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61 results for “soil physics”
Soil physical and chemical properties based on genetic horizon from 4 replicate pits placed around the replicate LTER control plots sampled in 1988 and 1989.
Dataset contains the following soil properties for each genetic horizon - site, Soil pit, upper and lower boundary (cm), Mg meq/100gm, Ca meq/100gm, K meq/100gm, CEC meq/100gm, pH, %C, %sand, %silt, %clay, Total %N, Total %P, % organic matter, Mn meq/100gm, Available-P ppm, %CO3, bulk density gm/cm3, Volume wt gm/m2.
Patterns of and controls over nitrogen inputs by green alder (Alnus viridis spp. fruticosa) to a secondary successional chronosequence in interior Alaska II - Soil Physical and Chemical Properties
In September of 1999 we collected soil cores to identify stage, replicate stand, canopy, and soil horizon patterns of soil physical (color, bulk density, pH) and chemical (N, C, P) parameters.
Yukon River Basin Fire and Permafrost Study: Soil physical and chemical characteristics by soil layer and year (2009-2012)
This study was designed to examine the effects of fire on permafrost across three soil landscapes in interior Alaska: rocky uplands, silty uplands, and sandy lowlands. This dataset includes information from each intensive study site on soil stratigraphy, texture, bulk density, moisture, water storage, pH, electrical conductivity, organic and inorganic carbon content, and ice content.
Soil chemical and physical property data for Green Lakes Valley, 1986.
Laboratory analyses were performed on soil samples from the Green Lakes Valley in the City of Boulder Watershed in order to characterize the chemical characteristics of the soil resource. The samples were collected during the 1986 excavations that were required during installation of zero-tension soil solution samplers.
Chemico-physical soil properties in Lilium pomponium populations
<p>Chemico-physical soil properties in <em>Lilium pomponium</em> populations. Soil data includes silt (g/kg), clay (g/kg), sand (g/kg), total nitrogen (g/kg), active carbonate (g/kg), total carbonate (g/kg), available extractable Ca (meq/100g), cation exchange capacity (meq/100g), electrical conductivity (1:5, dS.m-1), available extractable P (Olsen method, mg/kg), available extractable Mg (meq/100g), pH, available extractable K (meq/100g), carbon/nitrogen ratio, available extractable Na (meq/100g), organic matter (g/kg). Data of populations are reported in relevé locality data table</p>
Dataset of physical, biological and chemical soil properties from 10 European long-term experiments
<p>This dataset contains all measurements that were conducted within the Workpackage #2 of the SoilX Project (2022-2024). The data contains physical, chemical and biological soil parameters that were measured in ten European long-term field experiments, as well as soil management indicators calculated with the SoilManageR packager for R. Each data table contains different parameters, and they can be linked by the identifying columns (LTE, treatment, depth, block, replicate). Further information can be found in the ReadMe.txt.</p> <pre> </pre>
SMAP Daily Seamless Soil Moisture Products from 2015 to 2022 (Physics-constrained Gap-filling Method,PhyFill)
<p>The launch of Soil Moisture Active Passive (SMAP) satellite in 2015 has resulted in significant achievements in global soil moisture mapping. Nonetheless, spatiotemporal discontinuities in the soil moisture products have arisen due to the limitations of its orbit scanning gap and retrieval algorithms. To address this issue, this dataset presents a physics-constrained gap-filling method, shortly named PhyFill. The PhyFill method employs a partial convolutional neural network to explore spatial domain features of the original SMAP soil moisture data. Then, it incorporates variations in soil moisture induced by precipitation events and dry-down events as penalty terms in the loss function, thereby accounting for monotonicity and boundary constraints in the physical processes governing the dynamic fluctuations of soil moisture. The PhyFill model was applied to SMAP soil moisture data, resulting in continuous daily soil moisture data on a global scale. The core validation sites demonstrated that the reconstructed soil moisture data has a consistent ubRMSE compared with the original SMAP soil moisture data. The PhyFill method can generate globally continuous, high-accuracy soil moisture estimates, providing remarkable support for advanced hydrological applications, e.g., global soil moisture dry-down events and patterns.</p>
