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

The dataset contains model output from the CityCAT hydrodynamic model showing maximum water depths in Jakarta, Indonesia, during the January/February 2007 flood. The hourly rainfall and hourly lateral inflow boundary conditions from rivers used to obtain the flooding depths are also included. Full details about this dataset can be found at https://doi.org/10.5285/8e58f0bb-3ff1-41e8-b8f4-380983ec68bc

The dataset consists of long-term vegetation monitoring data from the Hard Hill burning plots sited in the Moor House - Upper Teesdale National Nature Reserve, Cumbria. An experiment to investigate the effects of rotational burning and grazing was initiated in 1954, consisting of a replicated block layout. Initial vegetation recording was carried out in 1961 and 1965 using a quadrat method and DOMIN scale. In 1972 onwards, vegetation was recorded using a pin frame. Data were recorded by staff from the Centre for Ecology & Hydrology and its predecessors. Full details about this dataset can be found at https://doi.org/10.5285/0b931b16-796e-4ce4-8c64-d112f09293f7

The WATCH Forcing data is a twentieth century meteorological forcing dataset for land surface and hydrological models. It consists of three/six-hourly states of the weather for global half-degree land grid points. It was generated as part of the EU FP 6 project "WATCH" (WATer and global CHange") which ran from 2007-2011. The data was generated in 2 tranches with slightly different methodology: 1901-1957 and 1958-2001, but generally the dataset can be considered as continuous. More details regarding the generation process can be found in the associated WATCH technical report and paper in J. Hydrometeorology. To understand how the data grid is formed it is necessary to read the attached WFD-land-long-lat-z files either in NetCDF or DAT formats. The data covers land points only and excludes the Antarctica. Qair or 2m specific humidity (instantaneous) is the instantaneous specific humidity at 2m measured in kg/kg at 6 hourly resolution and 0.5 x 0.5 degrees spatial resolution.

The WATCH forcing data (WFD) is a twentieth century meteorological forcing dataset for land surface and hydrological models. It consists of three/six-hourly states of the weather for global half-degree land grid points. It was generated as part of the EU FP 6 project "WATCH" (WATer and global CHange") which ran from 2007-2011. The data was generated in 2 tranches with slightly different methodology: 1901-1957 and 1958-2001, but generally the dataset can be considered as continuous. More details regarding the generation process can be found in the associated WATCH technical report and paper in J. Hydrometeorology. To understand how the data grid is formed it is necessary to read the attached WFD-land-long-lat-z files either in NetCDF or dat formats. The data covers land points only and excludes the Antarctica. Rainf or rainfall rate is the rainfall rate based on the Global Precipitation Climatology Centre (GPCC) bias corrected, undercatch corrected measured in kg/m2/s at 3 hourly resolution averaged over the next 3 hours and at 0.5 x 0.5 degrees spatial resolution. Please note that there is also a WFD Rainf CRU bias corrected dataset, but as the GPCC dataset is the preferred dataset only this rainfall dataset is available from the EIDC. These rainfall datasets contain rainfall data only and need to be combined with the respective WFD snowfall datasets to obtain precipitation data.

The WATCH Forcing data is a twentieth century meteorological forcing dataset for land surface and hydrological models. It consists of three/six-hourly states of the weather for global half-degree land grid points. It was generated as part of the EU FP 6 project "WATCH" (WATer and global CHange") which ran from 2007-2011. The data was generated in 2 tranches with slightly different methodology: 1901-1957 and 1958-2001, but generally the dataset can be considered as continuous. More details regarding the generation process can be found in the associated WATCH technical report and paper in J. Hydrometeorology. To understand how the data grid is formed it is necessary to read the attached WFD-land-long-lat-z files either in NetCDF or DAT formats. The data covers land points only and excludes the Antarctica. Tair or air temperature is the 2m air temperature (instantaneous) measured in K at 6 hourly resolution and 0.5 x 0.5 degrees spatial resolution.

This dataset includes polygons representing ecosystem types (ET) and their respective ecosystem services (ES) and disservices (EDS) in the Luanhe River Basin, with attributes recording 14 ecosystem types (ET), 11 provisioning services (PS), ten regulating services (RS), five cultural services (CS), 7 Ecological integrity indicators (EI), and 11 ecosystem disservices (EDS). Full details about this dataset can be found at https://doi.org/10.5285/2252d8a4-0ef3-403f-b2c3-3f7acbcac1d5

Data was collected to look at long-term trends in invertebrate ground predators. This dataset consists of count data (by gender) for all species of spider collected from three habitats (mire, dwarf-shrub heath, pine woodland) at the Cairngorms Environmental Change Network (ECN) site between 2004 and 2021. Spiders were collected in pitfall traps on a two-weekly basis between March and early November. Each habitat contained 10 pitfall traps, spaced 10 m apart. Samples were aggregated by habitat and collection date prior to analysis. The number of male and females of each species was recorded by the same expert araneologist for the duration (2004-2021). Full details about this dataset can be found at https://doi.org/10.5285/6077cd88-ad40-44bd-806a-fa3cebaa29d7

The data comprises river section, zone and test site delineation, winter Season average NDVI by section and zone 1989-2020, land cover maps seasonally 1989-2020, and derived land cover fractions by section and zone 1989-2020. The data was produced as part of a study to determine how changes in geomorphic form and dynamics due to human alteration to river flows and riparian land management relate to changes in vegetation communities in the Sutlej and Beas Rivers, India. Vegetated and other land cover, including water area, were quantified by winter season NDVI trends (in the plains of Punjab) and seasonal supervised classification of Landsat data for over a 30-year period. The work was supported by the Natural Environment Research Council (Grant NE/S01232X/1). Full details about this dataset can be found at https://doi.org/10.5285/9a96e199-34d0-46f9-9a64-140d300a2531

The data consists of identified exposed objects subject to flooding risk from the Tsho Rolpa Lake. The Tsho Rolpa Lake is the largest moraine-dammed proglacial lake in Nepal and was identified as one of the country’s most dangerous glacier lakes with a high possibility of outburst. Full details about this dataset can be found at https://doi.org/10.5285/3834d477-7a1d-4ad3-8a41-d38fc727dbd8