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26 results for “hydraulic properties”
Dataset of Soil hydraulic properties of Valle Telesina (Italy)
<p>The dataset contain a .xls file with the hydraulic properties georeferenced of 47 soil profiles of the "Valle Telesina (Italy) site, according to the parametrization of the van Genuthen-Mualem model (van Genuchten, 1980). Moreover a zipped folder with the shape files for the same area is provided.</p> <p>Following there is the description of the methods applied for the soil hydraulic characterization:</p> <p>Undisturbed soil samples were collected from the horizons using cylindrical steel samplers (8.5 cm diameter and 12.0 cm high). In the laboratory, the samples were saturated by slowly wetting from the bottom in order to remove all the air entrapped in the soil. The maximum water content,θ<sub>0</sub>, was gravimetrically determined and the saturated hydraulic conductivity, ks, was measured by a falling-head permeameter. Then, the Wind method was applied to simultaneously determine the water retention and hydraulic conductivity functions by subjecting the soil samples to an evaporation process. After sealing the bottom surface to prevent drainage, during the evaporation process - at appropriate pre-set time intervals - the weight of the whole sample and the pressure head at three different depths were measured. An iterative procedure was applied for estimating the water retention curve from these measurements. Then, the instantaneous profile method was applied to determine the unsaturated hydraulic conductivity. θr, θs, α and n parameters were derived by fitting the soil water retention data; under the restriction m=l−l/n, τ and k<sub>0</sub> parameters were derived by fitting the hydraulic conductivity data. Details of the tests and overall calculation procedures are described in Basile et al. (2012). The parameters obtained in the laboratory were then scaled to better reproduce the field behaviour by following the procedure suggested by Basile et al. (2003; 2006). Finally, for the few soils having considerable stone content, a correction of θs and k<sub>0</sub>, to take into account the stoniness, was applied (Coppola et al., 2013).</p> <p>References:</p> <p>Van Genuchten, M. T. (1980). A closed-form equation for predicting the hydraulic conductivity of unsaturated soils. Soil Science Society of America Journal, 44(5), 892–898.</p> <p>Basile, A., Buttafuoco, G., Mele, G., & Tedeschi, A. (2012). Complementary techniques to assess physical properties of a fine soil irrigated with saline water. Environmental Earth Sciences,66(7), 1797–1807.</p> <p>Basile, A., Ciollaro, G., & Coppola, A.(2003). Hysteresis in soil water characteristics as a key to interpreting comparisons of laboratory and field measuredhydraulic properties.Water Resources Research, 39(12).</p> <p>Basile, A., Coppola, A., De Mascellis, R., & Randazzo, L. (2006). Scaling approach to deduce field unsaturated hydraulic properties and behavior from laboratory measurements on small cores. Vadose Zone Journal,5(3), 1005–1016.</p> <p>Coppola, A., Dragonetti, G., Comegna, A., Lamaddalena, N., Caushi, B., Haikal, M., & Basile, A. (2013). Measuring and modeling water content in stony soils. Soil and Tillage Research,128, 9–22.</p>
Soil hydraulic and thermal properties determined in surface organic and mineral soils in the region near Toolik Lake on the North Slope of Alaska, 2016-2019
Soil cores of 5 cm diameter down to frozen soil were taken from a subset of sample sites for laboratory analysis. Determinations of hydraulic conductivity, thermal conductivity, porosity, and bulk density were made for each core. For a further subset of sites we developed soil moisture retention curves.
