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This map illustrates the satellite-detected surface waters extent and evolution over Oponono Lake; a large wetland fed by the Culevai Oshana, in Oshana region, Namibia, as observed from the Sentinel-1 images acquired on 02 and 14 March 2017. An increase of surface water extent was detected in the 14 March 2017 image, particularly in the upstream part of the lake: ~4,130 ha of surface water were observed the 02 March 2017 within the lake area and reached ~10,820 ha the 14 March 2017 corresponding to an evolution of about 160%. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR - UNOSAT.
This theme includes all OpenStreetMap features in this area matching ( Learn what tags means here ) : tags['waterway'] IS NOT NULL OR tags['water'] IS NOT NULL OR tags['natural'] IN ('water','wetland','bay') Features may have these attributes: - name - name:en - waterway - covered - width - depth - layer - blockage - tunnel - natural - water - source - name:no This dataset is one of many OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.
The rainfall evapotranspiration is part of the actual EvapoTranspiration and Interception (ETIa) that is satified from precipitation. It is calculated by spliting ETIa to rainfall and blue ET using pixel based soil moisture water balance (PixSWAB) model. **Data publication:** 2023-01-25 **Supplemental Information:** No data value: -9999 Unit: mm **Contact points:** Metadata Contact: [FAO-Data](mailto:fao-data@fao.org) Resource Contact: [Solomon Seyoum](mailto:s.seyoum@un-ihe.org) **Resource constraints:** Creative Commons Attribution 4.0 International (CC-BY-4.0) **Online resources:** Download the data from Google Cloud Storage
The blue evapotranspiration is part of the actual EvapoTranspiration and Interception (ETIa) that is not satified from precipitation but from supply or runoff from other cells or from groundwater. It is calculated by spliting ETIa to rainfall and blue ET using pixel based soil moisture water balance (PixSWAB) model. **Data publication:** 2023-01-25 **Supplemental Information:** No data value: -9999 Unit: mm **Contact points:** Metadata Contact: [FAO-Data](mailto:fao-data@fao.org) Resource Contact: [Solomon Seyoum](mailto:s.seyoum@un-ihe.org) **Resource constraints:** Creative Commons Attribution 4.0 International (CC-BY-4.0) **Online resources:** Download the data from Google Cloud Storage
Precipitation minus actual EvapoTranspiration and Interception (P-ET) is the difference between WaPOR P and ETIa. **Data publication:** 2023-01-25 **Supplemental Information:** No data value: -9999 Unit: mm **Contact points:** Metadata Contact: [FAO-Data](mailto:fao-data@fao.org) Resource Contact: [Solomon Seyoum](mailto:s.seyoum@un-ihe.org) **Resource constraints:** Creative Commons Attribution 4.0 International (CC-BY-4.0) **Online resources:** Download the data from Google Cloud Storage
The land use map based on Water Accounting Plus land use classification is produced based on WaPOR land cover class and protected areas from the World Database on Protected Areas and reservoirs from GRaND. **Data publication:** 2023-01-25 **Supplemental Information:** No data value: -9999 **Contact points:** Metadata Contact: [FAO-Data](mailto:fao-data@fao.org) Resource Contact: [Solomon Seyoum](mailto:s.seyoum@un-ihe.org) **Resource constraints:** Creative Commons Attribution 4.0 International (CC-BY-4.0) **Online resources:** Download the data from Google Cloud Storage
Spatial distribution of net annual water loss from ponds through evaporation and seepage. The water balance for fishponds was calculated by estimating the deficit between precipitation and combined evaporation plus seepage. Evaporation was calculated using the Hargreaves formula (i.e. mean monthly minimum and maximum air temperature data were provided by FAO) and seepage was a constant. **Data publication:** 1997-01-01 **Supplemental Information:** This map derives from a wider study that evaluates inland fish farming potential at a continental-level, published by J.M. Kapetsky and S. S. Nath with the title "A strategic assessment of the potential for freshwater fish farming in Latin America " . COPESCAL Technical Paper. No. 10. Rome, FAO. 1997. 128p. Resolution 9 km x 9 km. **Contact points:** Metadata Contact: [Jose Aguilar-Manjarrez](mailto:Jose.AguilarManjarrez@fao.org) **Data lineage:** Conversion from ASCII files to Arc/Info GRID **Online resources:** Online resource Online resource Net annual water loss from ponds through evaporation and seepage Net annual water loss from ponds through evaporation and seepage (GRID format)
