Simulated 15-min discharge time-series (1/10/2015-17/1/2016) for the River Kent at Sedgwick following a Natural Flood Management intervention of ‘Enhanced Hillslope Storage’ plus the baseline simulations are presented. To derive these data, the observed 15-minute discharge River Kent measured at the Environment Agency (EA) Sedgwick gauging station (https://nrfa.ceh.ac.uk/data/station/info/73005) through the 1 Oct 2015 to 17 Jan 2016 period were modelled using the latest version of Lancaster University’s Dynamic TOPMODEL (https://cran.r-project.org/web//packages/dynatop/index.html). The spatially distributed rainfall field used as input to TOPMODEL was derived from a new direction-dependent and topographically controlled interpolation using observed rainfall data for the Cumbrian Mountains (Page et al., 2022. Hydrological Processes 36: e14758, https://doi.org/10.1002/hyp.14758). Lack of perfect understanding of the hydrological processes routing rainfall for stream channels and then along stream channels to the Sedgwick gauge was represented by using a very wide range of model parameters applied randomly within 10,000 simulations. Using the approach detailed in Beven et al. (2022a. Hydrological Processes 36(10): e14703, https://doi.org/10.1002/hyp.14703), the resultant wide range of simulated discharge time-series was reduced by rejecting all but 67 simulations that passed the prescribed criteria. These 67 baseline simulations of observed behaviour through the +3 month period at Sedgwick are presented here. To represent the effect of adding surface storage distributed across this 209 sq km River Kent catchment, the Digital Elevation Model (DEM) used in the baseline simulations according to Hankin et al (2018. Technical report SC150005/R6. Environment Agency, Bristol. 77pp, https://www.gov.uk/flood-and-coastal-erosion-risk-management-research-reports/working-with-natural-processes-to-reduce-flood-risk) to represent bunds placed on hillslopes in rural areas. The bunds are a type of flood mitigation measure known as Natural Flood Management or NFM. These are known formally as ‘Enhanced Hillslope Storage’ or EHS features (Beven et al 2022b. Hydrological Processes 36: e14752, https://doi.org/10.1002/hyp.14752). The TOPMODEL parameter sets producing the 67 ‘acceptable’ baseline simulations were then re-run with the modified DEM. These results are also presented here. Full details about this dataset can be found at https://doi.org/10.5285/af081a90-b014-43f7-9399-c948a8b7672f

This dataset contains information about the background hydrochemistry and nutrient biogeochemistry of water samples collected from networks of interconnected rivers and lakes. Each water sample was analysed for the concentration of multiple fractions of nitrogen and phosphorus, and for the stable oxygen and nitrogen isotope composition of nitrate. Water samples were collected across the period 2017-2018 from multiple river-lake networks in the English Lake District and the Norfolk Broads. This research was supported by the Natural Environment Research Council (Grant NE/N006453/1: Hydroscape – Connectivity x Stressor Interactions) Full details about this dataset can be found at https://doi.org/10.5285/0d6de9b6-1f80-4f78-b65a-503db8ba63cf

This dataset provides the data produced as part of the work published in: Leeson, A. A., Foster, E., Rice, A., Gourmelen, N. and van Wessem, J. M.. 2019. 'Evolution of supraglacial lakes on the Larsen B ice shelf in the decades before it collapsed' Geophysical Research Letters. It includes 1) shapefiles of supraglacial lakes mapped in both optical (Landsat) and SAR (ERS) satellite imagery, 2) rasters of lake depth, derived from Landsat TM and ETM+ images acquired in 1988 and 2000 and 3) shapefiles of the study area considered in the paper. Funding was provided by ERPSRC grant EP/R01860X/1.

This dataset contains spatially and temporally resolved outputs describing supraglacial hydrology on the southwest Greenland Ice Sheet for the period 2015-2019. The data include gridded fields of surface meltwater routing, supraglacial lake extent and volume, lake drainage events (rapid and slow), and associated surface water fluxes at 100 m spatial resolution and daily temporal resolution. Outputs are derived from physically based simulations driven by climate model forcing, surface elevation data, and stress fields. The dataset has been evaluated against satellite-derived supraglacial lake observations and in situ proglacial discharge measurements, showing good agreement in lake distribution, seasonal evolution, and discharge magnitude. These data support analyses of surface meltwater storage and transfer across the ice surface and provide inputs for studies of ice-sheet hydrology and dynamics.

Persistent organic pollutant concentrations in artificial sea ice experiments at the Roland von Glasow Air-Sea-Ice Chamber (RvG-ASIC) at the University of East Anglia, UK. Experiments involved investigating chemical contaminant behaviours during sea ice formation and melt in order to assess possible exposure risk to sea ice biota. Funding was provided by: NERC ENVISION Doctoral Training Centre (NE/L002604/1). NERC and the German Federal Ministry of Education and Research (BMBF) funded Changing Arctic Ocean program EISPAC project (NE/R012857/1). British Antarctic Survey Collaboration Voucher. EUROCHAMP-2020 Infrastructure Activity under grant agreement (No 730997).