GeoERA RESOURCE H3O-PLUS data set which contains hydraulic properties of prime aquifers and aquitards in the Dutch-Flemish-German cross-border area
<p>Dataset which contains information about hydraulic properties of harmonized hydrogeological units in the Dutch-Flemish-German cross-border region which was compiled in the GeoERA RESOURCE project under WP3 H3O-PLUS. The harmonization of the 3D geometry of the cross-border hydrogeological units in the H3O projects constituted a major step towards a common hydrogeological dataset of the Roer Valley Graben and thus the harmonization of groundwater flow models. The database that was compiled provides the characterization of these hydrogeological units with respect to their hydraulic properties, primarily their hydraulic conductivity.<br> The associated report and appendices describe the database of hydraulic properties of aquifers and aquitards based on common criteria. Attention is also given to the characterization of hydraulic properties of faults.</p>
Hydraulic Properties of Expansive Yazoo Clay subjected to wet dry cycles
<p>The data file includes the investigation of the behavior of yazoo clay under different wet-dry cycles. The investigation was conducted using laboratory testing and numerical analysis.</p>
Dataset on soil hydraulic properties under contrasted plant covers and agricultural practices
<p>Complete dataset on the temporal variation of soil infiltrability along a homogeneous fluvisol, on bare soil or soil planted with two plant species with contrasted root systems (a Malvaceae with a tap-root system and a Poaceae with a fibrous root system), and impacted by three different management practices (burning, mowing, and chemical weeding). An original protocol, based on specific ring infiltrometers, able to measure the temporal dynamics of soil infiltrability was used. This dispositive takes into account the variability of the measurement across space.</p> <p> </p>
Data from: The PDI model system for parameterizing soil hydraulic properties
<p>The PDI ("Peters-Durner-Iden") model system represents a robust framework for parameterizing soil hydraulic properties, i.e. the water retention curve and the hydraulic conductivity curve, across the entire soil moisture spectrum. This model accounts for water retention and hydraulic conductivity in completely and partially-filled pores, including adsorption and film-flow. The model was developed in stages and a comprehensive overview of the model development and the model equations is provided in Peters et al. (2024). In this repository, we provide a Python file named "pdi.py" which can be used to compute the various submodels (PDI-VG, PDI-KOS, PDI-FX, ...) of the PDI model system. One MS Excel file is provided for easy access to one PDI model, the PDI-VG. The PYTHON functions contained in "pdi.py" can be used to calculate the water retention curve, the unsaturated hydraulic conductivity curve, the specific water capacity function, and the soil water diffusivity function. In addition, we provide five python scripts which illustrate how to call the various PDI functions in different contexts. Notably, "pdi.py" incorporates a utility function, 'export_hydrus_materin', which generates an ASCII file named "MATER.IN". This file serves as input for simulations with Hydrus-1D and Hydrus-2D3D, offering seamless integration with these simulation platforms. It's important to emphasize that the provided Python scripts and accompanying documentation are closely aligned with the research article by Peters et al. (2024). To streamline accessibility, the repository refrains from redundantly restating the theory or equations already detailed in the referenced publication.</p>
Effects of powdered cactus pear pruning amendment on the physical and hydraulic properties of two contrasting Mediterranean soils
<p>Full database.</p> <p>A production and consumption paradigm known as "circular economy" (CE) emphasizes sharing, renting, reusing, repairing, refurbishing, and, in particular, recycling materials as much as feasible. Traditional agriculture relied totally on the CE, progressively the search for maximization of yields has produced more and more by-products. Their recovery and reuse are possible with approaches that refer to the CE, for example, with the use of pruning biomasses. The cultivation of the cactus pear annually produces large quantities of pruning residues, which have been shown to be useful for the recovery and reuse of nutrients. This study investigates the hydraulic properties of benchmark soils in which this by-product is incorporated. Here we show that the amendment with powdered cactus pear pruning waste (PCPPW) positively affects soil water retention. However, observable benefits require very high amendment proportions, more than 20% by volume. These quantities make use in the open field unrealistic but offer perspectives in the horticultural and floricultural sectors. These results reveal agreement in direct comparison to what was thought to be the case previously, i.e., a decrease in soil bulk density, an increase in plant available water capacity and an increase in soil swelling. A few per cent application of PCPPW improves the drainable water capacity only in the case of not very clayey soils, where their use becomes useless. The principles of the CE are important, but they must not be pursued a priori. For example, in the use of soil amendments, the behavior in the different soils conditions the suitability of their use.</p>
Data from: The PDI model system for parameterizing soil hydraulic properties
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Mechanical and hydraulic transport properties of transverse-isotropic Gneiss deformed under deep reservoir stress and pressure conditions.
