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geoscientificInformation

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    The data set contains Soil Data used in the Gro for GooD Project in Kwale, Kenya based on KENSOTER database and soil survey in study area. The KENSOTER dataset, specific for Kenya, was compiled by the Kenya Soil Survey (KSS) and ISRIC and released in 2006 where ISRIC plays a lead role in methodology development and programme implementation (http://www.isric.org/projects/soil-and-terrain-soter-database-programme). The dataset includes over 600 soil components, including synthetic profiles, which have been derived from soil survey reports and expert knowledge. The second version of the dataset which has been made available includes additional soil profile database and is also used for the assessment of soil carbon stocks. The gaps in the measured soil profile data have been filled using a step-wise procedure which includes three main stages: (1) collate additional measured soil analytical data where available; (2) fill gaps using expert knowledge and common sense; (3) fill the remaining gaps using a scheme of taxotransfer rules. Parameter estimates are presented by soil unit for fixed depth intervals of 0.2 m to 1 m depth for: organic carbon, total nitrogen, pH(H2O), CECsoil, CECclay, base saturation, effective CEC, aluminium saturation, CaCO3 content, gypsum content, exchangeable sodium percentage (ESP), electrical conductivity of saturated paste (ECe), bulk density, content of sand, silt and clay, content of coarse fragments, and available water capacity. The data have recently been used for the Green Water Credit (GWC) programme in the Upper Tana River Valley. This dataset was prepared for the Gro for GooD project by Mike Thomas, Rural Focus Ltd., Kenya; John Gathenya, JKUAT, Kenya. Gro for GooD: Groundwater Risk Management for Growth and Development

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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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    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)

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    The newGeoSure Insurance Product (newGIP) provides the potential insurance risk due to natural ground movement. It incorporates the combined effects of the 6 GeoSure hazards on (low-rise) buildings: landslides, shrink-swell clays, soluble rocks, running sands, compressible ground and collapsible deposits. These hazards are evaluated using a series of processes including statistical analyses and expert elicitation techniques to create a derived product that can be used for insurance purposes such as identifying and estimating risk and susceptibility. The evaluated hazards are then linked to a postcode database - the Derived Postcode Database (DPD), which is updated biannually with new releases of Ordnance Survey Code-Point® data (current version used: 2020.1). The newGIP is provided for national coverage across Great Britain (not including the Isle of Man). This product is available in a range of GIS formats including Access (*.dbf), ArcGIS (*.shp) or MapInfo (*.tab). The newGIP is produced for use at 1:50 000 scale providing 50 m ground resolution.

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    High frequency (100 Hz) data from two horizontal induction coils measuring the Earth's magnetic field at the Eskdalemuir Observatory in the United Kingdom. The data covers the period from January 2018 to December 2018. Also included are examples of Matlab code and the frequency calibration files to convert to the raw data to SI units. Thumbnail spectrograms and metadata are also supplied.