nonCciKeyword

Modelling

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  • Estimates of annual volumes of manure produced by six broad farm livestock types for England and Wales at 10 km resolution, modelled with MANURES-GIS [1]. The farm livestock classes are: dairy cattle; beef cattle; pigs; sheep and other livestock; laying hens; broilers and other poultry. The quantities produced by each type are subsequently apportioned into managed and field-deposited manure. The managed manure sources are categorised as beef farmyard manure, beef slurry, dairy farmyard manure, dairy slurry, broiler litter, layer manure, pig farmyard manure, pig slurry and sheep farmyard manure. The destinations are recorded as grass, winter arable, spring arable and direct excreta when grazing. For each 10 km square, the quantity of manure going from each source to each destination is estimated. The values specify amount of excreta, in kilograms for solid manure and in litres for liquid manure. [1] ADAS (2008) The National Inventory and Map of Livestock Manure Loadings to Agricultural Land: MANURES-GIS. Final Report for Defra Project WQ0103 Full details about this dataset can be found at https://doi.org/10.5285/517717f7-d044-42cf-a332-a257e0e80b5c

  • Estimates of discharged loads of nitrogen, phosphorous and fine-grained sediments to rivers in England and Wales from multiple sector sources, reported at Water Framework Directive catchment scale, from the SEctor Pollutant AppoRtionment for the AquaTic Environment (SEPARATE) modelling framework [1]. The SEPARATE framework integrates information on pollutant emissions from multiple sources to provide apportionment and summarises these estimates on the basis of the WFD cycle 2 waterbodies for England and Wales. The estimated loads are expressed as tonnes per year. Sources are both diffuse and point sources. Diffuse sources include agriculture, urban, river channel banks, atmospheric deposition; point sources include sewage treatment works, septic tanks, combined sewer overflows, storm tanks. The pollutant loads and percentages are given as cumulative values with the values from the upstream catchment. Phosphorous is reported both as dissolved phosphorous and total phosphorous. [1] Zhang, Y.; Collins, A.L.; Murdoch, N.; Lee, D.; Naden, P.S. (2014) Cross sector contributions to river pollution in England and Wales: Updating waterbody scale information to support policy delivery for the Water Framework Directive. Environmental Science & Policy, 42, pp 16-32. doi:10.1016/j.envsci.2014.04.010

  • Gridded potential evapotranspiration over Great Britain for the years 1961-2017 at 1 km resolution. This dataset contains two potential evapotranspiration variables: daily total potential evapotranspiration (PET; kg m-2) for a well-watered grass and daily total potential evapotranspiration with interception correction (PETI; kg m-2). The data are provided in gridded netCDF files. There is one file for each variable for each month of the data set. This data set supersedes the previous version as bugs in the calculation of the variables have been fixed (for all years), temporal coverage of both variables has been extended to include the years 2016-2017 and the netCDF metadata has been updated and improved. Full details about this dataset can be found at https://doi.org/10.5285/9116e565-2c0a-455b-9c68-558fdd9179ad

  • MultiMOVE is an R package that contains fitted niche models for almost 1500 plant species in Great Britain. This package allows the user to access these models, which have been fitted using multiple statistical techniques, to make predictions of species occurrence from specified environmental data. It also allows plotting of relationships between species' occurrence and individual covariates so the user can see what effect each environmental variable has on the specific species in question. The package is built under R 3.1.2 and depends on R packages 'leaps', 'earth', 'fields', 'mgcv', 'stringr', 'gsubfn', 'randomForest' and 'nnet'. Full details about this application can be found at https://doi.org/10.5285/94ae1a5a-2a28-4315-8d4b-35ae964fc3b9

  • [THIS APPLICATION HAS BEEN WITHDRAWN]. MultiMOVE is an R package that contains fitted niche models for almost 1500 plant species in Great Britain. This package allows the user to access these models, which have been fitted using multiple statistical techniques, to make predictions of species occurrence from specified environmental data. It also allows plotting of relationships between species' occurrence and individual covariates so the user can see what effect each environmental variable has on the specific species in question. The package is built under R 2.10.1 and depends on R packages 'leaps', 'earth', 'fields' and 'mgcv'. Full details about this application can be found at https://doi.org/10.5285/c4d0393e-ff0a-47da-84e0-09ca9182e6cb

