30 datasets found

This map illustrates the structures/buildings damaged by Tropical Cyclone MELISSA-25. The analysis focuses on Crawford Village, Black River District, Saint Elizabeth Parish, as of 29 October 2025, where damage was detected using a WorldView-2 very high-resolution satellite image acquired on 29 October 2025. UNOSAT identified approximately 1,089 buildings as 100% damaged.

This is a preliminary analysis and has not yet been validated in the field. Ground verification is encouraged, and feedback can be sent to the United Nations Satellite Centre (UNOSAT).

Lake-TopoCat provides a global-scale dataset that links lakes with their drainage topology, delineates catchments, defines inter-lake pathways, and quantifies topological attributes (upstream/downstream relationships, drainage distances, outlet multiplicity, etc.). The input is based on HydroLAKES v1.0 and MERIT Hydro (3 arcsec), with algorithms to detect possible lake bifurcation, unit catchment delineation, reach segmentation, and network attribution. The database includes:

• Lake boundary polygons (same as HydroLAKES) enriched with drainage attributes
• Lake outlet points
• Unit catchment polygons corresponding to each lake outlet
• Inter-lake reach lines connecting outlets
• Lake-network basins (basin polygons delineating the full drainage domain of each lake network)

It covers ~1.43 million lakes (≥10 ha) and ~1.46 million outlets globally, and ~3 million inter-lake reaches, spanning ~77.5 × 10⁶ km² of catchment coverage (≈ 57 % of global landmass, excluding Antarctica). The dataset is freely available via Zenodo (DOI: 10.5281/zenodo.7916729) and is licensed under CC BY 4.0.

The Global Groundwater Quality Portal by IGRAC is a dedicated platform for sharing global maps and datasets related to groundwater quality. It brings together data and models developed by IGRAC and its international partners, including global assessments of groundwater contamination and occurrence of key elements such as arsenic, fluoride, PFAS, and salinity. The portal provides harmonized geospatial information that supports global and regional monitoring of groundwater quality, promotes data accessibility, and contributes to sustainable groundwater management worldwide. It is part of IGRAC’s mission to facilitate international information exchange and knowledge sharing on groundwater resources.

This dataset contains layers for manuscript 'Capturing the complete landslide–debris-rich flood continuum for accurate inventory, susceptibility and exposure mapping – lessons from Cyclone Idai'. They provide a comprehensive analysis of impact, susceptibility and exposure to landslide and associated debris-rich floods in the Chimanimani and Chipinge districts, Zimbabwe. This work was carried out within the framework of the UNESCO project BE-RESILIENT Zimbabwe, funded by the World Bank and managed by the UNOPS Zimbabwe Idai Recovery Project. We also acknowledge support from BELSPO STEREO-IV LACTOSE project. The authors thank the local authorities who facilitated data collection and fieldwork in eastern Zimbabwe.

The MAR Portal contains the Global MAR Inventory, an inventory of over 1200 sites where Managed Aquifer Recharge is or has been implemented. The Global MAR Inventory includes information on site name, MAR type, year of scheme deployment, the source of infiltration water, the final use of abstracted water, as well as the main objectives of the project.

This dataset presents a MAR suitability map for North Kenya, developed by Acacia Water (2013). The study evaluates hydrogeological, climatic, and land use conditions to identify areas suitable for MAR implementation across the region. The dataset provides geospatial information that can support water resources planning, groundwater recharge strategies, and climate change adaptation measures in North Kenya. It is part of the global collection of MAR suitability assessments compiled by IGRAC.

If you would like to contribute data to the MAR portal, please contact us at info@un-igrac.org.

The MAR Portal contains the Global MAR Inventory, an inventory of over 1200 sites where Managed Aquifer Recharge is or has been implemented. The Global MAR Inventory includes information on site name, MAR type, year of scheme deployment, the source of infiltration water, the final use of abstracted water, as well as the main objectives of the project.

