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396 results for “Surface water”
Data from: The influence of distance to perennial surface water on ant communities in Mopane woodlands, northern Botswana
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Data from: Surface-water dynamics and land use influence landscape connectivity across a major dryland region
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Global lake surface water temperature layers
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USEPA EMAP Surface Waters Lake Database Northeast Lake Water Chemistry Data, 1991-1994
The primary function of the lake water chemistry samples, collected with a van Dorn sampler, is to determine acid-base status, trophic state, and classification of water chemistry type. Water chemistry in lakes is analyzed for two purposes. First, to understand the chemical habitat within which biota must exist so that we can understand the biological potential of the system and second, to evaluate the chemical quality of the water for the purposes of determine the potential stresses to which the biota are exposed. Water chemistry parameters are reported for one sample taken at the location of the deepest part of the lake by a van Dorn sampler from a depth of 1.5 m. These include: aluminum, alkalinity, acid neutralizing capacity, calcium, carbonate, color, specific conductance, dissolved inorganic carbon, dissolved organic carbon, bicarbonate, potassium, magnesium, ammonium, sodium, nitrate, total nitrogen, pH, total phosphorus, silica, total suspended solids, turbidity, and chlorophyll-a. Sampling was initiated July 1991 and ended September 1994.
Wisconsin Surface Water Integrated Monitoring System (SWIMS) Department of Natural Resources lake nutrient data, 1970-2011
The Wisconsin Surface Water Integrated Monitoring System (SWIMS) program is the state´s repository for water and sediment monitoring data collected for Clean Water Act work and is the source of data sharing through the federal Water Quality Exchange Network. DNR Fisheries and Water Quality Biologists use the system to locate monitoring stations, providing a gateway to final, reviewed fisheries management datasets housed at the U.S. Geological Survey. SWIMS is also the data system that citizen volunteers use to document water monitoring results for our state´s lakes, streams and wetlands. Parameters typically collected on lakes are total phosphorus, chlorophyll a and Secchi. Through the DNR Long-Term Trend monitoring program, additional parameters such as Nitrogen have been collected. Lake data in SWIMS generally goes back to the 1970s (1970s data was imported in from the EPA STORET database, where DNR laboratory results went historically). The database is updated daily.
National Surface Water Survey: Eastern Lake Survey-Phase II Combined datasets: Spring (SPSFIM01), Summer (SUSFIM01), Fall (FASFIM01), Summer Chlorophyll (SUSCHLA), and Bathymetry data (BATHYM_M), 1986
The Eastern Lake Survey-Phase II (ELS-II), conducted in the spring, summer and fall of 1986. The focus of ELS-II was on the northeastern United States. ELS-II involved the resampling of a subset of lakes in the northeastern United States sampled in ELS-I to determine chemical variability and biological status. Furthermore, within-indexed period variability was examined in the fall of 1986 to provide insight concerning the ability to detect chemical changes over time, and the precision of the estimates of the number of acidic lakes from Phase I. The primary objectives of ELS-II were (1) to assess the sampling error associated with the ELS-I fall index sample, (2) to estimate the number of lakes with low acid neutralizing capacity (ANC) (i.e. potentially susceptible) that are not acidic in the fall but that are acidic in other seasons, and (3) to establish seasonal water chemistry characteristics among lakes. This data set is part of the National Surface Water Survey (NSWS) and the National Acid Precipitation Assessment Program (NAPAP). The data set contributes to the quantification of the extent, location, and characteristics of sensitive and acidic lakes and streams in the eastern United States sampled during the spring, summer and fall seasons.