<p>"This is the ReadMe file corresponding to the study entitled: "Mechanical and hydraulic transport properties of transverse-isotropic<br> Gneiss deformed under deep reservoir stress and pressure conditions" <br> <br> "By M. Acosta, & M. Violay." <br> <br> This study has been published in the International Journal of Rock Mechanics and Mining Sciences in June 2020. <br> https://doi.org/10.1016/j.ijrmms.2020.104235<br> <br> This Read-Me file has been last edited on 2020-06-31 <br> <br> This readme file describes the data repository and supplementary files accompanying the above publication. <br> For any further queries please contact mateo.acosta@epfl.ch <br> <br> The following files are included: <br> <br> --- Regarding Figure 3. <br> <br> "1) ""Acosta_et_al_2020_Figure3Data.xlsx"" " <br> This is the processed data from the experiments described in Figure1 of the article. <br> "In this .xlsx File, each sheet corresponds to one figure panel as follows: " <br> <br> Fig.3: One experiment example<br> Column A: Axial strain in (%) ; Column B: Effective axial stress (in MPa); Column C: Axial strain for AE's in (%) ; Column D: Acoustic emission hits (in #); Column D: Axial strain for porosity change in (%) ; Column E: Porosity change (in %);</p> <p>--- Regarding Figure 4. <br> <br> "1) ""Acosta_et_al_2020_Figure4Data.xlsx"" " <br> This is the processed data from the experiments described in Figure1 of the article. <br> "In this .xlsx File, each sheet corresponds to one figure panel as follows: " <br> <br> Fig.4a&g: Beta=0deg<br> Column A: Axial strain in (%) ; Column B: Effective axial stress (in MPa); Column C: Axial strain for AE's in (%) ; Column D: Acoustic emission hits (in #); Column D: Axial strain for porosity change in (%) ; Column E: Porosity change (in %);</p> <p>Fig.4b&h: Beta=30deg<br> Column A: Axial strain in (%) ; Column B: Effective axial stress (in MPa); Column C: Axial strain for AE's in (%) ; Column D: Acoustic emission hits (in #); Column D: Axial strain for porosity change in (%) ; Column E: Porosity change (in %);</p> <p>Fig.4c&i: Beta=45deg<br> Column A: Axial strain in (%) ; Column B: Effective axial stress (in MPa); Column C: Axial strain for AE's in (%) ; Column D: Acoustic emission hits (in #); Column D: Axial strain for porosity change in (%) ; Column E: Porosity change (in %);</p> <p>Fig.4d&j: Beta=60deg<br> Column A: Axial strain in (%) ; Column B: Effective axial stress (in MPa); Column C: Axial strain for AE's in (%) ; Column D: Acoustic emission hits (in #); Column D: Axial strain for porosity change in (%) ; Column E: Porosity change (in %);</p> <p>Fig.4e&k: Beta=90deg<br> Column A: Axial strain in (%) ; Column B: Effective axial stress (in MPa); Column C: Axial strain for AE's in (%) ; Column D: Acoustic emission hits (in #); Column D: Axial strain for porosity change in (%) ; Column E: Porosity change (in %);</p> <p>Fig.4f&l: LPG<br> Column A: Axial strain in (%) ; Column B: Effective axial stress (in MPa); Column C: Axial strain for AE's in (%) ; Column D: Acoustic emission hits (in #); Column D: Axial strain for porosity change in (%) ; Column E: Porosity change (in %);</p> <p>--- Regarding all other Figures, the tables provided in the article allow reproduction of these.</p> <p> </p>
Evaporation and permeameter data hydraulic properties stony soil
<p>We used the evaporation method to determine the hydraulic conductivity and the retention curve of a soil sample. The principle of this method is to simultaneously measure the matric head at different depths and the water content of an initially saturated soil sample submitted to evaporation.</p> <p>The experiments were performed over cylindrical Plexiglas samples of 1 L (height: 65 mm), perforated at the bottom to allow saturation from below and open to atmosphere on the upper side to allow evaporation of the soil moisture. Four 6 mm-long ceramic tensiometers (SDEC230) were introduced at 10, 25, 40 and 55 mm in height, respectively denoted T1 to T4 (the reference level is located at the bottom of the sample). In order to avoid preferential flow due to the introduction of the tensiometers on a same vertical line, each hole of the sample was horizontally shifted of 12 degrees vis-à-vis the center of the tube. The tensiometers are connected through a tube to a pressure transducer (DPT-100, DELTRAN). The setup was filled with degased water. The variation in pressure of the drying soil was recorded every 15 min by a CR800 (CAMPBELL SCIENTIFIC). Tensions beyond the consolidation point were not taken into account. The consolidation point refers to the state from which the measured pressure head starts to decrease as bubbles appear and water vapour accumulates (typically 68 kPa cm in this case).</p> <p>The total water loss as a function of time was monitored by a balance (OHAUS) with a sensitivity of 0.2 g with an accuracy of 1 g with a time resolution of 15 min. A 50 W infrared lamp was positioned 1 m above the sample surface to slightly speed up the evaporation process. The light was turned off for the first 24 hours of every experiment, as the evaporation rate is already high in a saturated sample. A measuring campaign lasted until 3 of the 4 tensiometers ran dry (the tension sharply drops down to approximately a null value). At the end of the experiment, the sample was oven dried for 24 hours at 105°C to estimate the .</p>