Physics-informed neural networks (PINNs) with unsaturated water flow models for inverse analysis of soil hydraulic parameters of layered soil profiles
<p>Information about the spatial distribution of soil hydraulic parameters is necessary for the accurate prediction of soil water flow and coupled movement of chemicals and heat at the field scale using a process-based model. Physics-informed neural networks (PINNs), which can provide physical constraints in deep learning to obtain a mesh-free solution, can be used to inversely estimate the soil hydraulic parameters from less and noisy training data. Previous studies using PINNs have successfully estimated soil hydraulic parameters for homogeneous soil but estimating such parameters of layered soil profiles where the interface depth and the parameters are unknown still has some difficulties. The objective of this study was to develop PINNs to inversely estimate the distribution of soil hydraulic parameters, such as saturated hydraulic conductivity and <em>α</em> and <em>n</em>, of the Mualem-van Genuchten model directly within layered soil profiles by predicting changes in pressure head from training data based on simulation results at given depths during infiltration. The impact of factors affecting PINNs performance, such as the weights assigned to each component of the loss function, the time range used in error computations, and the number of samples used to assess physical constraint was investigated. By assigning a larger weight to the physical constraint and excluding the earlier stage of infiltration in the loss function, the changes in pressure head and the three soil hydraulic parameter distributions within the layered soil profiles were successfully estimated. The developed PINNs can be further applied to more complex soils and can be improved.</p>
Figure 2 in Changes in galling insect community on Caryocar brasiliense trees mediated by soil chemical and physical attributes
Figure 2. Principal components regressions among: (A) Eurytoma sp. galling insect adults (Eur.) with phosphorus-Mehlich 1 (mg dm-3) contents (P.C.) and silt (dag kg-1) (Si.); (B) numbers of Eurytoma sp. glodoid galls (E.G.G.) with pH in water, capacity of cationic exchange (cmol dm-3) (C.C.E.), and P.C.; (C) area (mm2) of Eurytoma sp. glodoid galls (A.E.G.) with pH and clay (dag kg-1) (Cl.); (D) c length of conglomerate of Eurytoma sp. globoid galls (L.G.E.) with pH and Cl.; (E) width of conglomerate of Eurytoma sp. globoid galls (W.G.E.) with pH and Cl.; and (F) number of Hymenopteran discoid galls (H.D.G.) with aluminum (cmol dm-3) contents (A.C.), C.C.E., c and percentage of soil base saturation of the capacity of cationic exchange to pH 7.0 (S.B.S.) on Caryocar brasiliense trees in three years. The symbols represent the averages and the bars the standard errors. n = 111.
Figure 1 in Changes in galling insect community on Caryocar brasiliense trees mediated by soil chemical and physical attributes
Figure 1. Principal components regressions among: (A) abundance of galling insects (A.G.I.) with phosphorus-Mehlich 1 (mg dm-3) contents (P.C.) and sand (dag kg-1) (Sa.); (B) species richness of galling insects (S.R.G.I.) with capacity of cationic exchange (cmol dm-3) c (C.C.E.); (C) diversity of galling insects (D.G.I.) with C.C.E. and Sa.; (D) percentage of galled leaflet by all galls (P.G.L.) with pH in water and clay (dag kg-1) (Cl.); and (E) percentage of leaflet area taken by all galls (P.L.A.G.) with aluminum (cmol dm-3) contents (A.C.) and c C.C.E. on Caryocar brasiliense trees in three years. The symbols represent the averages and the bars the standard errors. n = 111.
