Keyword

Modelling

65 record(s)
 
Type of resources
Available actions
Topics
Keywords
Contact for the resource
Provided by
Years
Formats
Representation types
Update frequencies
Resolution
From 1 - 10 / 65
  • 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

  • This dataset comprises seven ensembles of hydrological model estimates of monthly mean and annual maximum river flows (m3s-1) on a 0.1° × 0.1° grid (approximate grid of 10 km × 10 km) across West Africa for historical (1950 to 2014) and projected future (2015 to 2100) periods. This dataset is the output from the Hydrological Modelling Framework for West Africa, or “HMF-WA” model. The ensembles correspond to CMIP6 (Coupled Model Inter-comparison Project Phase 6) historical and three projected future climate scenarios (SSP126, SSP245 and SSP585) with two future scenarios of water use. The scenarios of water use are (i) future water use that varies in line with projected population increases, and (ii) future water use is the same as present day. This dataset is an output from the regional scale hydrological modelling study from African Monsoon Multidisciplinary Analysis-2050 (AMMA-2050) project. Full details about this dataset can be found at https://doi.org/10.5285/346124fd-a0c6-490f-b5af-eaccbb26ab6b

  • 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

  • This model combines the carbon footprint of a reforestation project in the Peruvian amazon with a biomass model of the growing trees and a soil carbon model. The script aims at estimating the net carbon capture potential of a growing forest located in the Peruvian amazon and on degraded sandy soil only. It compares the emissions associated with setting up a reforestation plot (from seed reception to seedling transplant) with the expected carbon capture by the growing trees and increased soil carbon stock at a desired timescale. The model includes the production, use, and degradation of biochar. This model was produced within the Soils-R-GGREAT project, funded by NERC. Full details about this application can be found at https://doi.org/10.5285/ef45a7de-035a-486c-9cef-ee7f78a8efcf

  • 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

  • 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

  • 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

  • In situ meteorological forcing and evaluation data, and bias-corrected reanalysis forcing data for cold regions modelling at ten sites: one maritime (Sapporo, Japan), one arctic (Sodankylä, Finland), three boreal (Old Aspen, Old Jack Pine and Old Black Spruce, Saskatchewan, Canada) and five mid-latitude alpine (Col de Porte, France; Reynolds Mountain East, Idaho, USA, Senator Beck and Swamp Angel, Colorado, USA; Weissfluhjoch, Switzerland). The long-term datasets are the reference sites chosen for evaluating models participating in the Earth System Model-Snow Model Intercomparison Project (ESM-SnowMIP). Periods covered by the in situ data span from 1994 to 2016 with the period of available data varying by location from between 7 and 20 years of hourly meteorological data, with evaluation data (snow depth, snow water equivalent, albedo, soil temperature and surface temperature) available at varying temporal intervals. 30-year (1980-2010) time-series have been extracted from a global gridded surface meteorology dataset (Global Soil Wetness Project Phase 3) for the grid cells containing the reference sites, interpolated to one-hour timesteps and bias corrected.

  • This model code provides an example to demonstrate a new application of the 'learnr' R package to help authors to make elements of their research analysis more readily reproducible to users. It turns a R Markdown document to guided, editable, isolated, executable, and resettable code sandboxes where users can readily experiment with altering the codes exposed Full details about this application can be found at https://doi.org/10.5285/df57b002-2a42-4a7d-854f-870dd867618c