This dataset presents a MAR suitability map for Spain, developed under the DinaMAR project (2010). The study evaluates hydrogeological, climatic, and land use conditions to identify areas suitable for MAR implementation across the country. The dataset provides geospatial information that can support water resources planning, groundwater recharge strategies, and climate change adaptation measures in Spain. It is part of the global collection of MAR suitability assessments compiled by IGRAC.

If you would like to contribute data to the MAR portal, please contact us at info@un-igrac.org.

The MAR Portal contains the Global MAR Inventory, an inventory of over 1200 sites where Managed Aquifer Recharge is or has been implemented. The Global MAR Inventory includes information on site name, MAR type, year of scheme deployment, the source of infiltration water, the final use of abstracted water, as well as the main objectives of the project.

This dataset presents a MAR suitability map for Jordan, developed by Steinel et al. (2016). The study evaluates hydrogeological, climatic, and land use conditions to identify areas suitable for MAR implementation across the country. The dataset provides geospatial information that can support water resources planning, groundwater recharge strategies, and climate change adaptation measures in Jordan. It is part of the global collection of MAR suitability assessments compiled by IGRAC.

If you would like to contribute data to the MAR portal, please contact us at info@un-igrac.org.

The MAR Portal contains the Global MAR Inventory, an inventory of over 1200 sites where Managed Aquifer Recharge is or has been implemented. The Global MAR Inventory includes information on site name, MAR type, year of scheme deployment, the source of infiltration water, the final use of abstracted water, as well as the main objectives of the project.

This dataset presents a MAR suitability map for South Africa, developed by Department Water Affairs (2009). The study evaluates hydrogeological, climatic, and land use conditions to identify areas suitable for MAR implementation across the country. The dataset provides geospatial information that can support water resources planning, groundwater recharge strategies, and climate change adaptation measures in South Africa. It is part of the global collection of MAR suitability assessments compiled by IGRAC.

If you would like to contribute data to the MAR portal, please contact us at info@un-igrac.org.

The MAR Portal contains the Global MAR Inventory, an inventory of over 1200 sites where Managed Aquifer Recharge is or has been implemented. The Global MAR Inventory includes information on site name, MAR type, year of scheme deployment, the source of infiltration water, the final use of abstracted water, as well as the main objectives of the project.

The data shown in this portal have been made available by INOWAS (TU Dresden, Germany and funded by the German Federal Ministry of Education and Research) and the DEMEAU project (European Union FP7 project consortium). More information on the Global MAR Inventory project and its partners can be found or in the following publication: Stefan C. & Ansems N. (2017) Web-based global inventory of managed aquifer recharge applications. Sustain. Water Resour. Manag. https://doi.org/10.1007/s40899-017-0212-6.

The MAR Portal also contains a selection of regional MAR suitability maps, showing where MAR could be implemented.

If you would like to contribute data to the MAR portal, please contact us at info@un-igrac.org.

This dataset, compiled by Solar Chapter's Mengalir.co initiative, provides essential information on water infrastructure and access across 22 regencies in Indonesia's East Nusa Tenggara province. The data captures key water access metrics, infrastructure status, and demographic information to support water resource management, development planning, and humanitarian efforts in this semi-arid region. The dataset includes geospatial coordinates, administrative divisions, population demographics, water facility operations, access metrics, infrastructure types, water sources, and management entities for each regency.

The data synthesizes information from national and local government records, community participatory reports, and partner organization databases in an accessible CSV format for stakeholders addressing regional water challenges. This collection effort aims to support better planning and implementation of water solutions in East Nusa Tenggara, where many communities experience seasonal water shortages.

This map illustrates the satellite-detected water extent in Sindh, Balochistan, and Punjab Provinces, Pakistan, as observed from Sentinel-2 satellite images acquired on 31 July 2025 at 13:02 local time (08:02 UTC). Within the analyzed area of approximately 83,000 km², about 6,300 km² of land appears to be affected by floodwaters. The floodwater extent appears to have increased by approximately 1,300 km² since 11 July 2025. Based on WorldPop population data and the flood extent, approximately 2.3 million people are potentially exposed or living close to the flooded areas.

