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91 results for “hydraulic data”
Data and R code for "Negative effects of wind on plant hydraulics at the global scale"
<p>To minimize ontogenetic and methodological variation, we only included trait data that met the following criteria: (a) plants were grown in natural ecosystems, excluding greenhouse and common garden experiments; (b) measurements were made on adult plants and not on seedlings; (c) hydraulic traits were measured on terminal stem or branch segments in the sapwood at the crown; and (d) trait data were calculated as the mean value for each species at the same site when data were from multiple sources.</p> <p>Climate data were obtained either from the original reports or from WorldClim version 2 (http://worldclim.org/version2) if the original data were not available. The following variables were extracted from WorldClim: mean annual wind speed, mean annual precipitation, mean annual temperature, precipitation seasonality, temperature seasonality, precipitation of driest month, and minimum temperature of coldest month. The VPD data was extracted from the TerraClimate dataset (http://www.climatologylab.org/terraclimate.html). Annual PET (potential evapotranspiration) data were extracted from the CGIAR-CSI consortium (http://www.cgiar-csi.org/data). The moisture index (MI) is the ratio of precipitation to PET.</p> <p>Simple linear regression was used to examine the relationships between two variables, utilizing the 'lm' function in R software. Partial regression analysis was conducted using the R package VISREG to investigate the relationships between wind speed and plant hydraulics while controlling for other variables. This analysis helped to illustrate the independent effect of wind on plant hydraulics. The Random Forest machine-learning algorithm (implemented using the R package randomForest) was utilized to assess the relative importance of environmental variables for each plant hydraulic trait. The Mean Decrease in Gini was calculated as the average of a variable's total decrease in node impurity, taking into account the proportion of samples that reach that node in each individual decision tree in the random forest. This provides a measure of a variable's importance in estimating the value of the target variable across all of the trees in the forest. A higher Mean Decrease in Gini value indicates greater importance of the variable. Multiple regression analyses were performed to develop predictive equations for plant hydraulic traits using environmental variables. To test for hydraulic traits-wind speed slope directions and differences among species groups in different climatic regions, we used standardized major axis (SMA) analyses. The R package SMATR was employed for these analyses. We considered <em>p </em>< 0.05 as the threshold for statistical significance in all models.</p>
Data for: Phenotypic variation of hydraulic traits for woody species
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Data from: Friction of Longmaxi shale gouges and implications for seismicity during hydraulic fracturing
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Data from: Linking coordinated hydraulic traits to drought and recovery responses in a tropical montane cloud forest
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Data from: Pushing the limits to tree height: could foliar water storage compensate for hydraulic constraints in Sequoia sempervirens
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Data from: Convergence in resource use efficiency across trees with differing hydraulic strategies in response to ecosystem precipitation manipulation
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Data from: Initial hydraulic failure followed by late-stage carbon starvation leads to drought-induced death in tree, Trema orientalis
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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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Data from: Causes of ecological gradients in leaf margin entirety: Evaluating the roles of biomechanics, hydraulics, vein geometry, and bud packing
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Data from: Radial variation of wood functional traits reflect size-related adaptations of tree mechanics and hydraulics
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Data from: Anatomical and hydraulic responses to desiccation in emergent conifer seedlings
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Data from: Insular woody daisies (Argyranthemum , Asteraceae) are more resistant to drought-induced hydraulic failure than their herbaceous relatives
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WASHTREET - Hydraulic, wash-off and sediment transport experimental data obtained in an urban drainage physical model
<p><strong>WASHTREET</strong><strong> -</strong> <strong>Hydraulic, wash-off and sediment transport experimental data obtained in an urban drainage physical model.</strong></p> <p>This dataset contains the results from the tests carried out at a laboratory physical model in the Hydraulic Laboratory of the Centre for Technological Innovation in Construction and Civil Engineering (CITEEC) at the University of A Coruña (Spain) as part of the <a href="https://zenodo.org/communities/washtreet">WASHTREET project</a>. The objective of the project is to perform a series of high-resolution experiments where urban surface wash-off and sediment transport through gully pots and pipes were accurately measured in laboratory-controlled conditions in a separate drainage system.