This dataset comprises field sensor physicochemical and optical/fluorescence measurements, as well as laboratory microbiological and chemical analysis, for urban surface water samples. Samples were collected at different locations throughout the urban area of Kolkata, with the latitude and longitude of all sample location provided within the spreadsheets. Samples/data were collected across three separate field surveys undertaken in June 2018 (file 1), March 2019 (file 2) and December 2019 (file 3). This dataset forms a case study of the water quality of three different types of urban surface freshwaters within the city of Kolkata, India. This case study was created to deploy a prototype multichannel fluorimeter and assess its ability to identify waters with a high bacterial load and biological contamination events through the use of Peak T fluorescence. Full details about this dataset can be found at https://doi.org/10.5285/9bc3dce7-7c2b-49dd-9b76-819267d7a352

The dataset includes six files of UK physical river characteristics including five files of gridded data at 1km × 1km resolution and one comma separated table. The data includes: • Drainage directions (D8 flow method), ESRI coding • Drainage directions (D8 flow method), unifhy (python hydrology framework) coding • Catchment areas (km2) • Widths of bankfull rivers (m) • Depths of bankfull rivers (m) • NRFA gauging station locations (easting (m), northing (m)) Two versions of drainage directions are provided, both have the same drainage directions but different numbering systems. The comma separated NRFA (National River Flow Archive) gauging station locations table provides the best locations of 1499 river flow gauging stations on the 1km grids, together with the approximate error in the 1km × 1km gridded delineation of the upstream catchment area. All datasets are provided on the British National Grid. Full details about this dataset can be found at https://doi.org/10.5285/8df65124-68e9-4c68-8659-1c6b82c735e9

This dataset contains river (fluvial) and surface water (pluvial) flooding maps for the central highlands of Vietnam and surrounding provinces. Flood depth is estimated at 30m horizontal grid spacing for 10 return periods, ranging from the 1 in 5 year to the 1 in 1000 year return period flood. These maps are of relevance to planners and policy makers to estimate which areas of most at risk of flooding and can contribute towards policy such as the sustainable development goals. Full details about this dataset can be found at https://doi.org/10.5285/74e4e6ec-a119-4dc7-8ada-9513252b1b60

This dataset contains modelled outputs of the European river network modelled as 33,668 cells (5° longitude by 5° latitude). For each cell, modelled monthly flows were generated for an ensemble of tenscenarios for the 2050s and for the study baseline (naturalized flows for 1961 to 1990). Score classes are categorisation of flow alteration scenarios. Full details about this dataset can be found at https://doi.org/10.5285/d8ef71eb-3d22-4f98-af15-9d8e046ccb63

[This dataset is embargoed until January 2, 2024]. The data set contains grain size distributions, organic matter (OM) content and trace metal distribution (including Fe, Zn, Cu, Cr and Pb) of 37 shallow cores of sediments sampled from dams across the Limpopo River Basin. The dams include: Gaborone, Lotsane and Shashe dams in Botswana; Houtrivier, Nwanedi and Mutshedzi dams in South Africa; Ripple Creek and Zhovhe dams in Zimbabwe; and Massingir Dam in Mozambique. Data from 2 cores sampled from an oxbow lake in Mozambique are also included. The cores were collected with a gravity corer using PVC pipes of 5 cm diameter by a team from Botswana International University of Science and Technology (BIUST) led by Dr. Franchi between July 2018 and April 2021. Full details about this dataset can be found at https://doi.org/10.5285/b8db8239-3bde-454a-aa75-d1cec24c8763

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

[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

Distribution of soil parent materials in the Severn and Wye catchments. These were mapped during the Soil Hydrology Study conducted by JP Bell in 1968-1969: Bell, J.P. (1969). The Soil Hydrology of the Plynlimon Catchments. Institute of Hydrology Report No. 8, Institute of Hydrology, Wallingford, UK.

This dataset contains GR6J (which stands for modèle du Génie Rural à 6 paramètres Journalier) modelled daily river flow time series for 95 river catchments in Great Britain and driving data (precipitation and potential evapotranspiration calculated from temperature) from the EC-Earth Single Model Initial Condition Large Ensemble (SMILE) climate model. The large ensemble is based on the EC-Earth Global Climate Model (GCM) v2.3 and is run for present day (equivalent to present day climate with observed global mean surface temperature for the period 2011-2015) and pre-industrial plus 2°C and 3°C global warming conditions. In total, they make up 2000 years of data for each global warming level (i.e. 16 ensemble members x 25 realizations x 5 years = 2000 years). All ensemble members are pooled to form a continuous 2000-year time series of meteorological input and daily modelled river flows. Full details about this dataset can be found at https://doi.org/10.5285/d966ae7f-a29b-4c57-835d-f4efd0d65c88

Fieldwork was undertaken at the epishelf lake, Blaso, in Northeast Greenland between 19th July and 11th August 2017. CTD casts were made between 27/7/17 and 10/8/17. The CTD operated continuously and was deployed using a hand-spooled winch from a small boat at eight sites across the lake, with the objective of characterising water conditions at both calving fronts and in the three lake basins identified by the CHIRP survey. The CTDs were sampled between 31st July and 10th August 2017 and during this period there was persistent lake ice which prevented CTD measurements close to the eastern calving front. In contrast, most of the lake ice in the western basin had dispersed and melted by early August, allowing access to the western calving margin. Depth temperature and salinity observations are reported as metres (m), degrees centigrade (Deg C) and Practical Salinity Units (PSU). This project was funded by NERC Standard Grant NE/N011228/1