This dataset illustrates satellite-detected mudflow extent in Sao Vicente, Cabo Verde as observed from Pleiades very high-resolution satellite image. About 12 km² of land appears to be affected by the flood / mudflow extent. UNOSAT identified around 4200 affected buildings with around 12600 people potentially affected. In addition, approximately 80 km of roads with 5 bridges were affected.

This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to the United Nations Satellite Centre (UNOSAT).

This dataset illustrates satellite-detected mudflow extent in Santo Antao, Cabo Verde as observed from Pleiades very high-resolution satellite image. About 4 km² of land appears to be affected by the flood / mudflow extent. UNOSAT identified less than 460 affected buildings with less than 1000 people potentially affected. In addition, approximately 5 km of roads with 2 bridges were affected.

This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to the United Nations Satellite Centre (UNOSAT).

The Randolph Glacier Inventory (RGI) is a global set of glacier outlines intended as a snapshot of the world’s glaciers outside of ice sheets. It provides a single outline for each glacier from approximately the year 2000, as well as a set of attributes and other relevant auxiliary information. Glacier outlines are distributed as Shapefiles. Hypsometric data and attributes (CSV files) and metadata (json) are also available. All RGI data are packaged both globally and by region (as defined by the Global Terrestrial Network for Glaciers (GTN-G) Glacier Regions). The RGI is not suitable for measuring glacier-by-glacier rates of area change. However, it can be used to estimate glacier volumes; rates of elevation change at regional and global scales; and glacier responses to climatic forcing. RGI version 7.0 was developed by the “Working Group on the Randolph Glacier Inventory (RGI) and its role in future glacier monitoring” of the International Association of Cryospheric Sciences (IACS). The glaciological community contributes glacier mapping data to the Global Land Ice Measurements from Space (GLIMS) database. A subset of the glacier outlines in GLIMS are then extracted and reprocessed to produce the RGI. See the RGI documentation under "User Guide" (below) for more information.

The SIDS viewer provides groundwater related information on Small Island Developing States. At present the system contains mainly information derived from the Transboundary Waters Assessment Program (TWAP) on 43 SIDS. The data include indicators describing the hydrogeological, environmental, socio-economic and governance dimensions of the SIDS groundwater systems.

The data have been derived from questionnaire surveys and an extensive desk-top study executed by the Simon Frasier University (Canada) and coordinated by UNESCO-IHP. Data in the system can be explored and analysed using a map based viewer, which is particularly useful to make comparative analyses of multiple SIDS. Additionally SIDS information sheets are also available providing clear overviews per SIDS. Further data on SIDS will be collected and uploaded into the SIDS viewer as they become available.

For any queries or comments on the SIDS data and information, please visit our SIDS Focal Area page. (https://www.un-igrac.org/areas-expertise/small-island-developing-states-sids)

The Randolph Glacier Inventory (RGI) is a globally complete inventory of glacier outlines (excluding the ice sheets in Greenland and Antarctica). It is a subset of the database compiled by the Global Land Ice Measurements from Space (GLIMS) initiative. While GLIMS is a multi-temporal database with an extensive set of attributes, the RGI is intended to be a snapshot of the world’s glaciers at a specific target date, which in RGI 7.0 and all previous versions has been set as close as possible to the year 2000 (although in fact its range of dates can still be substantial in some regions). The RGI includes outlines of all glaciers larger than 0.01 km², which is the recommended minimum of the World Glacier Inventory.