</p> <p>The experimental facility is a 36 m2 full-scale street section and consists of a rainfall simulator placed over a concrete street surface with two gully pots that drain runoff into an underground pipe system. Further details of the physical model are provided in ‘1_Physical_model_description.pdf’. Two zip files with rain intensity distributions (‘2_Rain_intensity_maps.zip’) and model topographies (‘3_Elevation_data.zip’) complete physical model information as accurately measured inputs for hydraulic, wash-off and sediment transport experiments. ‘4_Hydraulic_tests_description.pdf’ describes experimental procedure, equipment, measuring points, results and data set files of the hydraulic characterization of the experiments. Data regarding these hydraulic tests is included in ‘5_Hydraulic_tests.zip’. In these tests, flow in both gully pots and in the pipe system outlet, and a total of 6 surface and 6 pipe depths were measured by ultrasound distance sensors for the different simulated rains.</p> <p>‘6_Washoff_tests_description.pdf’ includes information of the experimental initial conditions, the different sediment granulometries used, measuring points, experimental procedure and result files regarding wash-off and sediment transport experiments. Data files of a total of 23 tests are included in ‘7_Wash-off_tests.zip’. In these experiments, an initial mass of sediment is distributed over the model surface, and the wash-off and sediment transport processes are measured during a steady and uniform rainfall by total suspended solids (TSS) and particle size distribution (PSD) samples at the entrance of gully pots and at the pipe system outlet. Online turbidity measurements at pipe system outlet, pipe depths and flow at pipe system outlet are also measured during the experiments. Results regarding mass balances, which are performed at the end of the experiment to assess the final distribution of sediments, are also included. At last, some relevant photos and videos taken during the experiments are provided in ‘8_Multimedia.zip’. </p> <p>Flow measurements have been used in Naves et al. (2019) (DOI: <a href="https://doi.org/10.1016/j.jhydrol.2019.05.003">10.1016/j.jhydrol.2019.05.003</a>), together with the related datasets <a href="http://www.doi.org/10.5281/zenodo.3239401">WASHTREET - PIV data</a> and <a href="http://www.doi.org/10.5281/zenodo.3241337">WASHTREET - Structure from Motion data</a>, to calibrate a 2D shallow water model.</p> <p>The WASHTREET project is being developed in the scope of the PhD thesis of the first author, which is in receipt of a Spanish Ministry of Science, Innovation and Universities predoctoral grant [FPU14/01778]. The project also receive funding from the Spanish Ministry of Science, Innovation and Universities under POREDRAIN project RTI2018-094217-B-C33 (MINECO/FEDER-EU)</p> <p> </p> <p>Derived publications:</p> <ul> <li>Naves, J., Anta, J., Suárez, J., & Puertas, J. (2020). Hydraulic, wash-off and sediment transport experiments in a full-scale urban drainage physical model. <em>Scientific Data</em>, <em>7</em>(1), 1-13. <a href="https://doi.org/10.1038/s41597-020-0384-z">https://doi.org/10.1038/s41597-020-0384-z</a></li> <li>Naves, J., Rieckermann, J., Cea, L., Puertas, J., & Anta, J. (2020). Global and local sensitivity analysis to improve the understanding of physically-based urban wash-off models from high-resolution laboratory experiments. <em>Science of The Total Environment</em>, <em>709</em>, 136152. <a href="https://doi.org/10.1016/j.scitotenv.2019.136152">https://doi.org/10.1016/j.scitotenv.2019.136152</a></li> <li>Naves, J., Anta, J., Puertas, J., Regueiro-Picallo, M., & Suárez, J. (2019). Using a 2D shallow water model to assess Large-Scale Particle Image Velocimetry (LSPIV) and Structure from Motion (SfM) techniques in a street-scale urban drainage physical model. <em>Journal of Hydrology</em>, <em>575</em>, 54-65. <a href="https://doi.org/10.1016/j.jhydrol.2019.05.003">https://doi.org/10.1016/j.jhydrol.2019.05.003</a></li> <li>Naves, J., Anta, J., Suárez, J., & Puertas, J. (2020). Development and Calibration of a New Dripper-Based Rainfall Simulator for Large-Scale Sediment Wash-Off Studies. <em>Water</em>, <em>12</em>(1), 152. <a href="https://doi.org/10.3390/w12010152">https://doi.org/10.3390/w12010152</a></li> </ul>
Data from: Evaluation of parametric and nonparametric machine-learning techniques for prediction of saturated and near-saturated hydraulic conductivity
Parametric and nonparametric supervised machine learning techniques were used to estimate saturated and near saturated hydraulic conductivities (Ks, K10) from easily measurable soil properties including name of pedological horizon (HOR), soil texture (sand, silt & clay), organic matter (OM), bulk density (BD) and water contents (θpF1, θpF2, θpF3 and, θpF4.2) measured at four different matric heads (-10, -100, -1000, and -15848 cm). Using a stepwise linear model (SWLM) and the Lasso regression as parametric methods with 316 data in training and 135 data in testing phase, four pedotransfer functions (PTFs) were obtained in which water contents for both methods play an important role compared to other variables. SWLM showed better performance than Lasso in the testing phase for log(Ks) and log(K10) prediction with RMSE of 0.666 and 0.551 cm d-1 and R2 of 0.26 and 0.65. Nonparametric supervised machine learning methods trained and tested with similar data set significantly improved the accuracy of Ks prediction with R2 of 0.52, 0.36 and 0.53 for Gaussian regression process (GPR), support vector machine (SVM) and Ensemble (ENS) method in the testing stage. These methods also described 74.9, 66.7 and 72.5% of the variation of log(K10). Bootstrapping method validated the strong performance of nonparametric techniques. Feature selection capability of GPR determined that instead of using a model with all predictors, HOR, silt, θpF1 and θpF3 are sufficient for the prediction of log(Ks) or log(K10), HOR, silt, and OM can predict as accurate as the comprehensive model with all variables.