This dataset divides the Australian continent in major hydrological basins and their sub-basins according to its hydrological characteristics. It was obtained by delineating drainage basin boundaries from hydrologically corrected elevation data (WWF HydroSHEDS and Hydro1K). The dataset consists of the following information:- numerical code and name of the major basin (MAJ_BAS and MAJ_NAME); - area of the major basin in square km (MAJ_AREA); - numerical code and name of the sub-basin (SUB_BAS and SUB_NAME); - area of the sub-basin in square km (SUB_AREA); - numerical code of the sub-basin towards which the sub-basin flows (TO_SUBBAS) (the codes -888 and -999 have been assigned respectively to internal sub-basins and to sub-basins draining into the sea) **Data publication:** 2021-12-15 **Supplemental Information:** This dataset is developed as part of a GIS-based information system on water resources for the Australian continent. It has been published in the framework of the AQUASTAT - programme of the Land and Water Division of the Food and Agriculture Organization of the United Nations. **Contact points:** Metadata Contact: [AQUASTAT](mailto:aquastat@fao.org) Resource Contact: [Jippe Hoogeveen](mailto:jippe.hoogeveen@fao.org) **Data lineage:** The linework of the map was obtained by delineating drainage basin boundaries from hydrologically corrected elevation data with a resolution of 15 arc-seconds.The elevation dataset was part of a mapping product, HydroSHEDS, developed by the Conservation Science Program of World Wildlife Fund.Original input data had been obtained during NASA's Shuttle Radar Topography Mission (SRTM). **Online resources:** Download - Hydrological basins in Australia and New Zealand (ESRI shapefile) General information regarding the HydroSHEDS data product HydroSHEDS dataset download and technical information Rivers of Australia and New Zealand
SDG 6 Foundation Basin Units (SDG6-FBU). The SDG6-FBU is a geo-spatial data layer with spatial information derived from HydroBASIN level 12 (https://www.hydrosheds.org/products/hydrobasins). Each of these small hydrological units (approximately 1 million basins) is named according to the ‘SDG 6 Major Basin’ and ‘SDG 6 Sub-Basin’ classification, with the sub-basins nested within the major basins. **Data publication:** 2025-05-02 **Supplemental Information:** The dataset is included as part of Geo-Spatial Information collected and published in the framework of the AQUASTAT - programme of the Land and Water Division of the Food and Agriculture Organization of the United Nations. https://www.fao.org/aquastat/ **Citation:** Integrated Monitoring Initiative for SDG 6 (IMI-SDG 6), SDG6 Basin Maps, Foundation Basin Units, Latest update: 31/07/2024. Accessed (dd-mm/yy) from: https://data.apps.fao.org/catalog/iso/edit/edc5d019-e185-4104-8c13-3261c96e4c0a **Contact points:** Resource Contact: [Jippe Hoogeveen](mailto:jippe.hoogeveen@fao.org) Metadata Contact: [AQUASTAT](mailto:aquastat@fao.org) **Data lineage:** SDG 6 Foundation Basin Units (SDG6-FBU). The SDG6-FBU is a geo-spatial data layer with spatial information derived from HydroBASIN level 12 (https://www.hydrosheds.org/products/hydrobasins). Each of these small hydrological units (approximately 1 million basins) maintains attribute information from the following 4 source layers: • FAO (major basins and sub-basins) • TWAP (river basins component) • GRDC (river basins) • WMO (major basins and sub-basins), which allows for backward compatibility to be maintained to each source layer. In addition, each hydrological unit will be named according to the new ‘SDG 6 Major Basin’ and ‘SDG 6 Sub-Basin’ classification, with the sub-basins nested within the major basins. These new SDG 6 classifications will draw initially upon the source layers and then over time be revised based on country information. All improvements of the SDG 6 Basin Map will be conducted in this layer. This product "SDG 6 Foundation Basin Units (SDG6-FBU)" incorporates data from the HydroSHEDS database (https://www.hydrosheds.org/) which is © World Wildlife Fund, Inc. (2006-2013) and has been used herein under license. WWF has not evaluated the data and therefore gives no warranty regarding its accuracy, completeness, currency or suitability for any particular purpose. **Resource constraints:** This work is made available under the Creative Commons Attribution 4.0 International licence (CC-BY-4.0) **Online resources:** Download the data from Google Cloud Storage SDG6_BasinMaps_Final_Report_v1 SDG6_BasinMaps_Final_Report_v1_Appendices