How surface rock cover affects water and nutrient availability of Sonoran Desert annual plants -- Honors Thesis
Water and nutrient availability are the primary and secondary drivers of net primary productivity (NPP) in arid ecosystems. Although precipitation regulates water inputs, soil properties influence water availability for plant growth. Aridland soils are often covered with surface rocks, which can increase or decrease water availability by modifying evaporation, infiltration, light levels, and temperature. Due to the complexity of these direct and indirect mechanisms, the relationship between rock cover and NPP is not well understood. In this research we explore the relationship between rock cover, soil nutrient availability, and aboveground growth of desert annual plants over four years across a long-term nutrient enrichment experiment in the Sonoran Desert. We surveyed surface rock cover at fifteen sites in central Arizona that have been fertilized with nitrogen (N) and phosphorus (P), alone and in combination, for seven years. Using ANCOVA, we then explored the relative importance of rock cover, precipitation, and nutrient treatment on peak aboveground biomass of spring herbaceous annual plants that were collected in 2008, 2009, 2010, and 2013. We expected surface rocks to strengthen the positive relationship between precipitation, nutrient additions, and annual plant growth. Precipitation, nutrient additions, and surface rock cover together significantly influence growth of Sonoran Desert annual plants. As expected, nutrients and precipitation were the strongest drivers of annual plant biomass. Plant growth was positively related to N additions across all four years (ANCOVA, p <0.01); P in 2008 and 2010 years (p = 0.01 and 0.005, respectively);and precipitation in three of the four years (p < 0.05). Precipitation was the primary driver of plant biomass in the two driest years, 2009 and 2013 (partial eta2 = 0.51 and 0.52, respectively). Gravel (2-64 mm diameter) was only rock size class that was significantly related to annual plant biomass. Contrary to our expecta
Hubbard Brook Experimental Forest: Synoptic Surface Water Chemistry, 2015
This dataset presents field and analytical data collected during a synoptic surface water sampling survey on July 22-23, 2015. Watershed 3, watershed 9, and the upper west branch of Zig Zag Brook were included. Some results from these three catchments were published by Bailey et al. 2019, Frontiers in Earth Science. Additional sampling sites not included in this publication were on Paradise Brook, between weir 3 and its outlet to Hubbard Brook, and along the main stem of Hubbard Brook in the western portion of the valley. Sampling sites are designated as stream sites or seeps. Seeps are either off of the stream channel or are at anomolously perennial channel initiation points and are presumed to represent "longer, deeper" flowpaths where groundwater discharges to the surface. Seeps are typically characterized as having relatively low water temperature in the summer, and with chemistry contrasting from adjacent stream sites. These data were gathered as part of the Hubbard Brook Ecosystem Study (HBES). The HBES is a collaborative effort at the Hubbard Brook Experimental Forest, which is operated and maintained by the USDA Forest Service, Northern Research Station.
Synthetic river datasets built for testing and development of the Surface Water and Ocean Topography mission discharge algorithms
<p><strong>1.Summary</strong></p> <p>Datasets used for testing the performance of discharge estimation algorithms built in support of the Surface Water and Ocean Topography satellite mission. The benchmarking manuscript entitled “Exploring the factors controlling the performance of the Surface Water and Ocean Topography mission discharge algorithms” is currently under review at Water Resources Research. Once the manuscript is accepted, its DOI will be included here.</p> <p><strong>2.File description</strong></p> <p>The dataset is divided into four groups: 1-Ideal data, 2-Varying Temporal Sampling, 3-Measurement Uncertainty, and 4-SWOT Sampling and Uncertainty. Ideal data contains daily measurements with no observational uncertainty. Varying Temporal Sampling downsamples the ideal measurements considering different temporal frequencies with complete sets assuming: 1 measurement every 2 days, 3 days, 4 days, 5 days, 7 days, 10 days, and 21 days. The measurement uncertainty set adds errors to cross-sectional heights and widths, which are used to compute reach average height, width, and slope considering error corruption. The final set SWOT Sampling and Uncertainty accounts for SWOT temporal sampling and measurement uncertainty. Sets containing uncertainty have extra height, width, and slope attributes with the word true appended to the attribute name. Such attributes represent the uncorrupted measurements at the cross-section and reach scales. Height, width, and slopes for the SWOT sampling and Uncertainty dataset containing the value of negative 9999 denote points that are not observed at a particular location and time step.</p> <p>Data will be contained in one NetCDF file per river. The file contains the following groups and variables:</p> <p><strong>/River_Info/</strong></p> <p>Name: River name, data type: char</p> <p>QWBM: Mean annual discharge from the water balance model WBMsed (Cohen et al., 2014)</p> <p>rch_bnd: Reach boundaries measured in meters from the upstream end of the model</p> <p>gdrch: Reaches used in the study. Used to exclude small reaches defined around low-head dams and other obstacles where Manning’s equation should not be applied.</p> <p><strong>/XS_Timeseries/</strong></p> <p>t: Time measured in days since the first day or “0-January-0000” for cases when specific dates were available. Dimension: 1,time step.</p> <p>Z: Bed elevation in meters. Dimension: Cross-section, time step.