Data from: Leaf photosynthetic, economics and hydraulic traits are decoupled among genotypes of a widespread species of eucalypt grown under ambient and elevated CO2
Leaf economics and hydraulic traits strongly influence photosynthesis. While the level of coordination among these traits can differ between sets of species, leaf functional trait coordination within species remains poorly understood. Furthermore, elevated concentrations of atmospheric CO2 commonly influence the expression of leaf photosynthetic, economics and hydraulic traits in contrasting ways, yet the effect of variable concentrations of atmospheric CO2 on patterns of trait coordination within species remains largely untested. We examined the relationships among key leaf photosynthetic (e.g. net photosynthesis and photosynthetic biochemistry), economics and water-use (e.g. leaf mass per unit area and stomatal conductance) and hydraulic traits (e.g. vein density) in 14 genotypes of Eucalyptus camaldulensis grown in ambient (aCO2) and elevated (eCO2) [CO2]. We examined the level of coordination among leaf traits in aCO2 and then assessed whether growth in eCO2 altered that coordination. We found that leaf traits related to photosynthetic capacity, economics and water-use, and hydraulics were decoupled among genotypes grown in aCO2, yet strong relationships were generally observed among suites of traits within each 'functional group'. Significant responses to growth in eCO2 were observed for most leaf photosynthetic and economics and water-use traits, with the magnitude and direction of the response varying among traits. In contrast, leaf hydraulics traits were unaffected by variable growth CO2. Despite this, growth in eCO2 did not substantially alter patterns of leaf trait coordination observed in aCO2. These results suggest suites of leaf traits associated with photosynthetic capacity, economics and water-use and hydraulics, respectively, can form independent axes of variation among genotypes of a single species, regardless of growth CO2. Although growth in eCO2 did not substantially alter patterns of trait coordination, decoupling of leaf functional traits among genotypes may allow genetically distinct populations to produce novel combinations of traits that may be adaptive in response to changes in their local environment.
Supplementary Data for Manuscript "Examining the mid to long-term variability in saturated hydraulic conductivity of sandy soils and its influencing factors under constant head test in the laboratory"
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Data set for hydraulic fracture interactions with discontinuities study
<p>Data set used to generate results for hydraulic fracture interaction with discontinuities study</p>
Supporting Data:A pleiotropic 'stretch' phenotype is associated with metaxylem vessel element length, axial hydraulic conductance, root elongation, water utilization, and drought adaptation in maize.
<p>These data were collected to assess how xylem perforation plates affect water use strategies in maize (<em>Zea mays </em>L.) under water deficit through empirical studies in controlled environments and in the field. In this work, our goals were to explore the extent of intraspecific variation for the structure of perforation plates within an annual monocot and assess how this variation affects transport and use of water under drought stress. Specifically, we test the hypotheses that (1) simple perforation plates have a significant effect on water transport, (2) intraspecific variation exists for these features in maize, and (3) this variation affects water use strategies under drought stress. </p>
Hydraulic Data from pumping tests in the projects STIMTEC and STIMTEC-X
<p>Hydraulic Data from pumping tests, i.e., injection and production, and pressure monitoring in various boreholes drilled in Reiche Zeche (Freiberg, Germany) during the projects STIMTEC and STIMTEC-X</p>
Supporting information and data for "Chapter 1: Constraining Hydraulic Permeability at Great Depth by Using Magnetotellurics" in Pepin JD (2019) New Approaches to Geothermal Resource Exploration and Characterization (PhD dissertation)
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Allen Brain Atlas
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International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
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