Friction coefficient and frictional stability (rate & state parameter) data for triaxially compressed direct shear experiments on kaolinite-rich china clay and Mg-montmorillonite fault gouges (<2micron grain size). A total of 19 raw experimental datasets are presented as detailed in the index files: 13 on kaolinite-rich china clay, and 6 on cation-exchanged Mg-Montmorillonite. The raw data files, logged at either 1 or 2Hz, comprise confining pressures, upstream and downstream fluid pressures, force experienced by the direct shear assembly during triaxial compression, and absolute volumes of the confining pressure and fluid pressure reservoirs. Data is provided as measured by gauges in the pressure vessel in Volts, and also as calculated in MPa, kN and mm3. Also presented are the outputs of MATLAB models run to simulate the rate and state parameters k, a, b, dc and f0 for each experiment, with error data presented as 2sigma and standard error values. Parameters were determined using a non-linear least-squares fitting routine with the machine stiffness treated as a fitting parameter (c.f. Noda and Shimamoto, 2009). Data were fit by a single set of state variables (a, b, dc) with a linear detrend. Also presented are the outputs of Specific Thermogravimetric Analyses on kaolinite-rich china clay and Mg-montmorillonite.
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
NERC grant NE/R013535/1. Here we present the dataset collected during a brine-CO2 flow-through test using a synthetic sandstone with oblique fractures, performed under realistic reservoir conditions stress. We monitored geophysical, mechanical and transport properties, for drainage and imbibition conditions, representative of the injection and post-injection stages of the CO2 storage process. We collected ultrasonic P- and S-wave velocities and their respective attenuation factors, axial and radial strains, electrical resistivity, pore pressure, temperature and brine and CO2 partial flows (from which relative permeability was later calculated).
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
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
This is a 1:10,000 scale Bedrock geological map for some 800 km2 of the seabed across Weymouth Bay in Dorset. It joins seamlessly to the onshore BGS 1:10,000 scale Digital Geological Mapping (DiGMapGB-10) and therefore shows the coastal geology in detail. It comprises bedrock polygons, faults and limestone bed lines. The map was produced in 2015-16 by digitising against a seamless on- to offshore-shore elevation surface generated from high (1 m bin) resolution bathymetry and coastal Lidar data, collected as part of the Dorset Integrated Seabed Survey (DORIS) project and the Regional Coastal Monitoring Programme of England, made available by the Channel Coastal Observatory under the Open Government Licence. This map has been produced under the auspices of the Marine Environmental Mapping Programme (MAREMAP), in collaboration between the BGS and the University of Southampton. The map itself should be referred to as: Westhead, R K, Sanderson, D J, Dix, J K. 2016. Bedrock map for the offshore Weymouth Bay area, with seamless coastal joint to BGS onshore (DiGMapGB-10) mapping. Bedrock Geology. 1:10 000 (Marine Environmental Mapping Programme, MAREMAP)
Direct geological observations made during field work, tied to positional information collected by hand-held GPS.
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.
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.
The file contain groundwater level/depth (WL), Groundwater and Surface Water Quality data (EC (micro-siemens per centimetre or µS/cm), Temperature (°C) and pH) for 49 points under fortnightly monitoring relevant to Gro for GooD research project in Kwale County, Kenya. Blank - Data not available. Gro for GooD: Groundwater Risk Management for Growth and Development