The RGI was not designed for the measurement of glacier-by-glacier rates of area change, for which the greatest possible accuracy in dating, delineation and georeferencing is essential. While many RGI outlines meet these requirements, the primary focus of the RGI is on achieving global coverage, consistency, and proximity in a specific year. The strength of the RGI lies in its ability to handle large numbers of glaciers simultaneously. This allows, for example, for the estimation of glacier volumes and rates of elevation change at regional and global scales, as well as the simulation of cryospheric responses to climatic forcing.

Who develops and hosts the RGI? The RGI has been developed in an international community-driven effort of glaciologists starting in 2010. The inventory was named after “Randolph”, a town in New Hampshire, USA, where the team met for one of their meetings [Pfeffer et al., 2014]. In 2014 development of the RGI became the responsibility of the Working Group on the Randolph Glacier Inventory and Infrastructure for Glacier Monitoring, which operated under the International Association of Cryospheric Sciences (IACS). In 2019, a new Working Group was established to build upon the previous achievements and further expand its objectives: the IACS Working Group on the Randolph Glacier Inventory (RGI) and its role in future glacier monitoring and GLIMS.

The RGI datasets are listed on glims.org, and the RGI files can be downloaded through the data portal at the National Snow and Ice Data Center (NSIDC), which is the host for GLIMS.

Glacier product: includes outlines, attributes and auxiliary data for each individual glacier.

The Reference Observatory of Basins for INternational hydrological climate change detection (ROBIN) project established a new long-term collaboration of international experts to establish and sustain a global reference hydrological network (RHN), through common standards, protocols, indicators, and data infrastructure. ‘Reference Hydrometric Networks’ (RHNs), consist of gauging stations whose catchments are relatively undisturbed and record high quality data and little missing data. The concept of RHNs, their history and evolution are described in (Whitfield et al., 2012) previously and many countries have already established RHNs, however this is the first initiative to bring them together at a global level. The ROBIN Full Dataset consists of 3,060 stations in 30 countries, however the dataset described here is the ROBIN Public Dataset which contains metadata records for all 3,060 stations and daily streamflow data for a total of 2,386 stations. This tiered approached was due to data sharing restrictions in some countries. More information about the ROBIN Network and dataset can be found on the project website: https://www.ceh.ac.uk/our-science/projects/robin

The dataset covers the Counties of Turkana and Marsabit in northern Kenya. It includes borehole records with some geological and water quality measurements. It is part of the project "HYDROGEOLOGICAL MAPPING OF TURKANA and MARSABIT AQUIFERS" that was carried out by Rural Focus and SWAS WATER SURVEYS. A significant portion of the data that was required for these datasets was collected from various organizations including Oxfam, the Catholic Diocese of Lodwar, JICA, and the WRA of Kenya. The dataset has undergone improvements in accuracy and consistency while being normalized to align with UNESCO's groundwater data collection template.

Dataset with boreholes and dug wells in Ethiopia from mwater

The SWOT Level 2 River Single-Pass Vector Node Data Product from the Surface Water Ocean Topography (SWOT) mission provides water surface elevation, slope, width, and discharge derived from the high rate (HR) data stream from the Ka-band Radar Interferometer (KaRIn). SWOT launched on December 16, 2022 from Vandenberg Air Force Base in California into a 1-day repeat orbit for the "calibration" or "fast-sampling" phase of the mission, which completed in early July 2023. After the calibration phase, SWOT entered a 21-day repeat orbit in August 2023 to start the "science" phase of the mission, which is expected to continue through 2025.

Water surface elevation, slope, width, and discharge are provided for river reaches (approximately 10 km long) and nodes (approximately 200 m spacing) identified in the prior river database, and distributed as feature datasets covering the full swath for each continent-pass. These data are generally produced for inland and coastal hydrology surfaces, as controlled by the reloadable KaRIn HR mask. The dataset is distributed in ESRI Shapefile format. Please note that this collection contains SWOT Version C science data products.

This collection is a sub-collection of its parent: https://podaac.jpl.nasa.gov/dataset/SWOT_L2_HR_RiverSP_2.0 It contains only river nodes.