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383 results for “soil water”
Raw neutron counts from a soil water content hydroprobe at 15 NPP study sites at the Jornada Basin LTER, 1989-2019
This data package contains raw neutron count data for monthly soil water probe measurements made at 15 net primary production (NPP) study locations on Jornada Experimental Range (JER) and Chihuahuan Desert Rangeland Research Center (CDRRC) lands. Once a month, soil water content measurements are made at 10 depths (where possible) at each of 10 access tubes at each of the 15 NPP sites using a neutron probe (CPN Model 503DR Hydroprobe). This dataset consists of the count of thermalized neutrons at 30 cm depth intervals to a maximum depth of 300 cm. These counts are subsequently converted to volumetric water content as provided in a separate EDI package (knb-lter-jrn.210013003). The NPP sites these measurements are made at represent the 5 dominant vegetation types of the Jornada Basin, which consist of 3 shrub (creosotebush, mesquite dune, and tarbush) and 2 grass (upland grassland and playa) types. Three NPP sites are located in each of the types. Collection of this dataset was discontinued when the neutron probe instrument was replaced in mid-2019. Neutron probe soil water content data are still collected from the same NPP locations using a new instrument, and the raw neutron counts and corrected VWC data are found in EDI dataset knb-lter-jrn.210013003. This dataset is complete.
Soil Temperature and Water Content in Macrosystems Biodiversity Project at Harvard Forest 2011-2012
Patterns of biodiversity, such as the increase toward the tropics and the peaked curve during ecological succession, are fundamental phenomena for ecology. Such patterns have multiple, interacting causes, but temperature emerges as a dominant factor across organisms from microbes to trees and mammals, and across terrestrial, marine, and freshwater environments. However, there is little consensus on the underlying mechanisms, even as global temperatures increase and the need to predict their effects becomes more pressing. The purpose of this project is to generate and test theory for how temperature impacts biodiversity through its effect on biochemical processes and metabolic rate. A combination of standardized surveys in the field and controlled experiments in the field and laboratory measure diversity of three taxa -- trees, invertebrates, and microbes -- and key biogeochemical processes of decomposition in seven forests distributed along a geographic gradient of increasing temperature from cold temperate to warm tropical. Readings of soil temperature and soil moisture were taken with HOBO sensors from November 2011 to November 2012. These sensors were installed at five experimental tree growth plots installed by the Enquist Lab (PI, Brian Enquist) from the University of Arizona as part of a macrosystems biodiversity and latitude project supported by the National Science Foundation under Cooperative Agreement DEB#1065836.
Soil volumetric water content calculated from neutron hydroprobe data at 15 NPP study locations at the Jornada Basin LTER site, 1989-ongoing
This data package contains soil water content data calculated from monthly neutron hydroprobe count measurements made at 15 net primary production (NPP) study locations on Jornada Experimental Range (JER) and Chihuahuan Desert Rangeland Research Center (CDRRC) lands. Once a month, neutron probe measurements are made at 10 depths (where possible) at each of 10 access tubes at each of the 15 NPP sites using a neutron probe (CPN Model 503DR Hydroprobe and CPN Model 503 Elite Hydroprobe). The raw dataset, also on EDI (knb-lter-jrn.210013001), consists of the count of thermalized neutrons at 30 cm depth intervals to a maximum depth of 300 cm. In this data package, the raw neutron counts have been adjusted for radioactive decay of the neutron source, then converted to volumetric water content (VWC) to a maximum depth of 270 cm using calibration equations (deepest probe depths are excluded from VWC calculations). The NPP sites these measurements are made at represent the 5 dominant vegetation types of the Jornada Basin, which consist of 3 shrub (creosotebush, mesquite dune, and tarbush) and 2 grass (upland grassland and playa) types. Three NPP sites are located in each of the types. This data collection is ongoing with new data collected monthly (updates to the EDI package may occur less frequently). NOTE: This version of the dataset includes calibrated data from a new hydroprobe unit that has recently been put into service. Repair parts were no longer available for the older unit.
