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
BGS soil property data layers including parent material, soil texture, group, grain size, thickness and European Soil Bureau description. These data are delivered under the terms of the Open Government Licence (http://www.nationalarchives.gov.uk/doc/open-government-licence/), subject to the following acknowledgement accompanying the reproduced BGS materials: Contains British Geological Survey materials copyright NERC [year]. Contact us if you create something new and innovative that could benefit others firstname.lastname@example.org.
Data from laboratory experiments conducted as part of project NE/K011464/1 (associated with NE/K011626/1) Multiscale Impacts of Cyanobacterial Crusts on Landscape stability. Soils were collected from eastern Australia and transferred to a laboratory at Griffith University, Queensland for conduct of experiments. Soils were characterised before, during and after simulated rainfall to determine impact of rainfall on soil surface roughness and physical crusting. For two soils (#13 DL Clay_cyano; #14 DL sand_cyano) cyanobacterial crusts were grown on subsamples and these were used to compare the response of soils with, and without, cyanobacterial soil crusts to rainfall treatment. Rainfall intensity of 60 mm hr-1 was used and rainfall was applied for 2 minutes (achieving 2 mm application), 5 minutes (achieving 5 mm application), 2 minutes (achieving 2 mm application) at 24-hour intervals with soils dried at 35°C and 30% humidity between applications in a temperature/humidity-controlled room. Variables measured were soil texture, penetrometry, salinity, splash loss, infiltration, organic matter content, occurrence of ponding, three-dimensional topography. Details of rainfall simulator, growth of cyanobacteria (where soil #13 = Acbc, soil #14 = Bcbc) and all other methods can be found in Bullard et al. 2018, 2019. Bullard, J.E., Ockelford, A., Strong, C.L., Aubault, H. 2018. Impact of multi-day rainfall events onsurface roughness and physical crusting of very fine soils. Geoderma, 313, 181-192. doi: 10.1016/j.geoderma.2017.10.038. Bullard, J.E., Ockelford, A., Strong, C.L., Aubault, H. 2019. Effects of cyanobacterial soil crusts on surface roughness and splash erosion. Journal of Geophysical Research – Biogeosciences. doi: 10.1029/2018 tbc
The BGS has been commissioned by Defra to provide guidance on what are 'normal' levels of contaminant concentrations in English soils in support of the revision of the Part 2A Contaminated Land Statutory Guidance. The domain polygons and other data produced by this work are served as WMS here.
Countryside Survey topsoil pH and bulk density (g cm-3) data is representative of 0 - 15 cm soil depth. Topsoil 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; bulk density was estimated by making detailed weight measurements throughout the soil processing procedure. For topsoil pH and bulk density data, a total of 2614 cores from 591 1km x 1km squares across Great Britain were collected and analysed in 2007. Please see Emmett et al. 2010 for further details of sampling and methods (http://nora.nerc.ac.uk/id/eprint/5201/1/CS_UK_2007_TR3%5B1%5D.pdf). Estimates of mean values within selected habitats and parent material characteristics across GB were made using CS data from 1978, 1998 and 2007 using a mixed model approach. Please see Scott, 2008 for further details of similar statistical analysis (http://nora.nerc.ac.uk/id/eprint/5202/1/CS_UK_2007_TR4%5B1%5D.pdf). The estimated means of habitat /parent material combinations using 2007 data are modelled on dominant habitat and parent material characteristics derived from the Land Cover Map 2007 and Parent Material Model 2009, respectively. The parent material characteristic used was that which minimised AIC in each model (see Dataset Documentation). 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. Countryside Survey soils data are freely available under licence from the Environmental Information Data Centre catalogue. Full details about this dataset can be found at https://doi.org/10.5285/5dd624a9-55c9-4cc0-b366-d335991073c7
Supplementary material and link to published paper - Colluvium Supply in Humid Regions limits the Frequency of storm-triggered Landslides. DOI:10.1038/srep34438 Colluvium depth observations measured in the apexes of colluvial hollows in Macon County, North Carolina. Colluvium depths were measured using a soil tile probe (STD>0) and in pits excavated to bedrock (STD=0). Hollow axis gradient and hollow concavity were measured from a 6 m LiDAR derived DEM. Citation: PARKER, R. N., HALES, T. C., MUDD, S. M., GRIEVE, S. W. D. & CONSTANTINE, J. A. 2016. Colluvium supply in humid regions limits the frequency of storm-triggered landslides. Scientific Reports, 6, 34438.
