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804 record(s)

 

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    Direct geological observations made during field work, tied to positional information collected by hand-held GPS.

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    This data set contains land cover/land use data for the year 1990 and 2015 obtained through processing of Landsat images of US Geological Survey. These data sets were obtained through a supervised classification carried out with Landsat 8 image for 2015; Landsat 4 and 5 were used for land use classification of 1990. Gro for GooD: Groundwater Risk Management for Growth and Development

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    The file contain groundwater level/depth (WL), Groundwater and Surface Water Quality data (EC (micro-siemens per centimetre or µS/cm), Temperature (degrees C) and pH) for 49 points under fortnightly monitoring relevant to Gro for GooD research project in Kwale County, Kenya. Blank - Data not available. Note this is same dataset as NGDC record number 118189 with extended time series. Gro for GooD: Groundwater Risk Management for Growth and Development

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    These data files represent simulations of hydrated cation vacancies in the mantle mineral forsterite (Mg2SiO4) undertaken using the CASTEP atomic scale simulation code (http://www.castep.org/). Results from these simulations allow the structure relative stability of different defect configurations to be compared. Three types of cation vacancies are considered (M1, M2 and Si) each decorated by hydrogen in order to charge balance the system. For M1 and M2 this results in multiple configurations (with hydrogen bonded to different oxygen atoms around the vacant site). For Si there is only one configuration as all four oxygen atoms are bonded to hydrogen for the charge neutral defect. For each configuration input files detail the initial atomic structure of the defect along with simulation parameters. Output files record the progress of the simulation, the final atomic structure, the energy of this structure, and various predicted properties of the structure. Only ASCII output data is included as binary data created by CASTEP is not intended to be portable, and can easily be recreated using the ASCII files.

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    The dataset consist of daily rainfall data for 22 manual rain gauge stations installed by Gro for GooD project within and about the study area. The installed stations covering four river catchments name Ramisi River, Mukurumudzi River, Mtawa River and Mwachema River in Kwale County. The dataset period is from January 2016 to September 2017. Gro for GooD: Groundwater Risk Management for Growth and Development

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    The file consists of data sets from Kwale County, Kenya that describe biophysical characteristics of the catchment overlaid as layers. These include Basin, Sub-basins extent, Soil, DEM, Landuse, Slope, Rivers, Outlets and Monitoring Points. The data are in raster, shapefile, polygon, polyline and point format.

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    Porewaters from IODP Expedition 366 were extracted from serpentinite mud volcano sediments onboard the RV JOIDES Resolution (see Fryer et al, 2017; 2018 for details). Selected samples were then analysed at the University of Southampton for 87Sr/86Sr and boron isotopes and SUERC for stable hydrogen and oxygen isotope data. The strontium isotope data has recently been accepted for publication (Albers et al., 2019 (In Press) Fluid–rock interactions in the shallow Mariana forearc: carbon cycling and redox conditions, Solid Earth special issue "Exploring new frontiers in fluids processes in subduction zones").

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    The dataset consists of daily rainfall data for 23 manual rain gauge stations installed by Gro for GooD project within and about the study area. The installed stations covering four river catchments name Ramisi River, Mukurumudzi River, Mtawa River and Mwachema River in Kwale County. The dataset period is from January 2016 to November 2018. Gro for GooD: Groundwater Risk Management for Growth and Development

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    Data derived from NERC grant NE/I024127/1 1) 36Cl data and supporting chemistry. This folder contains the 36Cl concentration data, data on sample locations on fault planes, major and trace element concentrations, and similar data for upper slope samples. 2) Depth versus density data for trenches in colluvium. This folder contains measurements of weights and volumes of colluvial material removed from trenches for some of the 36Cl sites. These data are used to calculate colluvial densities to inform modelling of the 36Cl data. 3) Field Site Documentation. This folder contains field data and field photographs and movies of the sample sites. It also contains a file that summarises interpretations of the data in this folder, to provide numerical values needed to support modeling the 36Cl data to recover fault slip histories. 4) Google Earth Files to locate sample sites. This folder contains kmz files for Google Earth to locate the sample sites. 5) Terrestrial LiDAR data for each 36Cl sample sites. This folder contains Terrestrial LiDAR data (from a LiDAR on a tripod).

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    Image data published in AGU paper "Estimation of Capillary Pressure in Unconventional Reservoirs Using Thermodynamic Analysis of Pore Images". The images of unconventional shale rock pores were captured using nano-CT and SEM imaging methods. Images are segmented into fluid (or pore) and rock phases and are stored in RGB format as JPG files. Images were used to produce the plots and data presented in the above referenced paper.