An in situ observation dataset of soil hydraulic properties and soil moisture in a high and cold mountainous area on the northeastern Qinghai-Tibet Plateau
<p>Based on soil profile data at depths of 5 cm and 25 cm from 238 sampling sites, and on soil data from 32 soil moisture monitoring stations at depths of 5 cm, 15 cm, 25 cm, 40 cm, and 60 cm, we have compiled a soil hydraulic properties and soil moisture dataset for a high and cold mountainous area, Northeastern Qinghai-Tibet Plateau. Specifically, the soil hydraulic properties include clay, silt, sand, soil organic carbon, soil saturated hydraulic conductivity, soil water retention curve parameters (Van Genuchten model) and soil dry bulk density.</p>
GSHP: Global database of soil hydraulic properties
<p>A total of 15,259 SWCCs from 2,702 sites were assembled from published literature and other sources, standardized, and quality-checked to obtain global database of soil hydraulic properties (GSHP). The GSHP database covers most regions across the globe, with the highest number of curves from North America followed by Africa, Europe, Asia, South America, Australia/Oceania. In addition to SWCCs, other soil variables such as soil texture (12,233 measurements), bulk density (15,125 measurements), and soil organic carbon (2,255 measurements) are also listed in the database.</p> <p>The R code used for this study is available here: https://github.com/ETHZ-repositories/GSHP-database</p> <p>For more details / to cite this dataset please use:</p> <ul> <li>Gupta, S., Papritz, A., Lehmann, P., Hengl, T., Bonetti, S., and Or, D., (2022): Global Soil Hydraulic Properties dataset based on legacy site observations and robust parameterization”. Manuscript accepted to <strong>Scientific Data.</strong></li> </ul> <p>Examples of using the GSHP database to generate van Genuchten parameters maps can be found in <a href="https://doi.org/10.5281/zenodo.6343570">10.5281/zenodo.6343570</a>.</p> <p><strong>Description of the files</strong>:</p> <p>The datasets in this repository include: </p> <p><strong>WRC_dataset_surya_et_al_2021_final </strong>provides a global compilation of soil hydraulic properties and the information described in the<strong> Readme_GSHP file</strong>. <strong>Dataset_notebook </strong>shows the graphical representation of the GSHP database. </p> <p>The study was supported by ETH Zurich (Grant ETH-18 18-1). </p>
Data from: Soil hydraulic properties determined by inverse modeling of drip infiltrometer experiments extended with pedotransfer functions
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Imaging elastodynamic and hydraulic properties of in-situ fractured rock: An experimental investigation exploring effects of dynamic stressing and shearing
<p>We describe laboratory experiments to elucidate the relationship between nonlinear elasticity and permeability evolution in fractured media subjected to local stress perturbations. This study is part of an effort to image fluid pathways and fracture properties using active-source acoustic monitoring during fluid injection and shear of rough fractures. Experiments were conducted with L-shaped samples of Westerly granite fractured in-situ under tri-axial conditions with deionized water subsequently circulated through the resulting fractures. After in-situ fracturing, we separately imposed oscillations of the applied normal stress and pore pressure with amplitudes ranging from 0.2 to 1 MPa and frequencies from 0.1 to 40 Hz. During these dynamic perturbations an array of piezoelectric transducers continuously transmitted ultrasonic pulses across the fracture to monitor the evolving elastic response. We interpret the resulting evolution of elastic wave properties in the context of elastic nonlinearity and relate the estimated nonlinearity parameters to the relative change in permeability of the fractured media. Fracture roughness is then altered in-situ by shearing, with the generation of breccia and wear products. We document the evolution of permeability and fracture contact stiffness as a function of dynamic stressing and shear offset and discuss our findings in relation to fractures in Earth's crust.</p>
Dataset for Estimating soil hydraulic properties from oven-dry to full saturation using inverse modeling and shortwave infrared imaging
