Keyword

Inland waters

271 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 / 271
  • 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

  • Data were collected in 2015 and 2016 to provide information about spatial variations in water depth and river bed morphology (including bedform height) on the South Saskatchewan River, Canada. Water depth measurements were obtained with a Navisound NS 215 system and a Reson TC 2024 200kHz high-resolution dual frequency single beam echo sounder (SBES) operating at a sampling frequency of 10hz. Data were geolocated via a Leica 1230 Real-Time Kinematic (RTK) dGPS system. Data were collected in 2015 (between 7th and 9th September) and 2016 (between 2nd and 14th September) as part of NERC project NE/L00738X/1. Full details about this dataset can be found at https://doi.org/10.5285/14c80b71-6eb6-4dba-a298-b95a37059f55

  • Data were collected in 2017, to provide information on spatial patterns of dune migration rates and associated water flow characteristics, at locations on the South Saskatchewan River, Canada. Dune migration rates were measured using repeat aerial imagery. Bedform crests were digitised in individual images, and average dune migration rates were calculated from the mean migration distance between image pairs, divided by the time between image collection. Water depth and velocity data were collected using a Sontek M9 acoustic Doppler current profiler (aDcp) mounted on a small zodiac boat. The position of the aDcp was recorded using a RTK dGPS system. Data were collected on 12th June 2017 as part of NERC project NE/L00738X/1 Full details about this dataset can be found at https://doi.org/10.5285/864434b7-2102-4edc-802d-ebdbfe9ff766

  • 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 December 1, 2024]. This dataset contains information about the stable oxygen and hydrogen isotope composition (δ18O, δ2H and d-excess) of waters within the Five Lakes of Mikata catchment. Datapoints span March 2011 – January 2012 and July 2020 – July 2022. Samples include precipitation on an event-basis, weekly river water and weekly lake water. To accompany the precipitation isotope composition data, total precipitation and average temperature during each subsampling period is provided. Water temperature and salinity variations with depth within Lake Suigetsu on six dates across the 2020 – 2022 sampling interval are also given. This data was collected to determine if catchment water composition reflects East Asian Monsoon variability. This work was supported by an Australian Research Council Discovery Project (DP200101768), a JSPS KAKENHI Grant (19K20442) and the NERC IAPETUS2 Doctoral Training Partnership. Full details about this dataset can be found at https://doi.org/10.5285/6c8b8134-a877-41ee-aede-f480c7aaa80d

  • Aquatic carbon (dissolved inorganic carbon (DIC), dissolved organic carbon (DOC) and particulate organic carbon and the carbon isotopic composition of DIC) and nutrients (calcium, magnesium, potassium, sodium, total soluble phosphorus and silica) in rainfall fractions (rainwater, throughfall, stemflow and overland flow) were sampled in the Western Amazonian basin. The samples were collected towards the end of a wet season April - May 2012. Rainfall and throughfall samples were collected in plastic buckets. Stemflow samples were collected using stemflow collection systems. Overland samples were collected using a a plastic pipe cut lengthways directing flow into a plastic bucket. Established standard methods were used to analyse the DIC, DOC and nutrients. These methods are outlined in the lineage. The samples were taken to understand the nutrient and carbon delivery in rainwater as well as leaching from tree canopies, stems and from the soil surface. The data collection was carried out as part of the Natural Environment Research Council (NERC) funded Amazonica project (NE/F005482/1). Full details about this dataset can be found at https://doi.org/10.5285/59bdb8f6-fb1f-418f-a53c-394f6c68a334

  • Data comprise modelled flood extents for the Kampala district produced by simulating rainfall events over a 5m Digital Elevation Model (DEM) using a 2D finite-volume hydrodynamic model. The DEM was obtained from Makerere University and rainfall events were sampled across a range of depths and durations (for 20, 40, 60, 80 and 100 mm of rainfall over 1, 3 and 6 hours using flood depth thresholds of 0.1, 0.2 and 0.3 mm). The effects of infiltration were included within green areas based on spatial data obtained from Makerere University. Maximum depths were converted into extents using various thresholds. Full details about this dataset can be found at https://doi.org/10.5285/e53dea2e-cb25-4f0f-b5f9-937eecf15aff

  • This dataset contains water flow velocity, discharge, and suspended sediment compositions of the Irrawaddy (Ayeyarwady) River at Pyay, Myanmar and the Salween (Thanlwin) River at Hpa-An, Myanmar. The suspended sediment samples and the hydrological data were collected both during peak monsoon conditions (August 2017 and August 2018) and peak dry season conditions (February 2018 and May 2019). Water velocity was measured using Acoustic Doppler Current Profiler (ADCP) while collecting suspended sediment samples at various depths in the river. Additional flow velocity data was collected while laterally crossing the river channel from bank to bank, and was used to calculate total river discharge at these sites. The dataset includes suspended sediment concentrations, particulate organic carbon concentrations, and particle size distributions of sediment samples collected at various depths and locations in the two river channels. Full details about this dataset can be found at https://doi.org/10.5285/86f17d61-141f-4500-9aa5-26a82aef0b33

  • The data resource contains daily time-series of simulated streamflow, ground water levels and estimated demands, from humans, livestock and irrigation across the Narmada Basin, India. The data were generated using the Global Water Availability Assessment (GWAVA) Model 5. For the Upper Narmada, a baseline of 1970-2013 is presented along with a future time slice of 2028- 2060. For the whole Narmada, a baseline of 1981-2013 and future period of 2021-2099 is included. The data were produced to help predict how climate and land use change in the region would impact on future water security. The research was funded by NERC research grant NE/R000131/1 Full details about this dataset can be found at https://doi.org/10.5285/9fc7ab01-c622-46f1-a904-0bcd54073da3

  • 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