  • These spatial layers contain risk factors and overall risk scores, representing relative risk of Phytophthora infection (Phytophthora ramorum and P. kernoviae), for heathland fragments across Scotland. Risk factors include climate suitability, proximity to road and river networks and suitability of habitat for key hosts of Phytophthora and were broadly concurrent with the period between 2007 and 2013. This research was funded by the Scottish Government under research contract CR/2008/55, 'Study of the epidemiology of Phytophthora ramorum and Phytophthora kernoviae in managed gardens and heathlands in Scotland' and involved collaborators from St Andrews University, Science and Advice for Scottish Agriculture (SASA), Scottish Natural Heritage (SNH), Forestry Commission, the Food and Environment Research Agency (FERA) and the Centre for Ecology & Hydrology (CEH). Full details about this dataset can be found at https://doi.org/10.5285/8f09b7e6-6daa-4823-b338-4edad8de1461

  • The dataset contains annual global plant respiration (and related diagnostics, such as Net Primary Productivity, Gross Primary Productivity and soil respiration), applicable for pre-industrial times (taken as year 1860) through to the end of the 21st Century (year 2100). The spatial resolution of the data is 2.5 degrees latitude x 3.75 degrees longitude. These diagnostics are outputs from the Joint UK Land Environment Simulator (JULES land surface model) under four different approaches to calcluate leaf respiration. Each of four sets contains a total of 34 runs, each driven by a different CMIP5 model climate pattern, using the Integrated Model Of Global Effects of climatic aNomalies (IMOGEN) system. These are for a "business-as-usual" approach to fossil fuel usage, as the Representative Concentration Pathway scenario RCP8.5. These simulations form the basis for new research paper by Huntingford et al (2017, under review). Full details about this dataset can be found at https://doi.org/10.5285/24489399-5c99-4050-93ee-58ac4b09341a

  • The WATCH forcing data (WFD) is a twentieth century meteorological forcing dataset for land surface and hydrological models. It consists of three/six-hourly states of the weather for global half-degree land grid points. It was generated as part of the EU FP 6 project "WATCH" (WATer and global CHange") which ran from 2007-2011. The data was generated in 2 tranches with slightly different methodology: 1901-1957 and 1958-2001, but generally the dataset can be considered as continuous. More details regarding the generation process can be found in the associated WATCH technical report and paper in J. Hydrometeorology. To understand how the data grid is formed it is necessary to read the attached WFD-land-long-lat-z files either in NetCDF or dat formats. The data covers land points only and excludes the Antarctica. Rainf or rainfall rate is the rainfall rate based on the Global Precipitation Climatology Centre (GPCC) bias corrected, undercatch corrected measured in kg/m2/s at 3 hourly resolution averaged over the next 3 hours and at 0.5 x 0.5 degrees spatial resolution. Please note that there is also a WFD Rainf CRU bias corrected dataset, but as the GPCC dataset is the preferred dataset only this rainfall dataset is available from the EIDC. These rainfall datasets contain rainfall data only and need to be combined with the respective WFD snowfall datasets to obtain precipitation data.

  • This application is an implementation of the Ecological Risk due to Flow Alteration (ERFA) method in R language. This method assesses the potential impact of flow change on river ecosystems. Although the code was developed with a geographical focus on southeast Asia (example datasets are provided for the Mekong River Basin), it can be applied for any location where baseline and scenario monthly river flow time series are available. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. Full details about this application can be found at https://doi.org/10.5285/98ec8073-7ebd-44e5-aca4-ebcdefa9d044

  • This is an application providing code for the non-parametric comparison of soil depth profiles, and testing for significant differences between soil depth profiles, using bootstrapped Loess (local) regressions (BLR). The BLR approach was developed to be able to compare and test for significant differences in potentially non-linear depth profiles of soil properties across land use transitions, which does not need to meet any parametric distribution assumptions, and is intended to be generally applicable regardless of specific contexts of land use and soil type. A small dataset is provided with the code to demonstrate the BLR approach and its outputs. The code was written using the R statistical programming language and provides two examples of the BLR approach. This application was created by the Centre for Ecology & Hydrology at Lancaster in 2015 during the ELUM (Ecosystem Land Use Modelling & Soil Carbon GHG Flux Trial) project, which was commissioned and funded by the Energy Technologies Institute (ETI). Full details about this application can be found at https://doi.org/10.5285/d4f92cd8-43e8-49e4-8f9e-efcc0e3b2478