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

Automated measurements of water level and temperature at half-hourly intervals spanning parts of 2018, 2019 and 2020, from seven wetland sites in the Pastaza-Marañón Basin, Amazonian Peru. Full details about this dataset can be found at https://doi.org/10.5285/0d1d15da-e356-492d-88db-2dba3b9ec9b4

These data are input files for CAESAR-Lisflood (CL), a numerical hydrodynamic-landscape evolution model. These files were created to support coupled hydrodynamic-landscape evolution modelling to evaluate the geomorphological response of river channels affected by the 7th February 2021 ice-rock avalanche and debris flow in Chamoli District, Uttarakhand, India. They include 10 m digital elevation models (DEMs) of bed rock and land surface topography in a gridded (raster) format. They also include reanalysis-derived river discharge data generated by the GEOGloWS project at the following locations: Rontigad, Rishiganga, Dhauliganga, and Alaknanda. The configuration settings and parameters for CL modelling are also included. Full details about this dataset can be found at https://doi.org/10.5285/4cdd86b3-bf58-457d-b8cf-b57aed2d56d0

This is a set of six ASCII grids describing the peak flood event for six return periods (2-100 years) at each point of the river network in the state of Kerala, India. Estimates were derived in a similar way to the Flood Estimation Handbook* approach. The data is measured in cubic metres per second, and is given on an unprojected resolution of 15 arc-seconds per grid cell. This work was supported by the Natural Environment Research Council as part of the LAWIS programme delivering National Capability. * (Flood Estimation Handbook. Centre for Ecology & Hydrology, 1999, ISBN: 9781906698003) Full details about this dataset can be found at https://doi.org/10.5285/cba9f9db-4706-4f1e-aaf4-fd7769e00db0

This dataset comprises multiple baseline and future ensembles of hydrological model estimates of monthly mean and annual maximum river flows (m3s-1) on a 0. 0.008333° × 0. 0.008333° grid (approximate grid of 1 km × 1 km) across Peninsular Malaysia. Specifically, these are provided for historical (1971 to 2005) and projected future (2006 to 2099) periods, for 3 Representative Concentration Pathways (RCPs). This dataset is the output from the Hydrological Modelling Framework for Malaysia, or “HMF-Malaysia” model. The projected future hydrology simulations are provided for CORDEX-SEA (Coordinated Regional Downscaling Experiment – South East Asia) three RCPs (RCP2.6, RCP4.5 and RCP8.5) assuming (i) current artificial influences (CAI) such as water transfers and diversions and (ii) planned future artificial influences (FAI). This dataset is an output from the hydrological modelling study from the Malaysia - Flood Impacts Across Scales (FIAS) project. Full details about this dataset can be found at https://doi.org/10.5285/9b70bebe-189c-4ae8-9aee-1bb1db7b1ad5

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

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

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

[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