</p> <p>xs_rch: Reach number for each cross-section. Dimension: Cross-section,1.</p> <p>X: Flow distance measured from the most upstream end of the model to the cross-section (meters). Dimension: Cross-section, 1.</p> <p>longitude: Cross-section longitude in decimal degrees. Dimension: Cross-section,1.</p> <p>latitude: Cross-section latitude in decimal degrees. Dimension: Cross-section,1.</p> <p>W: River width in meters. Dimension: Cross-section, time step.</p> <p>Wtrue: River width in meters. Dimension: Cross-section, time step. Only present in datasets containing measurement uncertainty, in which case, this variable holds the water surface elevation value with no uncertainty.</p> <p>Q: Discharge (m<sup>3</sup>/s). Dimension: Cross-section, time step.</p> <p>H: Water surface elevation in meters. Dimension: Cross-section, time step.</p> <p>Htrue: Water surface elevation in meters. Dimension: Cross-section, time step. Only present in datasets containing measurement uncertainty, in which case, this variable holds the water surface elevation value with no uncertainty.</p> <p>A: Cross-sectional area of flow in m<sup>2</sup>. Dimension: Cross-section, time step.</p> <p>P: Wetted perimeter in meters. Dimension: Cross-section, time step.</p> <p>n: Manning’s roughness. Dimension: Cross-section, time step.</p> <p><strong>/Reach_Timeseries/</strong></p> <p>t: Time measured in days since the first day or “0-January-0000” for cases when specific dates were available. Dimension: 1,time step.</p> <p>W: Reach averaged river width in meters. Dimension: Reach, time step.</p> <p>Wtrue: Reach averaged river width in meters. Dimension: Reach, time step. Only present in datasets containing measurement uncertainty, in which case, this variable holds the width value with no uncertainty.</p> <p>Q: Reach averaged discharge (m<sup>3</sup>/s). Dimension: Reach, time step.</p> <p>H: Reach averaged water surface elevation in meters. Dimension: Reach, time step.</p> <p>Htrue: Reach averaged water surface elevation in meters. Dimension: Reach, time step. Only present in datasets containing measurement uncertainty, in which case, this variable holds the water surface elevation value with no uncertainty.</p> <p>S: Reach averaged water surface slope in meters per meter. Reach, time step.</p> <p>Strue: Reach averaged water surface slope in meters per meter. Dimension: Reach, time step. Only present in datasets containing measurement uncertainty, in which case, this variable holds the slope value with no uncertainty.</p> <p>A: Reach averaged area of flow in m<sup>2</sup>. Dimension: Reach, time step.</p> <p><strong>References</strong></p> <p>Cohen, S., A. J. Kettner, and J. P. M. Syvitski (2014), Global suspended sediment and water discharge dynamics between 1960 and 2010: Continental trends and intra-basin sensitivity, <em>Glob. Planet. Change</em>, <em>115</em>, 44-58, doi: <a href="https://doi.org/10.1016/j.gloplacha.2014.01.011">https://doi.org/10.1016/j.gloplacha.2014.01.011</a>.</p> <p> </p>
Sentinel-3A and Sentinel-3B radar altimetry water surface elevation in the Zambezi catchment
<p>This dataset contains the data presented in Kittel et al. (2020): Sentinel-3 radar altimetry for river monitoring – a catchment-scale evaluation of satellite water surface elevation from Sentinel-3A and Sentinel-3B, https://doi.org/10.5194/hess-2020-165</p> <p>The dataset is the full Sentinel-3A and 3B radar altimetry records for water surface elevation in the Zambezi catchment for all virtual stations containing at least 80% of the expected observations and predominantly single-peak waveforms. Not all VS have been manually checked or validated.</p> <p>Additionally the repository contains a shapefile with all Sentinel-3 virtual stations in the Zambezi.</p>
Data from: Numerical simulation of the free surface and water inflow of a slope, considering the nonlinear flow properties of gravel layers: a case study
Groundwater is an important factor of slope stability, and ninety percent of slope failures are related to the influence of groundwater. In the past, free surface calculations and the prediction of water inflow were based on Darcy's law. However, Darcy's law for steady fluid flow is a special case of non-Darcy flow, and many types of non-Darcy flows occur in practical engineering applications. In this paper, based on the experimental results of laboratory water seepage tests, the seepage state of each soil layer in the open-pit slope of the Yanshan Iron Mine, China, were determined, and the seepage parameters were obtained. The seepage behaviour in the silt layer, fine sand layer, silty clay layer, and gravelly clay layer followed the traditional Darcy law, while the gravel layers showed clear nonlinear characteristics. The relation among the permeability, the porosity and the non-Darcy coefficient is investigated. A coupled mathematical model is established for two flow fields, on the basis of Darcy flow in the low-permeability layers and Forchheimer flow in the high-permeability layers. In addition, we considered the effect of the seepage in the slope on the transition from Darcy flow to Forchheimer flow. Then, a numerical simulation was conducted by using finite element software (LELAC 2.2). The results indicate that the free surface calculated by the Darcy-Forchheimer model is in good agreement with the in situ measurements; however, there is an evident deviation of the simulation results from the measured data when the Darcy model is used. Through a parameter sensitivity analysis of the gravel layers, we found that the height of the overflow point and the water inflow calculated by the Darcy-Forchheimer model are consistently less than those of the Darcy model, and the discrepancy between these two models increase as the permeability increases. The necessity of adopting the Darcy-Forchheimer model was explained.