The data are dynamic response characteristics (DRCs) produced by modelling the rainfall-runoff behaviour of a series of micro-basins installed by the NERC Q-NFM project largely in Cumbria (UK) and ranging in scale from 0.0071 to 2.7329 sq. km. Specifically, the rainfall to discharge response of these basins has been modelled with the RIV algorithm of the CAPTAIN Toolbox (Taylor et al., 2007 doi.org/10.1016/j.envsoft.2006.03.002). The resultant modelled characteristics of the rainfall-discharge dynamics are presented on an event-by-event basis. Full details about this dataset can be found at https://doi.org/10.5285/ea641367-dc35-4695-97b8-63f7d6fa9105

Samples of snow, sea ice, seawater (0.5 m and 5 m depths) and meltponds were collected from two ice-covered stations located in the Barents Sea (81 N), during the "Nansen Legacy Q3" summer cruise of the Norwegian research vessel Kronprins Haakon on 26-28 August 2019. Perfluoroalkyl substances (PFAS) concentrations, salinity and stable oxygen isotopes were measured in all samples to determine sources and environmental fate of PFAS during late summer. NERC ENVISION Doctoral Training Centre (NE/L002604/1). NERC and the German Federal Ministry of Education and Research (BMBF) funded Changing Arctic Ocean program EISPAC project (NE/R012857/1). The Nansen Legacy research is funded by the Research Council of Norway (# 276730).

This dataset comprises of derived annual statistics for measures of rainfall, streamflow, temperature and stream acidity (pH) for a stream, draining a small, approximately 1.2 square kilometres, upland conifer catchment. The stream, Nant Trawsnant, drains into the Llyn Brianne reservoir, Powys, United Kingdom. The data are for a 31 year period covering 1st April 1982 to 1st April 2012. The streamflow and acidity data are derived from 15 minute resolution observations throughout the calendar year 2013 from associated stream gauging and water quality stations on the Nant Trawsnant. The monthly rainfall measures presented, were derived from local rain gauges. The monthly temperature measures presented were derived from observations at a weather station near Talgarth, Powys. Routines within the Lancaster University Computer-Aided Program for Time-series Analysis and Identification of Noisy Systems (CAPTAIN) Toolbox for Matlab were used to develop a dynamic model of these data. These models were then used to simulate the 31-year record for which monthly statistics were derived. The statistics were derived to develop greater understanding of the controls on the long-term dynamics of aquatic biodiversity observed by other researchers in this stream. The work was part of the Diversity in Upland River Ecosystem Service Sustainability (DURESS) project, NERC grant NE/J014826/1. Members of staff from the Lancaster Environment Centre, Lancaster University installed, maintained and downloaded the stream gauging and water quality stations and also carried out statistical analysis of the data. Full details about this dataset can be found at https://doi.org/10.5285/b085a784-0e16-4174-b208-465a8f43c8c8

This dataset comprises of derived annual statistics for measures of rainfall, streamflow, temperature and stream acidity (pH) for a stream, draining a small, approximately 0.6 square kilometres, upland grassland catchment. The stream, Nant Esgair Garn, drains into the Llyn Brianne reservoir, Powys, United Kingdom. The data are for a 31 year period covering 1st April 1982 to 1st April 2012. The streamflow and acidity data are derived from 15 minute resolution observations throughout the calendar year 2013 from associated stream gauging and water quality stations on the Nant Esgair Garn. The monthly rainfall measures presented, were derived from local rain gauges. The monthly temperature measures presented were derived from observations at a weather station near Talgarth, Powys. Routines within the Lancaster University Computer-Aided Program for Time-series Analysis and Identification of Noisy Systems (CAPTAIN) Toolbox for Matlab were used to develop a dynamic model of these data. These models were then used to simulate the 31-year record for which monthly statistics were derived. The statistics were derived to develop greater understanding of the controls on the long-term dynamics of aquatic biodiversity observed by other researchers in this stream. The work was part of the Diversity in Upland River Ecosystem Service Sustainability (DURESS) project, NERC grant NE/J014826/1. Members of staff from the Lancaster Environment Centre, Lancaster University installed, maintained and downloaded the stream gauging and water quality stations and also carried out statistical analysis of the data. Full details about this dataset can be found at https://doi.org/10.5285/00185590-537e-40e4-969c-039f44b4dad9

The dataset contains the chemical compositional changes occurred in anaerobic digestate, with and without biomass ash, simulating storage conditions during 128 days. Additionally, Sulphuric Acid (H2SO4) was added to these materials to test the effectivity on preventing nitrogen loss via acidification. Experiments were carried out in the laboratory during 2016, being measured via a combination of internal and external laboratories. The dataset provides data on chemical changes, namely: dry solids, pH, Kjeldahl nitrogen and total sulphur. Full details about this nonGeographicDataset can be found at https://doi.org/10.5285/e91e8c28-0176-4c5b-9b20-611eb505ab39