WSC - Gridded sample points at Wibu field site including yield, soil texture, water table depth, and estimated soil water retention parameters
A variety of data from gridded sampling points at the Wibu field site. The gridded sampling scheme is described in the Point Locations dataset. This dataset includes 2012 and 2013 absolute and normalized yield, soil textural characteristics (organic content, porosity, bulk density, particle size metrics, % sand/silt/clay), a variety of water table depth metrics (mean, percentiles, sum exceedance values, moving averages), and soil water retention parameters estimated using the Rosetta pedotransfer function. It was collected as part of a study of the impacts of water table depth, soil texture, and growing season weather conditions on corn production at the Wibu field site, described in Zipper et al. (in review). The Wibu field site is a commercial agricultural field, which grew corn in the 2012, 2013, and 2014 growing seasons. See Zipper and Loheide (2014) Ag. For. Met. for more information about the field site.
WSC - Soil moisture, temperature, and water potential at Wibu field site
Soil moisture, temperature, and water potential measurements for 3 locations within Wibu field site: (1) WIBU-6, which is characterized by deep (greater than6 m) groundwater and coarse soil; (2) WIBU-7, which is characterized by intermediate (2-4 m) groundwater and intermediate soil; (3) WIBU-8, which is characterized by shallow (0-3 m) groundwater and fine soil. For more information about the soil and groundwater levels, see other datasets from this field site. The Wibu field site is a commercial agricultural field, which grew corn in the 2012, 2013, and 2014 growing seasons. See Zipper and Loheide (2014) Ag. For. Met. for more information about the field site.
H2Ohio Wetland Monitoring Program Surface Water and Soil Nutrient Content from Wetlands across Ohio, USA (2021–2022).
This data package contains surface water and soil nutrient concentration datasets from wetland projects across Ohio, USA monitored by the H2Ohio Wetland Monitoring Program. Monitoring began in May 2021 and is ongoing. This data package will be updated yearly. In general, surface water samples are collected to measure concentrations of major nutrients, including inorganic nitrogen, ammonium-nitrogen, total nitrogen, dissolved reactive phosphorus, and total phosphorus. Sampling from major inflows and outflows is prioritized at flow-through wetland projects to support the calculation of nutrient filtration estimates using mass balance approaches. Surface water samples may also be collected from representative zones or hydrologic features with sufficient standing water (i.e., vernal pools, vegetated areas, interconnected smaller pond-like areas, etc.) to assess nutrient conditions and processes within the wetland system. The majority of surface water sampling (~monthly) occurs from March through December, with opportunistic sampling in January and February. Every effort is made to collect samples during hydrologic events (i.e., storms) as well as baseflow conditions. Concurrent with surface water sampling, hand-held multiparameter sensors are used to measure snapshots of physicochemical characteristics including dissolved oxygen, temperature, specific conductance, turbidity, and pH. Soil samples (0-5 cm) are collected in saturated and unsaturated zones at each identified soil "patch" determined from expert opinion, soil maps (Natural Resources Conservation Service), and/or hydrogeophysical assessment. Additionally, soil samples may be collected along major visible hydrologic or elevation gradients. Soil sampling occurs 1-3 times a year in select wetland projects.
Biogeochemistry data set for soil waters, streams, and lakes near Toolik Lake on the North Slope of Alaska, 2012 through 2020
Data file of the biogeochemistry of samples collected at various sites near Toolik Lake, North Slope of Alaska. Sample site descriptors include a unique assigned number (sortchem), site, date, time, depth, distance (downstream from a reference location), elevation, treatment, date-time, category, and water type (lake, surface, soil). Physical measures collected in the field include temperature (water, soil, well water), conductivity, pH, and average thaw depth in soil. Chemical analyses for the sample include alkalinity; dissolved inorganic and organic carbon (DIC and DOC); dissolved gases CO2 and CH4; inorganic and total dissolved nutrients (NH4, PO4, NO3, TDN, TDP); particulate carbon, nitrogen, and phosphorus (PC, PN, and PP); cations (Ca, Mg, Na, K, and Si); and anions (SO4 and Cl).
Soil Water Content at Harvard Forest HEM and LPH Towers 1998-2007
Water content of the top 20 cm of soil was measured using 1.5 inch diameter soil cores. Soil water content is of particular interest and importance in explaining patterns of soil respiration (including root respiration) and ecosystem respiration, 60 to 75% of which occurs below the ground surface at Harvard Forest. Soil water content in deciduous forest near the Little Prospect Hill Forest was in general found to be more variable than near the Hemlock tower. One influence contributing to this is the presence of a water table within 1 m of the soil surface near the hemlock tower, compared to a water table at unknown depth in the deeply drained soils in most parts of Little Prospect Hill. Relatively low evapotranspiration at the Hemlock tower site during the period when deciduous trees are foliated also contributes to higher water content in soil there, and a relatively thick surface organic layer. These influences tend to maintain soil respiration at higher levels in the hemlock forest during dry summers, but excessive moisture in the soil at the Hemlock site during very wet summers appears to suppress soil respiration.
