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    This dataset includes two cruises of data collected to investigate Arctic hydrate dissociation as a consequence of climate change and to determine vulnerable methane reservoir and gas escape mechanisms. Work during both JR269A and JR269B was focused on two separate geographical areas. The first of these was west of Prins Karls Forland, in water depths of between 150 and 1200 m. At its landward end, this survey area crosses a region at water depths up to 400 m where a dense concentration of methane escape bubble plumes occur. The second survey area straddles the summit of the Vestnesa Ridge, in water depths of 1180 to 1400 m, and is also the site of methane escape bubble plumes within the water column and of fluid escape chimneys and pockmarks previously imaged at and beneath the sea bed. This area lies approximately 100 km west of the mouth of Kongsfjorden. Data collection took place between August 2011 and July 2012. The research expedition used a deep-towed, very high resolution seismic system to image the small-scale structures that convey gas to the seabed and to detect the presence of gas in the sediments. This was done in conjunction with an electromagnetic exploration system that uses a deep-towed transmitter and receivers on the seabed to derive the variations in electrical resistivity in the sediments beneath the seabed. The observations carried out on the two cruises included; underway, meteorological observations and echo sounder data, multichannel seismic reflection profiling data, wide angle seismic survey data, and ocean bottom seismometer (OBS) data, ocean bottom electro-magnetometer data and controlled source electromagnetic surveys (CSEM). The overall objectives of the project were to determine the spatial distribution of gas and hydrate accumulations beneath the sea bed; to investigate and understand gas transport and escape mechanisms, their spatial distribution, and the controls on these; and to quantify gas and hydrate saturation values in situ within the pore spaces of the shallow sediment reservoirs. The research is focused on specific areas where significant accumulations of methane hydrate and active methane venting through the sea floor were observed and documented during the earlier JR211 cruise in 2008. This is a NERC funded project hosted by University of Southampton. The data held at BODC include multichannel seismic reflection, TOPAS sub-bottom profiler and 2D seismic reflection data in SEG-Y format. No further data are expected.

  • Geological model comprising artificial ground and superficial deposits in the city of Cardiff. Undifferentiated bedrock is included beneath the superficial deposits. This model provides a geological framework model and calculated surfaces for the superficial deposits for the city of Cardiff, principally Till, Glaciofluvial deposits, Alluvium and Tidal Flat Deposits.

  • This dataset contains the results of a laboratory study investigating the dissolution of UO3•nH2O particles in dynamic sediment/groundwater column systems, representative of the shallow subsurface at the Sellafield Ltd. site, UK. Measurements were carried out to determine the extent of uranic particle dissolution and the speciation of dissolved uranium within the columns under contrasting biogeochemical conditions (oxic and electron-donor amended). Columns effluents were analysed periodically for key biogeochemical indicators (nitrate, sulfate) and trace metals (iron, manganese, uranium) and systems were sacrificed after 6 and 12 months of groundwater flow. Upon sacrifice, columns were cross-sectioned, and the sediment structure preserved for synchrotron micro-focus X-ray Fluorescence (XRF) mapping, and uranium L-edge X-ray Absorption Spectroscopy (XAS) measurements. Sub-samples of column sediments were also analysed for acid extractable metals, microbial abundance and classification and bioavailable Fe(II) concentrations. Experiments were performed between March 2016 and March 2017. Subsequent analyses were performed between March 2017 and December 2018. This data was collected as part of the project: Understanding radioactive ‘hot’ particle evolution in the environment funded by the UK Natural Environment Research Council (grant NE/M014088/1). Full details about this nonGeographicDataset can be found at https://doi.org/10.5285/2702e1b0-13df-4ae4-9f91-4ac4bd07bbf1

  • This dataset presents modelled estimates of soil nitrogen concentration (% dry weight soil) at 1km2 resolution across Great Britain. A Generalized Additive Model approach was used with Countryside Survey soil nitrogen data from 2007 and including climate, atmospheric deposition, habitat, soil and spatial predictors. The model is based on soil nitrogen data from 913 locations across Great Britain and is representative of 0-15 cm soil depth. Soil N concentration was determined using a total elemental analyser. The Countryside Survey looks at a range of physical, chemical and biological properties of the topsoil from a representative sample of habitats across the UK. This work was supported by the Natural Environment Research Council award number NE/R016429/1 as part of the UK-SCAPE programme delivering National Capability. Full details about this dataset can be found at https://doi.org/10.5285/8ec2d5ae-5d19-4b58-8cf6-aafdad485bb2