Data from: Water-repellent plant surface structure induced by gall-forming insects for waste management
Many animals and plants have evolved elaborate water-repellent microstructures on their surface, which often play important roles in their ecological adaptation. Here we report a unique type of water-repellent structure on plant surface, which develops as an insect-induced plant morphology in a social context. Some social aphids form galls on their host plant, in which they produce large amount of hydrophobic wax. Excreted honeydew is coated by the powdery wax to form "honeydew balls", which are actively disposed by soldier nymphs through an opening on their gall. These activities are enabled by a highly water-repellent inner gall surface, and we discovered that this surface is covered with dense trichomes that are not found on normal plant surface. The trichomes are coated by fine particles of the insect-produced wax, thereby realizing a high water repellency with a cooperative interaction between aphids and plants. The plant leaves on which the gall is formed often exhibit patchy areas with dense trichomes, representing an ectopic expression of the insect-induced plant morphology. In the pouch-shaped closed galls of a related social aphid species, by contrast, the inner surface was not covered with trichomes. Our findings provide a convincing example of how the extended phenotype of an animal, expressed in a plant, plays a pivotal role in maintaining sociality.
Data from: Ecosystem productivity is associated to bacterial phylogenetic distance in surface marine waters
Understanding the link between community diversity and ecosystem function is a fundamental aspect of ecology. Systematic losses in biodiversity are widely acknowledged but the impact this may exert on ecosystem functioning remains ambiguous. There is growing evidence of a positive relationship between species richness and ecosystem productivity for terrestrial macroorganisms, but similar links for marine microorganisms, which help drive global climate, are unclear. Community manipulation experiments show both positive and negative relationships for microbes. These previous studies rely, however, on artificial communities and any links between the full diversity of active bacterial communities in the environment, their phylogenetic relatedness, and ecosystem function remains hitherto unexplored. Here we test the hypothesis that productivity is associated to diversity in the metabolically active fraction of microbial communities. We show in natural assemblages of active bacteria that communities containing more distantly related members were associated with higher bacterial production. The positive phylogenetic diversity–productivity relationship was independent of community diversity calculated as the Shannon index. From our long-term (7-year) survey of surface marine bacterial communities we also found that similarly productive communities had greater phylogenetic similarity to each other, further suggesting that the traits of active bacteria are an important predictor of ecosystem productivity. Our findings demonstrate that the evolutionary history of the active fraction of a microbial community is critical for understanding their role in ecosystem functioning.
Water level elevation data for monitoring wells and surface water gages at the Colorado State University Mountain Campus, 2019 – 2023
<p>This dataset contains groundwater and surface water levels measured between 2019 and 2023 at the Colorado State University Mountain Campus. The study site is situated within a formerly glaciated valley traversed by a modern perennial stream, the South Fork Cache la Poudre River, and occurs near the subalpine-montane ecosystem transition at an approximate elevation of 2,750 meters above sea level. Water levels were measured at two transects (the upstream and downstream transects). Each transect includes a surface water gage, two shallow hand-augered monitoring wells on the valley floor within the riparian zone, and a deeper water table observation well located on the adjacent terrace. Water levels were measured at a subhourly frequency using a combination of vented and non-vented pressure transducers. All data from non-vented transducers were corrected for barometric pressure fluctuations.</p>
Dataset: The Far-INfrarEd Spectrometer for Surface Emissivity (FINESSE) Part II: First measurements of the emissivity of water in the far-infrared.