Soil water content measurements and rainfall data for plots with experimentally altered precipitation and nutrient inputs at the Jornada Basin LTER site, 2011-ongoing
This dataset contains soil volumetric water content data collected starting in 2011 for a long-term precipitation and nutrient manipulation experiment at the Jornada Basin LTER site in southern New Mexico, U.S.A. This experiment uses precipitation shelters and irrigation treatments to manipulate water inputs, and fertilization treatments to alter nitrogen input to 2.5 x 2.5 meter plots in a desert grassland. Soil sensors are installed at surface and deep soil layers in each plot and collect hourly averages of volumetric water content using a time-domain reflectometry method. This dataset contains daily averages. This is an ongoing study and the dataset will be updated yearly.
Aggregated 30-minute soil water and temperature data from 9 NPP shrub sites at Jornada Basin LTER, 2013 - 2024 (for Pinos et al 2025 manuscript)
This is an aggregated dataset of 30-minute soil temperature and moisture data from 9 shrub-dominated NPP study sites at the Jornada Basin LTER site in southern New Mexico, U.S.A. Collection of soil volumetric water content data at all of the 15 Jornada LTER NPP sites, New Mexico, supports the environmental monitoring objectives of the Jornada LTER monitoring program that look at plant-soil water dynamics. Volumetric water content and soil temperature are measured every 30 minutes at an automated meteorological station installed at all 15 of the Jornada LTER program’s NPP sites. This dataset aggregates only the stations located at the 9 sites with shrub-dominated vegetation cover (creosotebush, tarbush, and mesquite dune sites). Measurements are made every 30 minutes at 10 cm, 20 cm, and 30 cm soil depths. This dataset is in support of the Pinos et al. 2025 manuscript.
NSW01 Soil water chemistry from porous cup lysimeters on watersheds with different fire treatment
Soil water nitrogen composition is measured using porous cup lysimeters. Measurements include nitrate, ammonia, phosphate, and organic nitrogen and phosphorus. Variables of interest are rainfall patterns, vegetation types, and time since burning.
Forest Transition Experiment - Soil Pore Water Salinity in a Coastal Virginia Forest
A pore water sipper was be used to collect a pore water sample from the top 15 cm of the soil, and was read using a portable refractometer in the field.
The Jefferson Project 2018 hydrologic, water quality, and soil quality data from 11 Tributary Stations within the Lake George basin, NY, USA.
The Jefferson Project at Lake George -- a partnership between Rensselaer Polytechnic Institute, IBM Research, and Lake George Association -- combines Internet of Things technology and powerful analytics with science to create a new model for environmental monitoring and prediction. The project is building a computing platform that captures and analyzes data from a network of sensors tracking water quality and movement. These sensor data are combined with other monitoring and experimental data to create a thorough understanding of the factors that drive the lake's food web, hydrology, and water quality. More information about The Jefferson Project is available at <https://jeffersonproject.rpi.edu/> In 2018, The Jefferson Project had eleven tributary monitoring stations around the lake collecting data on water quality, soil quality, and hydrology. These stations are TS_Finkle, TS_Hague, TS_Indian, TS_NorthwestBay, TS_Outlet, TS_PoleHill, TS_English, TS_Sunset, TS_ShelvingRock, TS_East, and TS_West. The stations have a sensor payload that may include some or all of the following sensors: YSI EXO2 Multi-parameter sonde, Campbell Scientific CS451 pressure transducer, SonTek-IQ+ multi-beam acoustic flow meter, Sontek-SL Doppler current meter, YSI WaterLOG® H-3123 submersible pressure transducer, and Stevens HydraProbe soil moisture sensor. The sensors collect data at high-frequency (~1 sample per minute) and the data is transferred in near real-time to off-site databases for monitoring and review by Jefferson Project researchers. Data provided is level 4 data which underwent data correction and downsampling to an hourly frequency.
The Jefferson Project 2019 hydrologic, water quality, and soil quality data from 12 Tributary Stations within the Lake George basin, NY, USA.
