyzer), hydrophobic functional groups (using Fourier transform infrared, FTIR), and their rank correlations (rs) based on multiple samples collected one year after the fires. We found that soil water repellency was substantial greater in burned soils in the first months after the fire, and persisted for the entire year in the more severely burned soils. We also determined that potential water repellency was much greater than actual water repellency, and that organic carbon content and hydrophobic functional groups were significantly correlated to potential water repellency (p < 0.0001). Correlations were stronger at Mount Pleasant (0.77 < rs s < 0.70). For actual water repellency only had significant correlations with soil organic content at Mount Pleasant (p < 0.0001), and with hydrophobic functional groups (p < 0.0001) at both sites except the unburned soils at Chimney Rock. However, these correlations were weaker than with potential water repellency, likely due to the influence of soil water content. Altogether, this study provides new insight into the influence of soil organic matter and its composition on post-wildfire soil water repellency.

Stewart and Abou Najm (2018) developed a comprehensive model (SA model) for single ring infiltration that consists of a couple of two-terms explicit infiltration equations similar, in form, to the approximate expansions proposed by Haverkamp et al. (1994) (HV model). Application of SA model requires the transition time, τcrit, from transient to steady state to be known a-priori or establishing a constraint among the four constants that figure in the infiltration equations. Estimation of soil saturated hydraulic conductivity, Ks, and capillary length, λ, from single ring infiltration measurements also needs a scaling parameter referred to “a” to be known. SA model assumes this scaling parameter as a constant and fixes its value at a = 0.45. However, there is evidence that a cannot be considered a constant independent of soil type and initial water content.This study investigates some open issues related to the use of the SA model for single ring infiltration: 1) how comparable is τcrit with the maximum time, tmax, that separates transient from steady state condition in HV model; 2) how the scaling parameter a depends on different experimental conditions and how it can be related to HV parameters.Preliminary theoretical considerations showed that the two characteristic times (τcrit and tmax) are related and, for relatively dry initial conditions, parameter a depends only on the soil type and ring radius being maximum for small ring radii or soils with high capillarity (a = 1) and minimum for large rings or coarse soils (a = 0.467).An optimization procedure, with a constraint among the four infiltration constants, was applied to fit the SA model to both analytical and experimental infiltration data to derive τcrit and the associated value of a.The analytical data confirmed that the ratio τcrit/tmax was constant and equal to 1.495, regardless the combination of soil, ring diameter and initial water saturation. The calculated a values varied between 0.706 and 0.904, with a mean equal to a = 0.807, and were independent of the initial water content for saturation degrees up to approximately 0.50.Application of the optimization procedure to field data was problematic given it was successful only in 29 out of 70 infiltration tests. Fixing τcrita-priori could be advisable in this case and it was shown that two alternative empirical criteria for selecting τcrit yielded a values differing by a nearly negligible mean factor of 1.10 and significantly correlated to one another (R2 = 0.997).However, a rather high percentage of a values (45.5%) were greater than the theoretical maximum value (a = 1), and therefore were physically implausible. Excluding these values from the analysis, the mean a parameter (a = 0.735) was close to that estimated by the successful applications of the optimization procedure (a = 0.673).Therefore, consistent results were obtained by field and analytical data with a values intermediate between the suggested values in the literature (a = 0.45 and 0.91). These findings can inform parameterization choices for others working with infiltration models, and should reduce uncertainty during interpretation of infiltration measurements.

Research over the past several decades has shown that preferential flow is more the rule than the exception. However, our collective understanding of preferential flow processes has been limited by a lack of suitable methods to detect and visualize the initiation and evolution of non-uniform wetting at high spatial and temporal resolutions, particularly in real-world settings. In this study, we investigate water infiltration initiation by tree trunk and root systems. We carried out time-lapse ground penetrating radar (GPR) surveys in conjunction with a simulated stemflow event to provide evidence of root-induced preferential flow and generate a three-dimensional representation of the wetted zone.We established a survey grid (3.5 m × 5 m, with a local slope of 10.3°), consisting of ten horizontal and thirteen vertical parallel survey lines with 0.5 m intervals between them. The horizontal lines were downslope-oriented. The grid was placed around a Quercus suber L. We collected a total of 46 (2 GPR surveys × 23 survey lines) radargrams using an IDS (Ingegneria Dei Sistemi S.p.A.) Ris Hi Mod v. 1.0 system with a 900-MHz antenna mounted on a GPR cart. Two grid GPR surveys were carried out before and after the artificial stemflow experiment. In the experiment, we applied 100 L of brilliant blue dye (E133) solution on the tree trunk. The stemflow volume of 100 L corresponded to 63.2 mm of incident precipitation, considering a crown projected area of 201 m2 and a 1.3% conversion rate of rainfall to stemflow. Trench profiles were carefully excavated with hand tools to remove soil and detect both root location and size and areas of infiltration and preferential pathways on the soil profile.The majority (84.4%) of artificially applied stemflow infiltrated into the soil, while the remaining 15.6% generated overland flow, which was collected by a small v-shaped plastic channel placed into a groove previously scraped on the downhill side of the tree. The 3D diagram clearly demarcated the dimension and shape of the wetted zone, thus providing evidence of root-induced preferential flow along coarse roots. The wetted zone extended downslope up to a horizontal distance of 3 m from the trunk and down to a depth of approximately 0.7 m. Put all together, this study shows the importance of accounting for plant and trees trunk and root systems when quantifying infiltration.