SDG 6 Foundation Basin Units (SDG6-FBU). The SDG6-FBU is a geo-spatial data layer with spatial information derived from HydroBASIN level 12 (https://www.hydrosheds.org/products/hydrobasins). Each of these small hydrological units (approximately 1 million basins) is named according to the ‘SDG 6 Major Basin’ and ‘SDG 6 Sub-Basin’ classification, with the sub-basins nested within the major basins. **Data publication:** 2025-05-02 **Supplemental Information:** The dataset is included as part of Geo-Spatial Information collected and published in the framework of the AQUASTAT - programme of the Land and Water Division of the Food and Agriculture Organization of the United Nations. https://www.fao.org/aquastat/ **Citation:** Integrated Monitoring Initiative for SDG 6 (IMI-SDG 6), SDG6 Basin Maps, Foundation Basin Units, Latest update: 31/07/2024. Accessed (dd-mm/yy) from: https://data.apps.fao.org/catalog/iso/edit/40bd6443-055a-4f76-b81f-187d08e9a77e **Contact points:** Resource Contact: [Jippe Hoogeveen](mailto:jippe.hoogeveen@fao.org) Metadata Contact: [AQUASTAT](mailto:aquastat@fao.org) **Data lineage:** SDG 6 Foundation Basin Units (SDG6-FBU). The SDG6-FBU is a geo-spatial data layer with spatial information derived from HydroBASIN level 12 (https://www.hydrosheds.org/products/hydrobasins). Each of these small hydrological units (approximately 1 million basins) maintains attribute information from the following 4 source layers: • FAO (major basins and sub-basins) • TWAP (river basins component) • GRDC (river basins) • WMO (major basins and sub-basins), which allows for backward compatibility to be maintained to each source layer. In addition, each hydrological unit will be named according to the new ‘SDG 6 Major Basin’ and ‘SDG 6 Sub-Basin’ classification, with the sub-basins nested within the major basins. These new SDG 6 classifications will draw initially upon the source layers and then over time be revised based on country information. All improvements of the SDG 6 Basin Map will be conducted in this layer. This product "SDG 6 Foundation Basin Units (SDG6-FBU)" incorporates data from the HydroSHEDS database (https://www.hydrosheds.org/) which is © World Wildlife Fund, Inc. (2006-2013) and has been used herein under license. WWF has not evaluated the data and therefore gives no warranty regarding its accuracy, completeness, currency or suitability for any particular purpose. **Resource constraints:** This work is made available under the Creative Commons Attribution 4.0 International licence (CC-BY-4.0) **Online resources:** Download the data from Google Cloud Storage SDG6_BasinMaps_Final_Report_v1 SDG6_BasinMaps_Final_Report_v1_Appendices
The rivers of South America are derived from the World Wildlife Fund's (WWF) HydroSHEDS drainage direction layer and a stream network layer.The drainage direction layer was created from NASA's Shuttle Radar Topographic Mission (SRTM) 15-second Digital Elevation Model (DEM).The raster stream network was determined by using the HydroSHEDS flow accumulation grid, with a threshold of about 100 km² upstream area. The stream network dataset consists of the following information: the origin node of each arc in the network (FROM_NODE), the destination of each arc in the network (TO_NODE), the Strahler stream order of each arc in the network (STRAHLER), numerical code and name of the major basin that the arc falls within (MAJ_BAS and MAJ_NAME); - area of the major basin in square km that the arc falls within (MAJ_AREA); - numerical code and name of the sub-basin that the arc falls within (SUB_BAS and SUB_NAME); - area of the sub-basin in square km that the arc falls within (SUB_AREA); - numerical code of the sub-basin towards which the sub-basin flows that the arc falls within (TO_SUBBAS) (the codes -888 and -999 have been assigned respectively to internal sub-basins and to sub-basins draining into the sea). The attributes table now includes a field named "Regime" with tentative classification of perennial ("P") and intermittent ("I") streams. **Data revision:** 2014-03-05 **Supplemental Information:** This dataset is developed as part of a GIS-based information system on water resources for South America. It has been published in the framework of the AQUASTAT - programme of the Land and