The Jefferson Project at Lake George -- a partnership between Rensselaer Polytechnic Institute, IBM Research, and Lake George Association -- combines Internet of Things technology and powerful analytics with science to create a new model for environmental monitoring and prediction. The project is building a computing platform that captures and analyzes data from a network of sensors tracking water quality and movement. These sensor data are combined with other monitoring and experimental data to create a thorough understanding of the factors that drive the lake's food web, hydrology, and water quality. More information about The Jefferson Project is available at https://jeffersonproject.rpi.edu/ In 2019, The Jefferson Project had twelve tributary monitoring stations around the lake collecting data on water quality, soil quality, and hydrology. These stations are TS_Finkle, TS_Hague, TS_Indian, TS_NorthwestBay, TS_Outlet, TS_PoleHill, TS_English, TS_Sunset, TS_Sucker, TS_ShelvingRock, TS_East, and TS_West. The stations have a sensor payload that may include some or all of the following sensors: YSI EXO2 Multi-parameter sonde, Campbell Scientific CS451 pressure transducer, SonTek-IQ+ multi-beam acoustic flow meter, Sontek-SL Doppler current meter, YSI WaterLOG® H-3123 submersible pressure transducer, and Stevens HydraProbe soil moisture sensor. The sensors collect data at high-frequency (~1 sample per minute) and the data is transferred in near real-time to off-site databases for monitoring and review by Jefferson Project researchers. Data provided is level 4 data which underwent data correction and downsampling to an hourly frequency.
The Jefferson Project 2020 hydrologic, water quality, and soil quality data from 12 Tributary Stations within the Lake George basin, NY, USA.
The Jefferson Project at Lake George -- a partnership between Rensselaer Polytechnic Institute, IBM Research, and Lake George Association -- combines Internet of Things technology and powerful analytics with science to create a new model for environmental monitoring and prediction. The project is building a computing platform that captures and analyzes data from a network of sensors tracking water quality and movement. These sensor data are combined with other monitoring and experimental data to create a thorough understanding of the factors that drive the lake's food web, hydrology, and water quality. More information about The Jefferson Project is available at https://jeffersonproject.rpi.edu/ In 2020, The Jefferson Project had twelve tributary monitoring stations around the lake collecting data on water quality, soil quality, and hydrology. These stations are TS_Finkle, TS_Hague, TS_Indian, TS_NorthwestBay, TS_Outlet, TS_PoleHill, TS_English, TS_Sunset, TS_Sucker, TS_ShelvingRock, TS_East, and TS_West. The stations have a sensor payload that may include some or all of the following sensors: YSI EXO2 Multi-parameter sonde, Campbell Scientific CS451 pressure transducer, SonTek-IQ+ multi-beam acoustic flow meter, Sontek-SL Doppler current meter, YSI WaterLOG® H-3123 submersible pressure transducer, and Stevens HydraProbe soil moisture sensor. The sensors collect data at high-frequency (~1 sample per minute) and the data are transferred in near real-time to off-site databases for monitoring and review by Jefferson Project researchers. The data provided here are level 4 data which underwent data correction and downsampling to an hourly frequency.
2017 hydrologic, water quality, and soil quality data from The Jefferson Projects 8 Tributary Stations within the Lake George basin, NY, USA.
The Jefferson Project at Lake George – a partnership between Rensselaer Polytechnic Institute, IBM Research, and Lake George Association – combines Internet of Things technology and powerful analytics with science to create a new model for environmental monitoring and prediction. The project is building a computing platform that captures and analyzes data from a network of sensors tracking water quality and movement. These sensor data are combined with other monitoring and experimental data to create a thorough understanding of the factors that drive the lake’s food web and overall water quality. More information about The Jefferson Project is available at https://jeffersonproject.rpi.edu/ In 2017, The Jefferson Project had eight tributary monitoring stations around the lake collecting data on water quality, soil quality and hydrology. These stations are TS_Finkle, TS_Hague, TS_Indian, TS_NorthwestBay, TS_Outlet, TS_PoleHill, TS_ShelvingRock and TS_West. The stations have a sensor payload that may include some or all of the following sensors: EXO2 Multi-parameter sonde, CS451 pressure transducer, SonTek-IQ+ multi-beam acoustic flow meter with five 3.0 MHz transducers, Argonaut-SL Doppler current meter, WaterLOG® H-3123 submersible pressure transducer, and Stevens HydraProbe soil moisture sensor. The sensors collect data at high-frequency (~1 sample per minute) and the data is transferred in near real-time to off-site databases for monitoring and review by Jefferson Project researchers. Data provided is level 4 data which underwent data correction and down sampling to an hourly frequency.