<p>This repository contains callibrated radiance measurements from the FINESSE instrument and related auxilary files as referenced in the article "The Far-INfrarEd Spectrometer for Surface Emissivity (FINESSE) Part II: First measurements of the emissivity of water in the far-infrared." by Warwick, L., Murray, J. and Brindley, H.</p> <p>In this paper we describe a method for retrieving surface emissivity across the wavenumber range 400-1600 cm-1 using novel radiance measurements from the Far INfrarEd Spectrometer for Surface Emissivity (FINESSE) instrument. FINESSE is described in detail in part I of the paper. We apply the method to two sets of measurements of distilled water. The first set of emissivity retrievals is of distilled water heated above ambient temperature to enhance the signal to noise ratio. The second set of emissivity retrievals is of ambient temperate water at a range of viewing angles. In both cases the observations agree well with calculations based on compiled refractive indices across the mid and far-infrared. It is found that the reduced contrast between the up and downwelling radiation in the ambient temperature case degrades the performance of the retrieval. Therefore a filter is developed to target regions of high contrast which improves the agreement between the ambient temperature emissivity retrieval and the predicted emissivity. These retrievals are, to the best of our knowledge, the first published retrievals of the emissivity of water that extend into the far-infrared and demonstrate a method that can be used for the in-situ retrieval of the emissivity of other surfaces in the field.</p>
Impact of surface water-groundwater interactions on residual saltwater desalinization behind subsurface dams in coastal aquifers
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Inputs and outputs for monolayers simulations in "Accurate Simulations of Lipid Monolayers Require a Water Model With Correct Surface Tension"
<p>Inputs and outputs file for simulations of POPC and DPPC Monolayers at 298K. For details see:</p>
AIMD simulations of water over transition metal surfaces
<p>AIMD simulations of water molecules over (111) surfaces of Ag, Au, Cu, Pt, Pd, and Rh, (211) and (100) surfaces of Ag, Au, Cu, and Pt, and (0001) surface of Ru. Data used for analysis in "OH binding energy as a universal descriptor of the potential of zero charge on transition metal surfaces," which can be found on ChemRxiv with DOI <a href="https://doi.org/10.26434/chemrxiv-2021-dkb6l">10.26434/chemrxiv-2021-dkb6l</a>.</p>
Supplementary material 1 from: Castaño Sánchez A, Pereira J, Gonçalves F, Reboleira A (2018) Comparative acute toxicity of the pharmaceutical compound Diclofenac on groundwater and surface water crustaceans. ARPHA Conference Abstracts 1: e29822. https://doi.org/10.3897/aca.1.e29822
Poster presented at the 24th International Conference on Subterranean Biology. University of Aveiro (Portugal), 20-24th August 2018.
Data from: Structure of the rare archaeal biosphere and seasonal dynamics of active ecotypes in surface coastal waters
Marine Archaea are important players among microbial plankton and significantly contribute to biogeochemical cycles, but details regarding their community structure and long-term seasonal activity and dynamics remain largely unexplored. In this study, we monitored the inter-annual archaeal community composition of abundant and rare biospheres in northwestern Mediterranean Sea surface waters by pyrosequencing 16S rDNA and rRNA. A detailed analysis of the rare biosphere structure showed that the rare archaeal community was composed of three distinct fractions. One contained the rare Archaea that became abundant at different times within the same ecosystem; these cells were typically not dormant, and we hypothesize that they represent a local seed bank that is specific and essential for ecosystem functioning through cycling seasonal environmental conditions. The second fraction contained cells that were uncommon in public databases and not active, consisting of aliens to the studied ecosystem and representing a non-local seed bank of potential colonizers. The third fraction contained Archaea that were always rare but actively growing; their affiliation and seasonal dynamics were similar to the abundant microbes and could not be considered a seed bank. We also showed that the major archaeal groups, Thaumarchaeota Marine Group-I (MGI) and Euryarchaeota Group-II.B (MGII.B) in winter and Euryarchaeota Group-II.A (MGII.A) in summer, contained different ecotypes with varying activities. Our findings suggest that archaeal diversity could be associated with distinct metabolisms or life strategies, and that the rare archaeal biosphere is composed of a complex assortment of organisms with distinct histories that affect their potential for growth.
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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.