Figure 4 in Changes in galling insect community on Caryocar brasiliense trees mediated by soil chemical and physical attributes
Figure 4. Principal components regressions among: (A) abundance of predators (A.Pr.) with phosphorus-Mehlich 1 (mg dm-3) contents (P.C.) and clay (dag kg-1) (Cl.); (B) species richness of predators (S.R.Pr.) with number of Hymenoptera discoid galls (H.D.G.), species richness of parasitoids (S.R.P.), and Cl.; (C) diversity of predators (D.Pr.) with diversity of parasitoids (D.P.) and Cl.; (D) number of Zelus armillatus (Zar.) with P.C., percentage of soil base saturation of the capacity of cationic exchange to pH 7.0 (S.B.S.), silt (dag kg-1) (Si.), numbers of Eurytoma sp. glodoid galls (E.G.G.), and capacity of cationic exchange (cmol dm-3) (C.C.E.); (E) number of Epipolops sp. (Epi.) c with protocooperanting ants (Ants), Cl., and pH in water; and (F) number of spiders (Spi.) with Ants, P.C., and Si. on Caryocar brasiliense trees in three years. The symbols represent the averages and the bars the standard errors. n = 111.
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>
Soil physical quality of a tropical sandy Ferralsol
<p>Dados de pesquisa da dissertação de mestrado do primeiro autor, vinculado à Universidade Estadual de Maringá, Maringá, BR.</p>
Physics-informed neural networks (PINNs) with unsaturated water flow models for inverse analysis of soil hydraulic parameters of layered soil profiles
Open the record for dataset details and reuse information.
physical and chemical information for soil cores from Imnavait watershed during 2003-2005
Physical (bulk density, soil thickness) and chemical (total C and N, d13C and d15N) information of soil cores taken from 15N addition plots in Imnavait watershed.
Eight Mile Lake Research Watershed, Thaw Gradient Extended sites: Physical properties of soil (temperature, moisture and thaw depth).
This data set contains meausrements of soil properties (soil moisture, soil temperature, thaw depth) of sites surrounding an eddy covariance tower. The purpose was to see how physical changes in the lanscape effect carbon fluxes measurede by the EC tower.
Soil chemical and physical property data for Green Lakes Valley, 1982 - 1983.
The genesis and water chemistry of two soil catenas and mineralogy of eolian dust were studied to evaluate the capacity of these soils to buffer acid conditions. Field and laboratory analyses of 50 soil pits and three eolian dust traps indicated that the surface horizons are mainly eolian dust accumulation and the subsurface horizons differed in texture, organic carbon percentage, bulk density, pH, concentration of soluble and exchangeable ions, dissolved organic carbon, and distribution and concentration of clay materials. The chemistry and mineralogy of the eolian dust resemble those of the surface horizons. Calcite, which increases soil buffering capacity, was found in the eolian dust. The eolian calcite probably comes from western Colorado, where limestone exposures are common. This natural liming process may reduce effects of acid rain on the aquatic system.
Soil chemical and physical property data for Martinelli slope, mid-1980s.
Soil pits were excavated at the Martinelli slope within the Boulder City Watershed. Soil profiles were described in the field and samples were analyzed in the laboratory for various constituents.
Soil chemical and physical property data for Saddle nodal plots, 1986.
Samples were collected from various soil horizons during installation of tension soil solution samplers adjacent to nodal plots in the Saddle. Excavation was limited to minimize disturbance. Consequently, complete soil profile descriptions were not made. Samples were analyzed in the laboratory for various constituents.
STEMMUS-SCOPE for PLUMBER2: A Physically Consistent Dataset Across the Soil-Plant-Atmosphere Continuum
<p>High-quality and long-term measurements of water, energy, and carbon fluxes between the land and atmosphere are critical for climate monitoring and land surface model (LSM) benchmarking. This dataset presents high-quality and long-term fluxes, and the corresponding above and below-ground hydrological, physiological, photosynthetic and radiative data derived from the STEMMUS-SCOPE model simulations for the PLUMBER2 project at 170 FLUXNET sites. The generated datasets by STEMMUS-SCOPE are in good agreement with quality in-situ measurements. Therefore, we recommend future applications of the datasets, for such as the detection and attribution of historical changes of fluxes and SM and associated extreme events, providing the initial and boundary conditions for atmospheric models, benchmarking various types of models, and monitoring drought risks. The published dataset can contribute to the development of earth system models in better representing land surface processes and land-atmosphere exchanges in forms of energy, water, and carbon.</p>
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
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
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.