The dataset describes the data needed for and results produced by the flood risk assessment framework under different development strategies of Luanhe river basin under a changing climate. The Luanhe river basin is located in the northeast of the North China Plain (115°30′ E-119°45′ E, 39°10′ N-42°40′ N) of China, is an essential socio-economic zone on its own in North-Eastern China, and also directly contributes to and influences the socio-economic development of the Beijing-Tianjin-Hebei region. The dataset here used for investigating the flood risk includes (1) uplifts of future climate scenarios to 2030 (2) the validation results of a historical event that happened in 2012; (3) the flood inundation prediction under different development strategies and climate scenarios to 2030; (4) and the spatial resident density map in Luanhe river basin to 2030. Wherein, the uplifts of the future climate change is generated based on the NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP) dataset and will be applied to the future design rainfall to represent the future climate scenarios; a 2012 event is select to validate the flood model, and the remote sensing data is adopted as real-world observation data; considering the uplifts and future land use data as input, the validated flood model is applied to produce flood inundation prediction under different development strategies and climate scenarios to 2030; and the inundation results are used to overlay the Gridded Population of the World, Version 4 (GPWv4) and then calculate the flood risk map of the local resident. These data are mainly open data or produced by authors. With all these data, the flood risk of the Luanhe river basin in the near future (2030) can be assessed. Full details about this dataset can be found at https://doi.org/10.5285/82055942-386a-4a8b-b2a1-0c3eea12b168

The dataset contains information on rates of hatching failure, threat status, and management interventions for 244 species of birds extracted from 233 previously published studies. Full details about this dataset can be found at https://doi.org/10.5285/8e157aa1-a81c-436d-bb5d-e7129d91487b

This dataset is a model output from the European Monitoring and Evaluation Programme (EMEP) model applied to the UK (EMEP4UK) driven by Weather and Research Forecast model meteorology (WRF). It provides UK estimates monthly averaged atmospheric deposition of oxidised sulphur, oxidised nitrogen, and reduced nitrogen at 3x3 km2 grid for the years 2002 to 2021. The data consists of atmospheric deposition values of oxidised sulphur, oxidised nitrogen, and reduced nitrogen. The EMEP4UK model version used here is rv4.36, and the WRF model version is the 4.2.2. This work was supported by the Natural Environment Research Council award number NE/R016429/1 as part of the UK-SCAPE programme delivering National Capability. Full details about this dataset can be found at https://doi.org/10.5285/904af4a0-d66d-460d-82eb-c8965e161b3e

[THIS DATASET HAS BEEN WITHDRAWN]. This dataset includes litterfall data from the experimental plots at the Climoor field site in the Clocaenog forest, NE Wales. Litterfall (natural senesced plant material) was collected in litterfall traps (12 x 7.5cm pots standing slightly proud of the soil/litter surface, emptied monthly). Litterfall was calculated by drying the contents of the traps and weighing the samples; values were calculated for each quadrat (total weight (g) only) and for each plot (total weight (g) and weight per metre squared (g/m2)). Data spans the periods Oct 1999 to Jan 2004 and July 2008 to June 2011. Full details about this dataset can be found at https://doi.org/10.5285/dd4dfc72-dafe-44a2-af2b-0118d949d7ad

The data consists of estimated hourly average inflow discharge (m3s-1) and water temperature (°C) of the inflow of the inner basin of Elterwater (lat: 54.428, long: -3.034) from January 2012 to December 2019. The work was supported by the Natural Environment Research Council (Grant NE/ L002604/1). Full details about this dataset can be found at https://doi.org/10.5285/2883aaf1-6148-49cb-904a-d271a028c716

This model code for object oriented data analysis of surface motion time series in peatland landscapes provides the procedure to assess peatland condition using object oriented data analysis. The model code assesses peatland condition according to which cluster each surface motion time series is assigned, based on key measures capturing differences between the time series. It can be run on any machine with R. Full details about this application can be found at https://doi.org/10.5285/dbdb9f19-c039-4a73-b590-e1acc7f79df4

[This dataset is embargoed until June 1, 2023]. This dataset contains details of sediment geochemistry, loss-on-ignition and sediment median particle size for two short reservoir cores collected from two reservoirs (Cowbury Dale and Higher Swineshaw), Stalybridge Tameside, Manchester. Cores were collected in 2018 following a severe moorland wildfire (July 2018) in the two reservoir catchments. Cores were collected from the deepest part of the reservoir using gravity coring and sampled at 2.5 mm intervals for analysis. The work was supported by the Natural Environment Research Council (Grant NE/S011560/1). Full details about this dataset can be found at https://doi.org/10.5285/4f447446-5461-48b2-b154-ff7094176502

The dataset contains parameter values that maximize revised Kling Gupta Efficiency (KGE’) between modelled and observed daily mean river flows when running one of 24 different hydrological models with one of 21 different climatic input datasets in one of 33 different catchments across the Citarum basin or 5 catchments across the Ciliwung basin, both in Java island, Indonesia. This dataset was created as part of a study on the advantages and disadvantages of using existing hydrological models, primarily developed for temperate and cold climates, in a tropical volcanic region. The hydrological models were based on those created for MARRMoT v1.2 (10.5194/gmd-12-2463-2019), recoded as sequential models in the R programming language. This work was supported by the Natural Environment Research Council (Grants NE/S00310X/1 and NE/S002790/1). Full details about this dataset can be found at https://doi.org/10.5285/f6cec7d4-edee-44b8-8f44-86d4f12ac72d

Dataset contains water chemistry data (pH, conductivity, dissolved carbon, dissolved gases, absorbance) from natural and artificial/restoration peat pools in Scottish peatlands. Water samples were collected seasonally from three sites, and more frequently (up to weekly) from one site, in within the Flow Country. Full details about this dataset can be found at https://doi.org/10.5285/17b51437-0231-4eac-a176-1277185ba2e9

This application is an implementation of the Ecological Risk due to Flow Alteration (ERFA) method in R language. This method assesses the potential impact of flow change on river ecosystems. Although the code was developed with a geographical focus on southeast Asia (example datasets are provided for the Mekong River Basin), it can be applied for any location where baseline and scenario monthly river flow time series are available. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. Full details about this application can be found at https://doi.org/10.5285/98ec8073-7ebd-44e5-aca4-ebcdefa9d044