Data from laboratory experiments conducted as part of project NE/K011464/1 (associated with NE/K011626/1) Multiscale Impacts of Cyanobacterial Crusts on Landscape stability. Soils were collected from two sites in eastern Australia and transferred to a laboratory at Griffith University, Queensland for conduct of experiments. Soils were A, a sandy loam, and B a loamy fine sand. Trays 120 mm x 1200 mm x 50 mm were filled with untreated soil that contained a natural population of biota. Soils were either used immediately for experiments (physical soil crust only: PC) or were placed in a greenhouse and spray irrigated until a cyanobacterial crust has grown from the natural biota. Growth was for a period of 5 days (SS), c.30 days (MS2) or c.60 days (MS1). Following the growing period (if applicable) trays were placed in a temperature/humidity controlled room at 35º and 30% humidity until soil moisture (measured 5 mm below the surface) was 5%. Trays were then subject to rainfall simulation. Rainfall intensity of 60 mm hr-1 was used and rainfall was applied for 2 minutes (achieving 2 mm application), 8 minutes (achieving 8 mm application) or 15 minutes (achieving 15 mm application). Following rainfall, trays were returned to the temperature/humidity-controlled room under UV lighting until soil moisture at 5 mm below the surface was 5%. A wind tunnel was then placed on top of each tray in turn and a sequential series of wind velocities (5, 7, 8.5, 10, 12 m s-1) applied each for one minute duration. On each tray the five wind velocities were run without saltation providing a cumulative dust flux. For the highest wind speed, an additional simulation run was conducted with the injection of saltation sands. Three replicates of each rainfall treatment were made. Variables measured include photographs, spectral reflectance, surface roughness, fluorescence, penetrometry, chlorophyll content, extracellular polysaccharide content, Carbon, Nitrogen and splash erosion and particle-size analysis (of wind eroded material). Details of rainfall simulator, growth of cyanobacteria, laser soil surface roughness characterisation and wind tunnel design and deployment in Strong et al., 2016; Bullard et al. 2018, 2019. Bullard, J.E., Ockelford, A., Strong, C.L., Aubault, H. 2018a. Impact of multi-day rainfall events on surface roughness and physical crusting of very fine soils. Geoderma, 313, 181-192. doi: 10.1016/j.geoderma.2017.10.038. Bullard, J.E., Ockelford, A., Strong, C.L., Aubault, H. 2018b. Effects of cyanobacterial soil crusts on surface roughness and splash erosion. Journal of Geophysical Research – Biogeosciences. doi: 10.1029/2018. Strong, C.S., Leys, J.F., Raupach, M.R., Bullard, J.E., Aubault, H.A., Butler, H.J., McTainsh, G.H. 2016. Development and testing of a micro wind tunnel for on-site wind erosion simulations. Environmental Fluid Mechanics, 16, 1065-1083.
This layer shows data collected mainly by the Geochemical Baseline Survey of the Environment (G-BASE) programme. Geochemical data are available for soil samples for the Humber-Trent and East Anglia atlas areas (see the Geochemical atlas areas layer). Samples for East Midlands and part of Southeast England have been collected and are currently either undergoing analysis or data conditioning. More than twenty urban areas have also been sampled and top soil analyses are available for these urban areas (Belfast, Cardiff, Corby, Coventry, Derby, Doncaster, Glasgow, Hull, Ipswich, Leicester, Lincoln, Manchester, Mansfield, Northampton, Nottingham, Peterborough, Scunthorpe, Sheffield, Swansea, Stoke, Telford, Wolverhampton and York). Regional samples are collected at an average density of one site per 2 square kilometres, urban sampling is at a density of 4 samples per square kilometre. Top soil samples are collected at a depth of 5 - 20cm. It is sieved through a 2mm mesh and milled to less than 150 microns. The data include analyses for some or all of the following elements by XRFS: Mg, P, K, Ca, Ti, Mn, Fe, V, Cr, Co, Ba, Ni, Cu, Zn, Ga, As, Se, Rb, Sr, Y, Zr, Nb, Mo, Pb, Bi, Th, U, Ag, Cd, Sn, Sb, Cs, La, Ce, Ge, Sc, Se, Br, Hf, Ta, W, Tl, Te and I. Loss on Ignition (LOI) and pH (in a slurry of 0.01 M CaCl2 ) is now routinely determined on 50% of regional and all urban samples.
Experimental results used to parameterise and a test a mathematical model of uranium diffusion and reaction in soil. The exeperiments and model are described in Darmovzalova J., Boghi A., Otten W., Eades, L., Roose T. & Kirk G.J.D. (2019) Uranium diffusion and time-dependent adsorption-desorption in soil: a model and experimental testing of the model. Eur. J. Soil Sci., doi: 10.1111/ejss.12814. The research was funded by NERC, Radioactive Waste Management Ltd and the Environment Agency through the Radioactivity and the Environment (RATE) programme (Grant Ref NE/L000288/1, Long-lived Radionuclides in the Surface Environment (LO-RISE)).
The British Geological Survey (BGS) in collaboration with the Environment Agency (EA) has developed a web-based tool that provides an indication of whether suitable conditions exist in a given area for Open-loop Ground Source Heat Pumps (GSHP). The tool is developed within a GIS and maps the potential for open-loop GSHP installations (heating/cooling output >100kW) in England and Wales at the 1:250,000 scale. Data layers from this tool are available to view in this service. The data in this service is available to access for free on the basis it is only used for your personal, teaching, and research purposes provided all are non-commercial in nature as described on http://www.bgs.ac.uk/about/copyright/non_commercial_use.html. Where commercial use is required, licences are available from the British Geological Survey (BGS). Your use of any information provided by the BGS is at your own risk. BGS gives no warranty, condition or representation as to the quality, accuracy or completeness of the information or its suitability for any use or purpose. All implied conditions relating to the quality or suitability of the information, and all liabilities arising from the supply of the information (including any liability arising in negligence) are excluded to the fullest extent permitted by law.