Water Depths and Water Temperatures near Soil Surface from Shark River Slough, Everglades National Park (FCE LTER), Florida, USA, October 2000 - ongoing
Water depth (from October 2000 to present) and water temperature (from September 2021 to present) are recorded at least hourly at SRS1c (not active), SRS1d, SRS2, SRS3, SRS4, SRS5, and SRS6. Water depth is measured with pressure water level loggers (Infinities USA or HOBO) that record water height relative to the local soil surface. Water temperature near soil surface is measured with HOBO loggers. Note by IM (2021): The water meters at some of the SRS sites have been moved over the years as boardwalks have been reconstructed. There is no set survey datum for these sites, so it is impossible to correct the data to an actual datum. For hydrologic applications, it may be better to use water level data from USGS stations.
Water Depths and Water Temperatures near Soil Surface from Taylor Slough, Everglades National Park (FCE LTER), Florida, USA, August 1999 - ongoing
Water depth (from August 1999 to present) and water temperature (from May 2021 to present) are recorded hourly at TS/Ph1a, TS/Ph2 and TS/Ph3 and every 30 minutes at TS/Ph6a and TS/Ph7a. Water depth is measured with pressure water level loggers (Infinities USA or HOBO) that record water height relative to the local soil surface. Water temperature near soil surface is measured with HOBO loggers. Note by IM (2021): The water meters at some of the TS sites have been moved over the years as boardwalks have been reconstructed. There is no set survey datum for these sites, so it is impossible to correct the data to an actual datum. For hydrologic applications, it may be better to use water level data from USGS stations.
Water, Soil, Floc, Plant Total Phosphorus, Total Carbon, and Bulk Density data (FCE) from Everglades Protection Area (EPA) from 2004 to 2016
These data are a compillation of data from multiple sources including South Florida Water Management District (SFWMD) DBhydro web database, United States Environment Protection Agency Regional, Environmental Monitoring and Assessment (REMAP), Everglades Soil Mapping (ESM), and Florida Coastal Everglades Long Term Ecological Research (FCE-LTER). The matrix of these data were compiled for soil, surface water, floc, and plants where the nutrients are counted for total phosphorus, total carbon, and bulk density. When downloading the data from DBhydro, only regularly collected samples (SAMP) were included these data. As per DBhydro metadata, the regular samples were collected monthly by grab method throughout the year from 2004 to 2016 for SFWMD monitoring stations across the EPA. All flagged and field quality controlled values were excluded to avoid the duplication of data. In order to maintain the quality assurance/ quality control (QA/QC) the method detection limit for water TP was fixed at 2 µg/L by the SFWMD. This data set were used to assess the decadal trend of TP concentration in surface water and soil in EPA. Available data from 2004 to 2014 was collected for soils and from 2004 to 2016 for water to understand a decade of trends. Both Geographic Information System (GIS) and statistical data analysis were applied to determine changes in water quality and soil chemistry. These data are the basis for Shishir Sarker's Master's thesis.
Long-term Atmospheric, Soil and Water Sensor Data from the GCE-LTER Eddy Covariance Flux Tower on Sapelo Island, Georgia
Long-term measurements of various atmospheric, soil and water properties were made using electronic sensors attached to the GCE-LTER eddy covariance flux tower deployed in a Spartina alterniflora salt marsh on Sapelo Island, Georgia. Variables measured include air and water temperature, relative humidity, precipitation, wind speed and direction, soil temperature, water pressure and solar radiation components (i.e. incident and reflected photosynthetically available, total, long-wave and shortwave radiation). Measurements were logged at 5 minute intervals using multiple Campbell Scientific Instruments CR3000 data loggers, and then combined into a single monotonic time series data set. Quality control analyses were performed to remove values deemed invalid due to sensor failure or miscalibration and to assign Q/C qualifiers to values outside expected ranges or failing various sanity and quality checks of the data. Note that some measurements were spatially replicated with multiple sensors deployed in different micro-habitats (e.g. at the tower and in a nearby marsh platform or creek). Sensors were also added to the tower at various times after the initial installation, therefore some variables do not span the entire period of record. Measurements at this site are ongoing, and the data set will be updated annually to include additional observations.
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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)
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DANDI Archive for NWB datasets
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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
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.