Water Division of the Food and Agriculture Organization of the United Nations. **Time coverage**: 2014 **Contact points:** Resource Contact: [Jippe Hoogeveen](mailto:Jippe.Hoogeveen@fao,org) Resource Contact: [Livia Peiser](mailto:Livia.Peiser@fao.org) Metadata Contact: [AQUASTAT](mailto:aquastat@fao.org) **Data lineage:** The linework of the map was obtained by converting the stream network to a feature dataset with the Hydrology toolset in ESRI ArcGIS.The Flow Direction and Stream Order grids were derived from hydrologically corrected elevation data with a resolution of 15 arc-seconds.The elevation dataset was part of a mapping product, HydroSHEDS, developed by the Conservation Science Program of World Wildlife Fund.Original input data had been obtained during NASA's Shuttle Radar Topography Mission (SRTM). **Resource constraints:** This work is made available under the Creative Commons Attribution 4.0 International licence (CC-BY-4.0) **Online resources:** Download - Rivers of South America (ESRI shapefile) Technical information on the data source More updated information on HydroSHEDS 2025
Geo-referenced point database on dams in Central Asia. This dataset is described extensively on the AQUASTAT website at https://www.fao.org/aquastat/en/databases/dams. On this website, the dataset is also published in Excel to facilitate the publication of information on dams without geographical co-ordinates. It is accompanied by an explanatory document that provides specific information about the references used, and brief notes on the more complicated dams. For shapefile description, please see the READ ME in the zip file. **Data publication:** 2013-06-24 **Contact points:** Metadata Contact: [AQUASTAT](mailto:aquastat@fao.org) **Data lineage:** More information on this data on the AQUASTAT Website at https://www.fao.org/aquastat/en/databases/dams **Resource constraints:** This work is made available under the Creative Commons Attribution 4.0 International license (CC-BY-4.0) **Online resources:** Download - Dams in Central Asia (ESRI shapefile) Geo-referenced dam databases on AQUASTAT website
This map, compiled to support the analysis of SOLAW report concerning trends and current use of water use in agriculture, shows the percentage of irrigated area supplied by groundwater. Irrigation mainly relies on renewable freshwater resources, either surface water or groundwater. However, while the extent of irrigation and related water uses are reported in statistical databases or by model simulations, information on the source of irrigation water is still very rare. A recent global inventory undertaken by FAO and the University of Bonn reports that 113 million ha, or 38 percent of the total area equipped for irrigation of 301 million ha, is irrigated by groundwater (Siebert et al, 2010). **Data creation:** 2025-12-11 **Contact points:** Metadata Contact: [AQUASTAT](mailto:aquastat@fao.org) **Data lineage:** Input data for this map include: - Global map of irrigation areas at 5 arc-min (Siebert et al., 2007) - Data on sources of irrigation water available by country through the FAO AQUASTAT database - Additional data obtained through desk studies on distribution of sources of irrigation water. The legend indicates the share of irrigated land serviced by groundwater in each pixel. **Resource constraints:** This work is made available under the Creative Commons Attribution 4.0 International license (CC-BY-4.0) **Online resources:** Download - Percentage of irrigated area serviced by groundwater (ESRI GRID) SOLAW web page
Reference EvapoTranspiration (RET) is defined as the evapotranspiration from a hypothetical reference crop and it simulates the behaviour of a well-watered grass surface. The value of each pixel represents the total of the daily reference evapotranspiration for that specific year. The data is provided from January 2009 to 2022. **Data publication:** 2020-01-01 **Supplemental Information:** No data value: -9999 Unit: mm (1mm=1l/m² or 1mm=10m³/ha) Conversion factor: the pixel value in the downloaded data must be multiplied by 0.1 New dekadal data layers are released approximately 5 days after the end of a dekad. A higher quality version of the same data layer is uploaded after 6 dekads have passed. This final version of the dekadal dataset has a higher quality because gap filling and interpolation processes, where needed, have been based on more data observations. This implies that other temporal aggregations (monthly, seasonal, annual), and