<p>In this repository, we provide all the datasets that are needed to reproduce the analysis conducted in the paper entitled "Estimating soil hydraulic properties from oven-dry to full saturation using inverse modeling and shortwave infrared imaging."</p> <p><br> codes: This folder contains Python codes to run the forward and inverse modeling. Install the following packages.<br> notebook, fenics, numpy, pandas, matplotlib, scipy, numdifftools, and lmfit for inverse modeling (needs to be run on Linux).<br> data: This directory contains data used in the inverse modeling.<br> gif: This directory contains GIF movies of the upward infiltration experiments.</p> <p>readme.xlsx: This file explains which data are used for each figure in the paper.</p>
Effects of Application of Recycled Chicken Manure and Spent Mushroom Substrate on Organic Matter, Acidity, and Hydraulic Properties of Sandy Soils
<p>This study aimed at examining the effects of long-term application of<br> chicken manure (CM) and spent mushroom substrate (SMS) on organic matter accumulation, acidity,<br> and hydraulic properties of soil. Two podzol soils with sandy texture in Podlasie Region (Poland)<br> were enriched with recycled CM (10 Mg ha1) and SMS (20 Mg ha1), respectively, every 1–2 years<br> for 20 years. The application of CM and SMS increased soil organic matter content at the depths<br> of 0–20, 20–40, and 40–60 cm, especially at 0–20 cm (by 102–201%). The initial soil pH increased in<br> the CM- and SMS-amended soil by 1.7–2.0 units and 1.0–1.2 units, respectively. Soil bulk density at<br> comparable depths increased and decreased following the addition of CM and SMS, respectively.<br> The addition of CM increased field water capacity (at –100 hPa) in the range from 45.8 to 117.8%<br> depending on the depth within the 0–60 cm layer. In the case of the SMS addition, the value of the<br> parameter was in the range of 42.4–48.5% at two depths within 0–40 cm. Depending on the depth, CM<br> reduced the content of transmission pores (>50 m) in the range from 46.3 to 82.3% and increased the<br> level of residual pores (<0.5 m) by 91.0–198.6%. SMS increased the content of residual pores at the<br> successive depths by 121.8, 251.0, and 30.3% and decreased or increased the content of transmission<br> and storage pores. Additionally, it significantly reduced the saturated hydraulic conductivity at<br> two depths within 0–40 cm. The fitted unsaturated hydraulic conductivity at two depths within the<br> 0–40 cm layer increased and decreased in the CM- and SMS-amended soils, respectively. The results<br> provide a novel insight into the application of recycled organic materials to sequester soil organic<br> matter and improve crop productivity by increasing soil water retention capacity and decreasing<br> acidity. This is of particular importance in the case of the studied low-productivity sandy acidic soils<br> that have to be used in agriculture due to limited global land resources and rising food demand.</p>
Data from: Quantifying in situ phenotypic variability in the hydraulic properties of four tree species across their distribution range in Europe
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WAYS TO IMPROVE THE ANTIOXIDANT PROPERTIES OF HYDRAULIC OILS FOR GROUND EQUIPMENT
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Developmental and water deficit-induced changes in hydraulic properties and xylem anatomy of tomato fruit and pedicel
<p><span>Xylem water transport from the parent plant into the fruit plays a crucial role in fruit growth, development, and quality formation. Current research on fruit hydraulics has attempted to partition the hydraulic resistance of the pathway over development. However, no consensus has been reached and this question has not been addressed in the context of changing plant and fruit water status under water deficit. We rigorously investigated the developmental changes of hydraulic property of the fruit and pedicel under well-irrigated condition and water deficit based on hydraulic measurements, fruit rehydration, dye tracing, light and electron microscopy, and flow modeling. A decline in water transport capacity did not occur in the pathway prior to the fruit, but within the fruit itself, which might lie in the xylem and/or outside-xylem pathway. The developmental pattern of pathway hydraulic resistance was not significantly influenced by water deficit. The changed xylemic water flow between the fruit and the parent plant due to a reduced driving force under water deficit could explain the reduced fruit water accumulation. This work provides new insights into the understanding of xylem water transport in fleshy fruits and its sensitivity to water deficit from a hydraulics perspective.</span></p>
Supplementary material 1 from: Dang NA, Jackson BM, Tomscha SA, Lilburne L, Burkhard K, Tran DD, Phi LH, Benavidez R (2022) Guidelines and a supporting toolbox for parameterising key soil hydraulic properties in hydrological studies and broader integrated modelling. One Ecosystem 7: e76410. https://doi.org/10.3897/oneeco.7.e76410
Supplementary Material S1
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