  • The dataset details global positioning system (GPS) locations and elevations recorded for 1323 sampling sites across UK saltmarshes. Between 2018 and 2021, soil was sampled at 1323 locations as part of the Carbon Storage in Intertidal Environments (C-SIDE) project to facilitate the calculation of saltmarsh soil organic carbon stocks and burial rates. Sites were chosen to represent contrasting habitat types in the UK, in particular sediment types, vegetation and sea level history. The work was carried out under the NERC programme - Carbon Storage in Intertidal Environment (C-SIDE), NERC grant reference NE/R010846/1. Full details about this dataset can be found at https://doi.org/10.5285/d61b6033-be45-4682-b4dc-a2f95feefa7d

  • This data set includes a range of physico-chemical properties measured from topsoil within a wide range of land use types across Wales, collected as part of the Glastir Monitoring and Evaluation Programme (GMEP). The properties included are: soil organic matter (loss on ignition (LOI)), derived carbon concentration, total soil organic carbon (SOC), nitrogen, total soil phosphorous, Olsen-phosphorous (within improved land only), pH, electrical conductivity, soil bulk density of fine earth, fine earth volumetric water content when sampled and soil water repellency - water drop penetration time. The monitoring programme was set up by the Welsh Government in 2013 to monitor the effects of the Glastir agri-environment scheme on the environment and ran from 2013 to 2016. The field survey element was based on a stratified random sampling design of 300 x 1km square sites across Wales, and was managed by the Centre for Ecology & Hydrology. Full details about this dataset can be found at https://doi.org/10.5285/0fa51dc6-1537-4ad6-9d06-e476c137ed09

  • This is a spatial dataset containing polygons representing different geology types in the Moor House National Nature Reserve, northern Pennines, England. The survey was undertaken by G.A.L. Johnson under a grant by The Nature Conservancy in the 1950s and 1960s. Full details about this dataset can be found at https://doi.org/10.5285/0e3aefb2-ce86-4d09-8ff0-6d165dfd48db

  • This dataset presents modelled estimates of soil pH at 1km2 resolution across Great Britain. A Generalized Additive Model approach was used with Countryside Survey soil pH data from 2007 and including climate, atmospheric deposition, habitat, soil and spatial predictors. The model is based on soil pH data from 2446 locations across Great Britain and is representative of 0-15 cm soil depth. Soil pH was measured using 10g of field moist soil with 25ml de-ionised water giving a ratio of soil to water of 1:2.5 by weight. The Countryside Survey looks at a range of physical, chemical and biological properties of the topsoil from a representative sample of habitats across the UK. This work was supported by the Natural Environment Research Council award number NE/R016429/1 as part of the UK-SCAPE programme delivering National Capability. Full details about this dataset can be found at https://doi.org/10.5285/4b0e364d-61e6-48fb-8973-5eb18fb454cd

  • The data comprises river section, zone and test site delineation, winter Season average NDVI by section and zone 1989-2020, land cover maps seasonally 1989-2020, and derived land cover fractions by section and zone 1989-2020. The data was produced as part of a study to determine how changes in geomorphic form and dynamics due to human alteration to river flows and riparian land management relate to changes in vegetation communities in the Sutlej and Beas Rivers, India. Vegetated and other land cover, including water area, were quantified by winter season NDVI trends (in the plains of Punjab) and seasonal supervised classification of Landsat data for over a 30-year period. The work was supported by the Natural Environment Research Council (Grant NE/S01232X/1). Full details about this dataset can be found at https://doi.org/10.5285/9a96e199-34d0-46f9-9a64-140d300a2531

  • This dataset presents modelled estimates of soil carbon concentration (g kg-1) at 1km2 resolution across Great Britain. A Generalized Additive Model approach was used with Countryside Survey soil carbon data from 2007 and including climate, atmospheric deposition, habitat, soil and spatial predictors. The model is based on soil carbon data from 2446 locations across Great Britain and is representative of 0-15 cm soil depth. Loss-on-ignition (LOI) was determined by combustion of 10g dry soil at 375 degrees Celsius for 16 hours; carbon concentration was estimated by multiplying LOI by a factor of 0.55. The Countryside Survey looks at a range of physical, chemical and biological properties of the topsoil from a representative sample of habitats across the UK. This work was supported by the Natural Environment Research Council award number NE/R016429/1 as part of the UK-SCAPE programme delivering National Capability. Full details about this dataset can be found at https://doi.org/10.5285/3aaa52d3-918a-4f95-b065-32f33e45d4f6