Soil erosion is a major threat to soil resources, continuing to cause environmental degradation and social poverty in many parts of the world. Many field and laboratory experiments have been performed over the past century to study spatio-temporal patterns of soil erosion caused by surface runoff under different environmental conditions. However, these historical data have never been integrated together in a way that can inform current and future efforts to understand and model soil erosion at different scales. Here, we designed a database (SoilErosionDB) to compile field and laboratory measurements of soil erosion caused by surface runoff, with data coming from sites across the globe. The SoilErosionDB includes 18 columns for soil erosion related indicators and 73 columns for background information that describe factors such as latitude, longitude, climate, elevation, and soil type. Currently, measurements from 99 geographic sites and 22 countries around the world have been compiled into SoilErosionDB. We provide examples of linking SoilErosionDB with an external climate dataset and using annual precipitation to explain annual soil erosion variability under different environmental conditions. All data and code to reproduce the results in this study can be found at: Jian, J., Du, X., Stewart, R., Tan, Z. and Bond-Lamberty, B.: jinshijian/SoilErosionDB: First release of SoilErosionDB, Zenodo, https://doi.org/10.5281/zenodo.4030875, 2020b. All data are also available through GitHub: https://github.com/jinshijian/SoilErosionDB.

Preferential flow is more the rule than the exception, in particular during water infiltration experiments. In this study, we demonstrate the potential of GPR monitoring to detect preferential flows during water infiltration. We monitored time-lapse ground penetrating radar (GPR) surveys in the vicinity of single-ring infiltration experiments and created a three-dimensional (3D) representation of infiltrated water below the devices. For that purpose, radargrams were constructed from GPR transects conducted over two grids (1 m × 1 m) before and after the infiltration tests. The obtained signal was represented in 3D and a threshold was chosen to part the domain into wetted and non-wetted zones, allowing the determination of the infiltration bulb. That methodology was used to detect the infiltration below the devices and clearly pointed at nonuniform flows in correspondence with the heterogeneous soil structures. The protocol presented in this study represents a practical and valuable tool for detecting preferential flows at the scale of a single ring infiltration experiment.

The macroscopic capillary length is a critical parameter for the modeling of infiltration in single-ring experiments. Current methods to quantify this parameter either require multiple infiltration experiments, thus increasing effort and potential for error, or laboratory characterization that does not reflect field condition. We propose a simple field method for the estimation of the macroscopic capillary length, λc, from Beerkan runs (single-ring infiltration experiment with measurements of initial and saturated soil water contents). In the proposed method, we use the final portion of the cumulative infiltration, corresponding to the steady state of the water infiltration, to develop a reliable predictor of λc. The proposed model was validated using analytically generated data along with an experimental database that included 433 Beerkan runs from a wide range of conditions and types of soils. The analytical validation demonstrated the reliability of the proposed λc estimates for different soil textures and initial soil water contents. Altogether, the proposed method constitutes a simple solution for estimating λc, and it can improve our ability to estimate Ks in the field.

Many soil physical models assume a homogeneous domain and equilibrium conditions, even as decades of evidence have suggested that such states are rarely present in the real world. Instead, natural soils tend to be characterized by physical heterogeneity (e.g., macropores) and non-equilibrium movement of water, solutes and gases (e.g., preferential flow and transport), making it critical to develop physically realistic yet parsimonious descriptors of these processes. In this presentation we discuss recent advances using multi-domain descriptions of soils to model preferential flow and subsurface contaminant movement under field conditions. Here we emphasize the use of simplifying assumptions and straightforward parameterizations, and consider whether those factors constrain the ability of such models to realistically represent underlying physical mechanisms. We also discuss results of an innovative field experiment aimed at constraining macropore porosity, which is a key yet highly uncertain factor in such multi-domain models. Finally, we consider the relevant scales of these multi-domain models, and whether such approaches merit consideration in larger (e.g., hillslope- or catchment-scale) simulations.