This dataset contains the dates and magnitudes of extreme river discharge and associated skew surge peaks for UK estuaries between 1984 and 2013. The lag time between the drivers is also provided. Thirty years of river discharge and sea level data for 126 estuaries around the UK were analysed. The river discharge and tide gauge data were used at a 15-minute temporal resolution. A peaks over threshold analysis was completed to identify peaks in the river discharge record which exceeded the 95th percentile. The largest skew surge associated with each extreme discharge event was identified, and saved if this value also exceeded the 95th percentile. Full details about this dataset can be found at https://doi.org/10.5285/d895fadb-d762-441a-9f3f-1ebe1cbabfa7

The Digital Elevation Model (DEM) domain includes the tidally influenced Conwy estuary, downstream of the Cwmlanerch river gauge on the River Conwy and extending offshore into Conwy Bay and the Menai Strait at the coastal boundary. A number of sources were combined to generate the land elevation data, including (a) seabed bathymetry, (b) land elevations and (c) location and heights of existing flood defences. The domain topography was based on the marine DEM, Lidar Digital Terrain Model (DTM) and Ordnance Survey Terrain 5m DTM. The Lidar DTM data was used to check and, where necessary, augment the flood defences vector database. Full details about this dataset can be found at https://doi.org/10.5285/7217e6c0-46c7-4f87-bc36-589f884d3b02

A colour LiDAR (Light Detection And Ranging) dataset was obtained at the cliffs at Happisburgh, Norfolk, UK, over a period of 9 months (April 6, 2019 to December 23, 2019). The scans were taken daily for 90% of the study period using a FARO S350 TLS (Terrestrial LiDAR Scanner). Scans were carried out from two locations consecutively, positioned at around 40 m from the cliffs. The full scans are also split into smaller subsets: "slices", 1 m wide bands oriented perpendicular to the shoreline, and "grids", smaller areas of the beach, to assist analysis. The numerical model SWAN (Simulated Waves Nearshore) (v41.31a), run in non-stationary mode, was used to simulate hourly sea states at the study site to aid in the context of environmental conditions. Wind parameters from the ERA5 reanalysis and bathymetry from the OceanWise 1 arc second digital elevation model (DEM) were used to force the SWAN model, and obtained wave parameters in 4x6 km rectangular grid around the scanning site, with a 10m interval, and a 26x26 km square grid encompassing the smaller grid, with a 100 m interval. The LiDAR scans were also projected into both colour and intensity images, viewing the shoreline from above. This research was funded by the UK Natural Environment Research Council (NE/M004996/1; BLUE-coast project). The on-location LiDAR Scanning and Technical R&D operated by ScanLAB Projects Ltd was funded by Innovate UK's Audience of the Future Program (Multiscale 3D Scanning with Framerate for TV and Immersive Applications project). The first 6 months of LiDAR scans (April to September 2019) were funded by Innovate UK, and this project was continued by the NERC BLUE-coast funding for the last 3 months (October to December 2019).

The dataset comprises of physical and biogeochemical measurements of saltmarsh soils from across 19 UK saltmarshes. The data provides a quantitative measure of soil dry bulk density, organic carbon content, nitrogen content, CN ratio, N/C ratio, δ13Corg and δ15N across varies substrate and marsh types. Between 2018 and 2021, 33 wide diameter gouge cores (60 mm in diameter) were collected as part of the Carbon Storage in Intertidal Environments (C-SIDE) project to facilitate the calculation of organic carbon burial rates in saltmarsh soils. Sites were chosen to represent contrasting habitats types in the UK, in particular sediment types, vegetation and sea level history. The work was carried out under the NERC programme - Carbon Storage in Intertidal Environment (C-SIDE), NERC grant reference NE/R010846/1. Full details about this dataset can be found at https://doi.org/10.5285/279558cd-20fb-4f19-8077-4400817a4482