This is a web map service of the UKCEH digital river network of Great Britain (1:50,000). It is a river centreline network, based originally on OS 1:50,000 mapping. There are four layers: 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 is a web map view service for the Integrated Hydrological Units (IHU) of the United Kingdom. The IHU define geographical reference units for hydrological purposes including river flow measurement and hydrometric data collection in the UK. The layers in this service represent the following component polygon layers: Hydrometric Areas with Coastline; Hydrometric Areas without Coastline; Groups; Sections; and Catchments. Each layer represents a different level of spatial detail. The coarsest level, Hydrometric Areas, is provided in two versions to meet differing user needs. Each Hydrometric Area is made up of one or more Groups. Each Group carries a name constructed from names of the major river flowing through the Group, the major river flowing into the Group, the major river into which the Group flows, and in some cases also from local county names. Each Group is made up of smaller units called Sections. A Section is the drainage area of a watercourse between two confluences. Only confluences of named watercourses were considered. Similarly to Groups, each Section carries a name constructed from names of the major river flowing through the Section, the major river flowing into the Section, and the major river into which the Section flows. Catchments represent the full area upstream from an outlet of every Section. Polygons within each layer do not have gaps and, with the exception of Catchments, polygons within one layer do not overlap. The Hydrometric Areas with Coastline layer covers Great Britain and Northern Ireland, but all other layers currently cover Great Britain only as no dataset with river geometries and names with suitable detail is available for Northern Ireland.

The dataset contains high-resolution flow transects that were obtained from representative sites at six rivers within sub-catchments of contrasting geology (clay, greensand, chalk) of the Hampshire River Avon catchment (UK). Data were obtained from field-based measurements in seasonal campaigns conducted between spring 2013 and winter 2014. Full details about this dataset can be found at https://doi.org/10.5285/16df35a9-90ab-4273-8b6c-5ef3648ec76d

This dataset is a model output, from the Grid-to-Grid hydrological model driven by observed climate data (CEH-GEAR rainfall and Oudin temperature-based potential evaporation). It provides monthly mean flow (m3/s) and soil moisture (mm water/m soil) on a 1 km grid for the period 1891 to 2015. To aid interpretation, two additional spatial datasets are provided: - Digitally-derived catchment areas on a 1km x 1km grid - Estimated locations of flow gauging stations on a 1km x 1km grid and as a csv file. The data were produced as part of MaRIUS (Managing the Risks, Impacts and Uncertainties of drought and water Scarcity), which was a UK NERC-funded research project (2014-2017) that developed a risk-based approach to drought and water scarcity (http://www.mariusdroughtproject.org/). Full details about this dataset can be found at https://doi.org/10.5285/f52f012d-9f2e-42cc-b628-9cdea4fa3ba0

This data resource contains information on anthropogenic litter from the Portoviejo River, in Ecuador, collected between years 2021 and 2022. This work is part of the Natural Environment Research Council project “Reducing the impacts of plastic waste in the Eastern Pacific Ocean” (NE/V005448/1). The purpose of collecting this dataset was to obtain consistent observational data of solid waste contamination in a South American river system using a newly developed clean-up technology called the Azure System. The dataset contains information of weight (in kilograms) of different categories of anthropogenic litter collected using the Azure System, a floating barrier designed as a litter extraction tool for rivers. The system was developed by Ichthion Limited (https://ichthion.com/), who were also responsible for data collection on site. The barrier was installed at the city of Portoviejo, where litter was collected from February 2021 until December 2022 and quantities were reported weekly for each month. Full details about this dataset can be found at https://doi.org/10.5285/e78e1cef-e30b-4313-8733-c03e1a7b7b2f

These data include greenhouse gas concentrations and physio-chemical water properties for the Clyde estuary in Scotland to support understanding of the GHG sources and sinks and their associated mechanisms in a highly stratified, temperate urban estuary. These measurements look at the changes in GHG along the Clyde estuary taking measurements from land to sea down the estuary on the ebb tide at both the surface and bed so the impact of location, river flow, wastewater treatment outflows and stratifications can be understood. Full details about this dataset can be found at https://doi.org/10.5285/a22b495e-b2cd-43cd-95b7-8712b64dc0da

