Data comprise reservoir inflows and release data (including spills), evaporation loss and optimised monthly rule curve ordinates (upper, lower and critical) for Pong and Bhakra reservoirs in Northern India. Also included in the rule curve data are associated reservoir rationing ratios that can be applied to gross demand when rationing is also indicated. Data contain monthly Inflows, net-evaporation loss and release (all in million cubic metres, i.e. x 10^6 m^3) as simulated by WEAP for the Pong and Bhakra reservoir for the baseline (1989 - 2008); mid-century (2032-2050) and end-century (2082-2100) periods. The future inflows were based on forcing the WEAP model of the basin with climate projections of the GFDL-CM3 CMIP model The data were collected by Heriot-Watt University under the Sustaining Himalayan Water Resources in a Changing Climate (SusHi-Wat) project funded by NERC. Full details about this dataset can be found at https://doi.org/10.5285/46135938-cc6c-44a0-b35b-f6e5f5dd1221

This dataset contains a timeseries of pressure (dbar), sea pressure (dbar), and depth (m), within the inner regions of four UK estuaries: Conwy, Dyfi, Milford Haven and Kent. Data was collected between 2020 and 2023. The temporal resolution is either 1s or 10 s. Specific information on the data locations, deployment methods, units and reference levels, data structure, and quality control can be found in the accompanying supporting documentation (read_me.docx). Full details about this dataset can be found at https://doi.org/10.5285/84600f32-b4e8-4f29-851a-5ed0cd8ec9a4

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

This dataset reports the responses of annual river flow to forestation in 43 catchments and contains 770 data points. Data shows the change in river flow following forestation at annual time scales, along control river flow measurements and associated metadata from primary and secondary sources. Data collection, processing and interpretation were performed by Laura Bentley and David A. Coomes between January 2018 and October 2019. Forestation was defined as a change in land cover from a stable, non-forested state to a forested one, independent of the long-term history of forest cover. Paired measurements of annual river flow following forestation (mm) and river flow under control land cover conditions (mm) are provided for each year that the catchment dataset satisfied our inclusion criteria. River flow response is provided as both an absolute difference (mm) and as a percentage of control flow in the same year. Estimates of catchment annual precipitation, annual potential evapotranspiration, forest age, forest area, and the year of study are provided for each river flow response data point. Metadata are provided concerning catchment land cover history, land use history, catchment area, forest type, average climate and the method of forest establishment. The dataset contains catchments that were planted with trees and catchments in which forest cover regenerated without planting. Historical forest cover was reported in some catchments, and not reported in others. The 43 catchments a distributed unevenly across the globe, in 13 countries. The length of time series for each catchment varies from 2 years to 57 years, with and average duration of 19 years. Full details about this dataset can be found at https://doi.org/10.5285/5baa5d91-d552-4fc6-8a8c-29ae45192d77

This is a long-term monitoring dataset of surface temperature, surface oxygen, water clarity, water chemistry and phytoplankton chlorophyll a from weekly or fortnightly sampling at the South Basin of Windermere in Cumbria, England that began in 1945 for some variables. The data were initially collected by the Freshwater Biological Association but have been collected by the Centre for Ecology & Hydrology (CEH) and its predecessor Institute of Freshwater Ecology (IFE) since 1989. 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. Water samples are based on a sample integrated from 0 to 5 m (1945-1962), 0 to 10m (1962-1964) and 0 to 7m (1964 onwards). Measurements are made from a boat at a marked location (buoy) at the deepest part of the lake. All data are from March 1945 until the end of 2013. Full details about this dataset can be found at https://doi.org/10.5285/e3c4d368-215d-49b2-8e12-74c99c4c3a9d

Data were generated to investigate the influence of bed roughness on the dynamics of large sand-bed rivers like the South Saskatchewan, Canada. The influence of roughness was investigated by using a numerical model to simulate the evolution of the river bed for a hypothetical sand-bed river modelled on the South Saskatchewan. The model generated information on the evolving river bed topography, water depth, flow velocities and sediment transport rates, over a period of 28 years as part of NERC project NE/L00738X/1 Full details about this dataset can be found at https://doi.org/10.5285/790e507c-ce99-47ca-99b4-c97a684ee8c6

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

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

Datasets consists of the results of Computational Fluid Dynamics (CFD) flow simulations for a section of the South Saskatchewan River, Canada. The aim of these CFD simulations was to investigate the effect of dunes on the depth-averaged and near-bed flow fields. Modelling was carried out using the open source CFD package OpenFOAM to solve the three-dimensional Navier-Stokes equations. The dataset consists of two files, one with simulation results for a river bed characterised by alluvial bedforms (dunes) and one for a smooth river bed without dunes. This work was part of NERC project NE/L00738X/1. Digital Surface Models (DSMs) were constructed using imagery obtained on four occasions (13th May 2015; 2nd Sept 2016; 8th June 2017; and 12th June 2017). Full details about this dataset can be found at https://doi.org/10.5285/7db04405-2f5e-4543-aa94-948ddbcd588a

The data consist of stable water isotope composition in the rivers , lakes, soils and flooded areas in the Western Siberia Lowlands (WSL). Sampling area encompassed a 1700 km south-north transect spanning from approx. 56°N to 68°N in latitude and 74°E to 84°E in longitude. Samples were collected during multiple field campaigns between February 2014 and November 2016. The dataset in produced as a part of the JPI/NERC funded SIWA project "Climate impact on the carbon emission and export from Siberian inland waters". The dataset has resulted in two publications submitted to peer-review: (i) Ala-aho et al. (2018). Using stable isotopes to assess surface water source dynamics and hydrological connectivity in a high-latitude wetland and permafrost influenced landscape. Journal of Hydrology, 556, 279-293. (ii) Ala-aho et al. (2018). Permafrost and lakes control river isotope composition across a boreal Arctic transect in the Western Siberian lowlands. Environmental Research Letters, 13(3), 34028. Full details about this dataset can be found at https://doi.org/10.5285/ca17e364-638d-4949-befb-b18b3770aec6