The Annual Characteristics and Long-Term Statistics offer basic hydrological statistics of timeseries data of the gauging stations being represented in the Global Runoff Database. Annual characteristics are derived from monthly discharge data, either through aggregated daily data or originally provided monthly data. Long-term statistics and long-term variability are derived from annual characteristics too.
Large-sample datasets are essential in hydrological science to support modelling studies and global assessments. This dataset is an extension to Caravan, a global community dataset of meteorological forcing data, catchment attributes, and discharge data for catchments around the world (Kratzert et al. 20231). The extension includes a subset of those hydrological discharge data and station-based watersheds from the Global Runoff Data Centre (GRDC), which are covered by an open data policy (Attribution 4.0 International; CC BY 4.0). In total, the dataset covers stations from 5357 catchments and 25 countries worldwide with a time series record from 1950 – 2022. GRDC is an international data centre operating under the auspices of the World Meteorological Organization (WMO) at the German Federal Institute of Hydrology (BfG). Established in 1988, it holds the most substantive collection of quality assured river discharge data worldwide. Primary providers of river discharge data and associated metadata are the National Hydrological and Hydro-Meteorological Services of WMO Member States. 1Kratzert, F., Nearing, G., Addor, N. et al. Caravan - A global community dataset for large-sample hydrology. Sci Data 10, 61 (2023). https://doi.org/10.1038/s41597-023-01975-w
The Arctic-HYCOS forms the Arctic region component of the the World Hydrological Cycle Observing System (WHYCOS) implemented to support existing international initiatives. The objective of the Arctic-HYCOS Project is to allow the collection and sharing of hydrological data to evaulate freshwater fluxes to the Arctic Ocean and Seas, monitor the changes and enhance understanding of the hydrological regime of the Arctic region. GRDC hosts this dataset on behalf of the Arctic-HYCOS member countries.
The Southern Africa Flow Database, established between 1992 and 1997 to support rainfall-runoff modelling, contains flow time series data from about 815 stations across Southern Africa (SA). Initially hosted at the University of Dar es Salaam during the SA FRIEND Phase I and maintained by CEH in Wallingford in Phase II, the SA Flow Database is operated by GRDC since November 2010.
The European Water Archive (EWA) collected long-term daily flow data and catchment information from more than 4000 river gauging stations in 30 countries. In October 2014 the EURO-FRIEND-Water meeting in Montpellier concluded that the EWA will no longer be updated and will be "frozen at its current state". By release and on behalf of the data providers, the former EWA stations and flow data will be integrated in the Global Runoff Database. The archived data remain unchanged and will be provided by GRDC on special request by writing to grdc@bafg.de. Please use the GRDC station catalogue on the GRDC Portal for up-to-date data of stations in Europe.
The Global Terrestrial Network for River Discharge (GTN-R) is the river discharge component of the Global Terrestrial Network - Hydrology (GTN-H) to support the Global Climate Observing System (GCOS) and the Hydrology and Water Resources Programme of the WMO (HWRP). The basic idea of the GTN-R project is to draw together the already available discharge data provided by the National Hydrological Services (NHS) and to redistribute it in a standardised way. Core component is the GCOS Baseline River Network of gauging stations located near the mouth of the world's major rivers. In cooperation with the Hydrological Services of the WMO Member States this network is continually being extended by confirmation of additional stations.GRDC contributes to the GTN-H by collection of discharge data. Access to GTN-R data follows GRDC's data policy of free and unrestricted but identified access and is limited to noncommercial applications. Use the GCOS/GTN-R stations catalogue to create your individual list of project stations for download via GRDC Data Portal.
Objective weather types of Deutscher Wetterdienst derived from different Reanalysis and Global Climate Model simulations for the control run (1951-2000) and the projection period (2000-2100). On the one hand, the dataset is useful for evaluation of representative circulation statistics in Central Europe, on the other hand, for the analysis of future weather types due to climate change. Added temperature and precipitation data allow to study the weather type effectiveness for these important climate parameters.
BALTEX (the Baltic Sea Experiment) was launched in 1992 as a Continental-scale Experiment (CSE) of the Global Energy and Water Exchanges Project (GEWEX) within the World Climate Research Program (WCRP). The research focus of BALTEX was primarily on the hydrological cycle and the exchange of energy between the atmosphere and the surface of the Earth. The study region of BALTEX is the Baltic Sea and its huge catchment region. In 2015, the BALTEX Hydrological Dataset moved from Swedish Meteorological and Hydrological Institute (SMHI) to the GRDC in order to ensure sustainable operation and regular updates as an integral part of the Global Runoff Database. By release and on behalf of the National Hydrological Services, the former BALTEX stations and flow data are integrated in the Global Runoff Database.
National Hydrological Services have identified “climate sensitive” stations on request of the WMO Commission for Hydrology in order to assess the variability and trends in hydrological data associated with climate variability and change. GRDC has offered to integrate this dataset into the Global Runoff Database.
The GEMStat Dashboard visualizes the water quality of global water bodies on different spatial and temporal scales, based on data from the GEMStat Database . Available data includes the parameters dissolved oxygen, nitrogen, phosphorus and pH, all core parameters of the UN SDG 6.3.2 water quality indicator. The data are voluntarily provided by countries and organizations worldwide within the framework of the GEMS/Water Programme of the United Nations Environment Programme (UNEP) .