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

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

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 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 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 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

Data were collected in 2015, 2016 and 2017 to provide high resolution imagery for two sections of the South Saskatchewan River, Canada. Photographs were acquired using conventional aerial plane images with a 0.06m ground resolution, captured at a height of approximately 1500m from a fixed-wing aeroplane with an UltraCamXp sensor. Imagery was obtained on four occasions (13th May 2015; 2nd Sept 2016; 8th June 2017; and 12th June 2017). The dataset consists of eight orthomosaics; one for each of the two river sections on each of the four dates. Images were collected as part of NERC project NE/L00738X/1. Full details about this dataset can be found at https://doi.org/10.5285/7473d4f9-c9a7-40ad-9f58-e58e25997fc5

Data were collected in 2015, 2016 and 2017 to provide information on the distribution of flow depth and depth-averaged flow velocity at cross-sections on the South Saskatchewan River, Canada. Data were obtained using a Sontek M9 acoustic Doppler current profiler (aDcp) mounted onto either a small zodiac boat or a SonTek Hydroboard. Data for each cross-section is recorded in a single file. Individual points within each file represent single locations on the particular cross-section. Data were collected as part of NERC project NE/L00738X/1. Full details about this dataset can be found at https://doi.org/10.5285/e4fe2ebe-b207-47d5-8c77-9873afc63da9

This dataset contains fluvial flood maps of the present day 1 in 20 year return period, and corresponding flood extents for 3 SSP (Shared Socioeconomic Pathway)/RCP(Representative Concentration Pathway) scenarios for the future (2070-2100). Change in flood return periods are estimated using CMIP6 projections and subsequently used to extract flood maps from a global flood model. Full details about this dataset can be found at https://doi.org/10.5285/0d5d69ae-7f50-40ee-a0c9-2522de138f27

The shapefiles contain the classification and locations of each river style determined by the authors. The data were used to characterise the river styles in Bislak River, Philippines. Shapefiles were clipped to the catchment boundary from different national government agencies to produce different thematic maps. Catchment properties such as land use (from the National Mapping and Resource Information Authority (NAMRIA)), geology (from the Mines and Geosciences Bureau), fault (from Philippine Institute of Volcanology and Seismology, rainfall isohyets, slope map, and the digital elevation model (also from NAMRIA) were used for regional and catchment analysis. The data only covers the whole Bislak catchment, Philippines. The CSV contains data used for the stream power analysis where stream power is a factor of slope and discharge. Full details about this dataset can be found at https://doi.org/10.5285/31ae71aa-74a9-466b-9a3a-25d2b1a9406e