Topic
 

inlandWaters

213 record(s)
 
Type of resources
Available actions
Topics
Keywords
Contact for the resource
Provided by
Years
Formats
Representation types
Update frequencies
Scale
Resolution
From 1 - 10 / 213
  • This dataset contains data on geomorphological characteristics and flow-related variables along the Beas River (Punjab, India) between Pong dam and Harike barrage in January 2020. The variables provided include cross-sectional area, water depth, river channel width, river flow velocity and dry-season discharge measured at ten reference sites with stable banks and straight, linear channels without islands or other mid-channel structures. Full details about this dataset can be found at https://doi.org/10.5285/f899fbc5-7034-45c0-a15c-9ee1d92a693f

  • [This dataset is embargoed until August 1, 2023]. Measurements of sediment properties (including organic and carbonate content), radionuclides (210Pb, 137Cs, 241Am) and elements (including mercury, nickel, copper, zinc, and lead) in lake sediment successions. Radionuclide dating provides a reliable chronology of sediment ages from the mid-19th century (sometimes only 20th century) to the present (2016). The dataset comprises a standardised matrix of multiple measured sediment variables (element values per mass) against stratigraphic depth for 8 lakes. In some water bodies multiple core datasets exist. Full details about this dataset can be found at https://doi.org/10.5285/4b4a2388-fea2-48e8-8d61-4b93ada479bb

  • This dataset contains maximum water depth and maximum water velocity for 12 different Glacial Lake outburst floods (GLOFs) scenarios of the Tsho Rolpa Lake, Nepal. Also included is the water depth of dam breach flow and discharge of dam breach flow under each scenario. The GLOFs scenarios were created using a simple dam breach model. A high-performance hydrodynamic model was then used to simulate the resulting flood hydrodynamics. Full details about this dataset can be found at https://doi.org/10.5285/f4292d99-de93-4a28-a821-b2a6a826df4c

  • NB The data are stored in the European Nucleotide Archive (ENA) with accession numbers as follows: ENA accession number: ERP016063 - Name "Daisy Lake Shotgun" - Study PRJEB14421 ena-STUDY-UNIVERSITY OF CAMBRIDGE-15-06-2016-17:31:41:520-20 and can be accessed at https://www.ebi.ac.uk/ena/data/view/PRJEB14421 ENA accession number: ERP019980 - Name "Sudbury Lake mesocosms shotgun" - Study PRJEB18063 ena-STUDY-UNIVERSITY OF CAMBRIDGE-23-11-2016-12:04:04:617-1945 and can be accessed at https://www.ebi.ac.uk/ena/data/view/PRJEB18063 ENA accession number: ERP110084 - Name "Lake sediment mesocosm microbial communities" STUDY PRJEB27946 ena-STUDY-UNIVERSITY OF CAMBRIDGE-26-07-2018-16:21:00:749-1221 and can be accessed at https://www.ebi.ac.uk/ena/data/view/PRJEB27946

  • Data comprise water chemistry (analysis included phosphorus and nitrogen species, dissolved reactive silicon, suspended solids, chlorophyll, fluoride, chloride, and sulphate) in water samples taken at Lake Akrotiri, Cyprus, and its main inputs between July 2019 and November 2020. The eight monitoring sites included marginal samples from around the lake and also samples of the input canals that drained the surrounding marshes and a drainage pipe. Full details about this dataset can be found at https://doi.org/10.5285/0de897cd-3aa3-45a3-8bff-3bff62c01f30

  • 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 by the UK Centre for Ecology & Hydrology (UKCEH) at Derwent Water in Cumbria, England. 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. Ammonium (NH4N), nitrate (NO3N), 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. Measurements are made from a boat at a marked location (buoy) at the deepest part of the lake. When it was not possible to visit the buoy, samples were taken from the shore, thus water samples were not integrated on these occasions, marked as Flag 2. All data are from January 2014 until the end of 2018. Unfortunately, due to funding shortages, the long-term monitoring of Derwent Water ended early 2019. 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. Full details about this dataset can be found at https://doi.org/10.5285/7e7d722c-bdd7-4900-a443-e26370d72438

  • This dataset is part of Integrated Hydrological Units (IHU) of the UK, a set of geographical reference units for hydrological purposes including river flow measurement and hydrometric data collection. Hydrometric Areas are either integral river catchments having one or more outlets to the sea or tidal estuary, or they may include several contiguous river catchments having topographical similarity but separate tidal outlets. Hydrometric Areas are the coarsest units of the IHU in terms of spatial resolution. This dataset represents the same entities as the Hydrometric Areas with Coastline. The coastline of Hydrometric Areas without Coastline follows the boundaries of the CEH Integrated Hydrological Digital Terrain Model, from which IHU were derived, while the coastline used in Hydrometric Areas with Coastline was derived from Ordnance Survey data. The Hydrometric Areas without Coastline currently covers Great Britain only as no dataset with river geometries and names with suitable detail is available for Northern Ireland. Full details about this dataset can be found at https://doi.org/10.5285/3a4e94fc-4c68-47eb-a217-adee2a6b02b3

  • The dataset contains measurements of soil temperature and volumetric water content from plots in agricultural grasslands in the Hampshire Avon catchment (UK) from late-2013 to September 2015. Manipulations of soil temperature were made at three orthogonal experiments in three sub-catchments of contrasting geology (chalk, clay and greensand) between May and September 2015. Full details about this dataset can be found at https://doi.org/10.5285/6868abb7-db38-4362-92d5-f5d0140bdfc3

  • Data from two small streams, two rivers and rainfall fractions in the Western Amazonian basin at Tambopata National Reserve in Madre de Dios region, Peru. Data presented are nutrients (calcium, magnesium, potassium, sodium, total soluble phosphorus and silica) and fluvial carbon - dissolved inorganic carbon (DIC) and its isotopic composition δ13C-DIC, dissolved organic carbon (DOC) and particulate organic carbon (POC). Samples were collected during the period from February 2011 to May 2012 targeting both wet and dry seasons. Samples for DIC samples were collected using pre-acidified evacuated Exetainers. Established standard methods were used to take samples for DOC and nutrients. Established standard methods were used to analyse samples for DIC, DOC and nutrients These methods are outlined in the lineage. The samples were taken to understand the hydrological controls on the carbon concentrations and fluxes during different flow conditions. The data collection was carried out as part of the Natural Environment Research Council funded Amazonica project. Full details about this dataset can be found at https://doi.org/10.5285/ee1b9eb7-6fbd-4dd5-8f8f-e07d32c057e4

  • 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