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 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

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

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

[This dataset is embargoed until January 1, 2024]. This dataset comprises multiple baseline and future ensembles of hydrological model estimates of monthly mean and annual maximum river flows (m3s-1) on a 0. 0.008333° × 0. 0.008333° grid (approximate grid of 1 km × 1 km) across Peninsular Malaysia. Specifically, these are provided for historical (1971 to 2005) and projected future (2006 to 2099) periods, for 3 Representative Concentration Pathways (RCPs). This dataset is the output from the Hydrological Modelling Framework for Malaysia, or “HMF-Malaysia” model. The projected future hydrology simulations are provided for CORDEX-SEA (Coordinated Regional Downscaling Experiment – South East Asia) three RCPs (RCP2.6, RCP4.5 and RCP8.5) assuming (i) current artificial influences (CAI) such as water transfers and diversions and (ii) planned future artificial influences (FAI). This dataset is an output from the hydrological modelling study from the Malaysia - Flood Impacts Across Scales (FIAS) project. Full details about this dataset can be found at https://doi.org/10.5285/9b70bebe-189c-4ae8-9aee-1bb1db7b1ad5

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.

The dataset describes the inundation results simulated by high-performance integrated hydrodynamic modelling system (HiPIMS) model for the pluvial flooding and fluvial flooding in Can Tho city Vietnam. Wherein, the pluvial flooding results simulated by HiPIMS are driven by the design rainfall in the 2, 5, 10, 20, 50, and 100 years return period, respectively, and the fluvial flooding results simulated by HiPIMS are driven by the river water level boundary in 2011. Full details about this dataset can be found at https://doi.org/10.5285/585ce4f2-0070-490f-adb2-ed7f1207605b

This dataset is a model output from the European Monitoring and Evaluation Programme (EMEP) model applied to the UK (EMEP4UK) driven by Weather and Research Forecast model meteorology (WRF). It provides UK estimates annual averaged atmospheric composition at approximately 5Km grid for the year 2015 for a set of vegetation removal experiments. * UK current vegetation * UK no vegetation * UK Urban current vegetation * UK No urban vegetation * UK Urban 25% open greenspace conversion * UK Urban 50% open greenspace conversion The EMEP model version used here is the rv4.10 and rv4.17, and the WRF model version is the 3.7.1. This work was supported by the Natural Environment Research Council award number NE/R016429/1 as part of the UK-SCAPE programme delivering National Capability and the Office of National Statistics to support the ONS-Defra natural capital accounting programme in the UK. Full details about this dataset can be found at https://doi.org/10.5285/bad6721c-574b-4229-b023-c7b13ae4c099

Data were collected in 2015, 2016 and 2017 to provide Digital Surface Models (DSM) for two sections of the South Saskatchewan River, Canada. DSMs were generated using aerial plane images with a 0.06m ground resolution, captured at a height of c. 1500 m from a fixed-wing aeroplane with an UltraCamXp sensor. DSMs were generated as part of NERC project NE/L00738X/1. DSMs were constructed using imagery obtained on four occasions (13th May 2015; 2nd Sept 2016; 8th June 2017; and 12th June 2017). The dataset consists of eight DSMs; one for each of the two river sections on each of the four dates. Full details about this dataset can be found at https://doi.org/10.5285/13695138-227f-4d85-9049-0a9cba9e1867