This dataset is model output from the GR4J lumped catchment hydrology model. It provides 500 model realisations of daily river flow, in cubic metres per second (cumecs, m3/s), for 303 UK catchments for the period between 1891-2015. The modelled catchments are part of the National River Flow Archive (NRFA) (https://nrfa.ceh.ac.uk/) and provide good spatial coverage across the UK. These flow reconstructions were produced as part of the Research Councils UK (RCUK) funded Historic Droughts and IMPETUS projects, to provide consistent modelled daily flow data across the UK from 1891-2015, with estimates of uncertainty. This dataset is an outcome of the Historic Droughts Project (grant number: NE/L01016X/1). The data are provided in two formats to help the user account for uncertainty: (1) a 500-member ensemble of daily river flow time series for each catchment, with their corresponding model parameters and evaluation metric scores of model performance. (2) a single river flow time series (one corresponding to the top run of the 500), with the maximum and minimum daily limits of the 500 ensemble members. Full details about this dataset can be found at https://doi.org/10.5285/f710bed1-e564-47bf-b82c-4c2a2fe2810e

This is part of an ongoing long-term monitoring dataset of surface temperature, surface oxygen, water clarity, water chemistry and phytoplankton chlorophyll a from fortnightly sampling at the South Basin of Windermere in Cumbria, England that began in 1945 for some variables. The data have been collected by the UK Centre for Ecology & Hydrology (UKCEH). The data available to download comprise surface temperature (TEMP) in degree Celsius, surface oxygen saturation (OXYG) in % air-saturation, Secchi depth (SECC) in metres, alkalinity (ALKA) in µg per litre as CaCO3 and pH. Total ammoniacal nitrogen (NH4N), total oxidised nitrogen (TON), soluble reactive phosphate (PO4P), total phosphorus (TOTP), dissolved reactive silicon expressed as SiO2 (SIO2) and phytoplankton chlorophyll a (TOCA) are all given in µg per litre. Water samples are based on a sample integrated from 0 to 7m. All data are from January 2023 until the end of 2023. Full details about this dataset can be found at https://doi.org/10.5285/23dfa136-82f4-4c96-8df0-f44c1798f7b4

This dataset contains high-resolution (5-minute) raw, atmospheric corrected and mean sea level adjusted water level data for 9 flood storage areas (FSAs) in the Littlestock Brook catchment (a tributary of the River Evenlode, Thames Basin) from 2018 to 2022. The dataset also includes the estimated 9 x FSA stored volume time-series, estimated using a depth-stored volume lookup table for each FSA, produced from a digital elevation model of each feature and a depth-area-volume toolset. The annual barometric pressure time-series used to correct water level is also provided. This dataset was collected by UKCEH as part of a hydrological monitoring programme for the Littlestock Brook Natural Flood Management scheme. This work was supported by the SPITFIRE NERC DTP (NE/L002531/1) and the SCENARIO NERC DTP (NE/L002566/1). Full details about this dataset can be found at https://doi.org/10.5285/cf70f798-442a-4775-963c-b6600023830f

This dataset contains biogeochemical measurements of surface water, sampled across Loch Etive, Scotland, between the 3rd and 7th of October 2022. The dataset encompasses 23 locations including nine open loch stations, four fish-farm adjacent loch sites, six river inflows, and four process experiment river sites, enabling a comparison of water chemistry across marine, freshwater, and anthropogenically influenced environments. Surface water samples were collected and analysed for an extensive range of biogeochemical parameters. In-field measurements included water temperature, pH, dissolved oxygen, and specific conductivity. Laboratory analyses comprised: - Alkalinity - Major nutrients, including nitrate, nitrite, ammonium, soluble reactive phosphorus (SRP), and silica - Dissolved and total organic and inorganic carbon and nitrogen (DOC, TIC, TDN) - Trace elements and rare earth elements (REEs), including lithium, barium, aluminium, and a full suite of lanthanides - Stable isotope composition of oxygen (δ18O), determined via isotope ratio mass spectrometry - Chromophoric and fluorescent dissolved organic matter (CDOM/FDOM), with derived indices such as fluorescence index (FI), biological index (BIX), and humification index (HIX) In addition to water chemistry, particulate samples were collected and analysed for total suspended solids (TSS), particulate organic matter (POM), particulate inorganic matter (PIM), chlorophyll-a concentration, and particulate organic carbon/nitrogen (POC/PON). Phytoplankton community composition was assessed by flow cytometry, quantifying major groups including diatoms, pico- and nano-chlorophytes, cryptophytes, and cyanobacteria. This comprehensive dataset is intended to inform biogeochemical process understanding in polar analogue environments and to validate analytical workflows and inter-institutional protocols. Full details about this dataset can be found at https://doi.org/10.5285/50f4344e-a79a-4e1f-a9ee-e7985ed847cd