This dataset provides hydro-meteorological timeseries and landscape attributes for 671 catchments across Great Britain. It collates river flows, catchment attributes and catchment boundaries from the UK National River Flow Archive together with a suite of new meteorological timeseries and catchment attributes. Daily timeseries for the time period 1st October 1970 to the 30th September 2015 are provided for a range of hydro-meteorological data (including rainfall, potential evapotranspiration, temperature, radiation, humidity and flow). A comprehensive set of catchment attributes are quantified describing a range of catchment characteristics including topography, climate, hydrology, land cover, soils, hydrogeology, human influences and discharge uncertainty. This dataset is intended for the community as a freely available, easily accessible dataset to use in a wide range of environmental data and modelling analyses. A research paper (Coxon et al, CAMELS-GB: Hydrometeorological time series and landscape attributes for 671 catchments in Great Britain) describing the dataset in detail will be made available in Earth System Science Data (https://www.earth-system-science-data.net/). Full details about this dataset can be found at https://doi.org/10.5285/8344e4f3-d2ea-44f5-8afa-86d2987543a9
This dataset contains channel cross-sections for the River Lambourn and Westbrook Channel at the Centre for Ecology & Hydrology (CEH) River Lambourn Observatory at Boxford, Berkshire. The CEH River Lambourn Observatory located in the county of Berkshire, UK (51.445o N 1.384o W) comprises a 600 m reach of the River Lambourn with 10 hectares of associated riparian wetland. The Westbrook Channel divides the wetland into northern and southern meadows. Channel cross-section surveys were conducted using Trimble R8TM dGPS for the Westbrook Channel in May 2013 and the River Lambourn in November 2013. Full details about this dataset can be found at https://doi.org/10.5285/e918198d-42e1-48e6-85ba-3916e20a6658
This data set comprises of weekly water quality monitoring data of seven sites along the River Thames, UK, and fifteen of its major tributaries from February 2009 to February 2013. Parameters measured were phosphorus and nitrogen species, dissolved reactive silicon, water temperature, pH, Gran alkalinity, suspended solids, chlorophyll and major dissolved anions (fluoride, chloride, bromide, sulphate) and cations (sodium, potassium, calcium, magnesium, boron). Dissolved and total iron, manganese, zinc, copper concentrations have also been produced from August 2010 to February 2013. The accompanying daily river flow data are also supplied. Samples were taken as part of the Centre for Ecology & Hydrology's Thames Initiative monitoring programme. Full details about this dataset can be found at https://doi.org/10.5285/e4c300b1-8bc3-4df2-b23a-e72e67eef2fd
[This dataset is embargoed until June 1, 2021]. The dataset provides raster gridded estimates of open water and inundated vegetation for the Barotseland Region in Western Zambia. There are a total of 55 images covering the period 2016-2019 at a spatial resolution of 10m. The images were generated using an automatic classification routine applied to Sentinel-1 radar imagery, with classification refinements made using ancillary datasets such as the Global Urban Footprint, and the Height Above Nearest Drainage terrain derivative generated using SRTM digital elevation data. These data are valuable for a range of applications including public health and water resources. Full details about this dataset can be found at https://doi.org/10.5285/4ef558d2-05d4-4ae2-988e-a5c2450b95dd
This is a view service of the CEH 1:50k rivers dataset. This is a river centreline network, based originally on OS 1:50,000 mapping. There are four layer: rivers; canals; surface pipes (man-made channels such as aqueducts and leats) and miscellaneous channels (including estuary and lake centre-lines and some underground channels).
This dataset comprises river centrelines, digitised from OS 1:50,000 mapping. It consists of four components: rivers; canals; surface pipes (man-made channels for transporting water such as aqueducts and leats); and miscellaneous channels (including estuary and lake centre-lines and some underground channels). This dataset is a representation of the river network in Great Britain as a set of line segments, i.e. it does not comprise a geometric network.
This dataset contains logged and manual observations of groundwater levels for piezometers at the Centre for Ecology & Hydrology (CEH) River Lambourn Observatory wetlands at Boxford, Berkshire, for the period February 1 2012 to January 16 2015 (01/02/2012 to 16/01/2015). The CEH River Lambourn Observatory located in Berkshire, UK (51.445o N 1.384o W) comprises c. 10 ha of riparian wetland which is bordered to the east by a 600 m stretch of the River Lambourn. The subsurface architecture comprises bedrock Chalk, overlain by gravels and then peat. Also presented are datums and ground levels for each piezometer, with data available for groundwater levels in peat, gravels and chalk. Groundwater heads were routinely checked at all piezometers by manually dipping observed water levels. At selected piezometers groundwater heads were monitored every 15 minutes using pressure transducers. Piezometers were not anchored to bedrock, though piezometer datum movement due to peat compressibility with saturation was discounted after comparisons of level surveys. Full details about this dataset can be found at https://doi.org/10.5285/f4b8ca09-31a7-4f20-9fc1-eb35744e28d6
The dataset comprises a derived freshwater flux field for the Southern Ocean. This flux field is the rate of freshwater (m^-3 s^-1) entering each point of a grid covering the Southern Ocean, divided by the surface area (m^-2) represented by each grid point, which gives a flux (m s^-1) at each grid point. It was produced using up-to-date freshwater data from ice shelves, icebergs, and rivers over the period 2010-2015 and integrated over a surface encompassing Antarctica and surrounding waters. These data are intended for use in the Southern Ocean State Estimate (SOSE) iteration of the MIT General Circulation Model (MITgcm), but can be adapted for use on a different grid or model. The flux data are in units of m yr-1, on a 2160x320 grid. MATLAB scripts and tables of runoff data are available and show how the field was produced, how the data can be used and how different data can produce the field for a different grid. The field was created to update the accuracy of the freshwater input to a model based on SOSE, and to stabilise it with respect to the formation of open-ocean polynyas. This field was produced by Mark Hammond under the supervision of Dr Dan Jones at the British Antarctic Survey.
This data contains the time series flow discharge results of hydrological simulation of the River Trent at Colwick using UKCP09 Weather Generator inputs for a variety of time slices and emissions scenarios. The Weather Generator (WG) inputs were run on a hydrological model (Leathard et al., unpublished), calibrated using the observed record 1961-2002. Each simulation is derived from 100 30-year time series of weather at the WG location 4400355 for Control, Low, Medium and High emissions scenarios for the 2020s, 2030s, 2040s, 2050s and 2080s time slices. The datasets include the relevant accompanying input WG data. Full details about this dataset can be found at https://doi.org/10.5285/986d3df3-d9bf-42eb-8e18-850b8d54f37b
Data consist of modelled estimates of observed/expected Biological Monitoring Working Party (an index for measuring the biological quality of rivers using selected families of macroinvertebrates as biological indicators) scores for freshwater streams across Great Britain (GB). The BMWP scores (1-10) are based on the principle that macroinvertebrates differ in their perceived sensitivity or tolerance to organic pollution (i.e. nutrient enrichment). Values greater than 1 indicate high water quality. Data pooled across two survey years (1998 and 2007) was used to model the relationships between headwater stream quality and catchment/stream characteristics for headwater streams across GB based on known relationships for headwater streams in Countryside Survey squares. Modelled estimates of stream water quality were based on a Boosted Regression Tree modelling approach . Full details about this dataset can be found at https://doi.org/10.5285/85e7beb6-e031-4397-a090-841b8c907d1b