layers that depend on those, are updated as well. Practically this means that a final annual aggregation of the most recent full calendar year can only be produced after the end of February. Likewise, the final monthly aggregation of the most recent calendar months can only be produced 2 full months later. **Citation:** FAO 2018. WaPOR Database Methodology: Level 1. Remote Sensing for Water Productivity Technical Report: Methodology Series. Rome, FAO. 72 pages. Licence: CC BY 4.0 IGO **Contact points:** Metadata Contact: [WaPOR](mailto:wapor@fao.org) Resource Contact: [WaPOR](mailto:wapor@fao.org) **Data lineage:** See daily Reference EvapoTranspiration (L1_RET_E) for further information. The annual data is obtained by taking the daily RET, summing the days of each year. **Resource constraints:** Creative Commons Attribution 4.0 International (CC BY 4.0) **Online resources:** Download the data from Google Cloud Storage
The actual Evapotranspiration and Interception (ETIa) is the sum of the soil evaporation (E), canopy transpiration (T), and evaporation from rainfall intercepted by leaves (I). The value of each pixel represents the ETIa in a given year. The data is provided from January 2009 to 2023. **Data publication:** 2020-01-01 **Supplemental Information:** No data value: -9999 Unit : mm Map code : L1-AETI-A Scale Factor : 0.1 Conversion factor: the pixel value in the downloaded data must be multiplied by 0.1 New dekadal data layers are released approximately 5 days after the end of a dekad. A higher quality version of the same data layer is uploaded after 6 dekads have passed. This final version of the dekadal dataset has a higher quality because gap filling and interpolation processes, where needed, have been based on more data observations. This implies that other temporal aggregations (monthly, seasonal, annual), and layers that depend on those, are updated as well. Practically this means that a final annual aggregation of the most recent full calendar year can only be produced after the end of February. Likewise, the final monthly aggregation of the most recent calendar months can only be produced 2 full months later. **Citation:** FAO 2018. WaPOR Database Methodology: Level 1. Remote Sensing for Water Productivity Technical Report: Methodology Series. Rome, FAO. 72 pages. Licence: CC-BY-4.0 **Contact points:** Metadata Contact: [WaPOR](mailto:wapor@fao.org) Resource Contact: [WaPOR](mailto:wapor@fao.org) **Data lineage:** See ETIa by dekad for further information. The annual total is obtained by taking the ETIa in mm/day, multiplying by the number of days in a dekad, and summing the dekads of each year. **Resource constraints:** Creative Commons Attribution 4.0 International (CC BY 4.0) **Online resources:** Download the data from Google Cloud Storage
The actual Evapotranspiration and Interception (ETIa) is the sum of the soil evaporation (E), canopy transpiration (T), and evaporation from rainfall intercepted by leaves (I). The value of each pixel represents the ETIa in a given month. The data is provided from January 2009 to 2023. **Data publication:** 2020-01-01 **Supplemental Information:** No data value: -9999 Unit: mm Map code : L1-AETI-M Scale Factor : 0.1 Conversion factor: the pixel value in the downloaded data must be multiplied by 0.1 New dekadal data layers are released approximately 5 days after the end of a dekad. A higher quality version of the same data layer is uploaded after 6 dekads have passed. This final version of the dekadal dataset has a higher quality because gap filling and interpolation processes, where needed, have been based on more data observations. This implies that other temporal aggregations (monthly, seasonal, annual), and layers that depend on those, are updated as well. Practically this means that a final annual aggregation of the most recent full calendar year can only be produced after the end of February. Likewise, the final monthly aggregation of the most recent calendar months can only be produced 2 full months later. **Citation:** FAO 2018. WaPOR Database Methodology: Level 1. Remote Sensing for Water Productivity Technical Report: Methodology Series. Rome, FAO. 72 pages. Licence: CC BY 4.0 IGO **Contact points:** Metadata Contact: [WaPOR](mailto:wapor@fao.org) Resource Contact: [WaPOR](mailto:wapor@fao.org) **Data lineage:** See ETIa by dekad for further information. The monthy total is obtained by taking the ETIa in mm/day, multiplying by the number of days in a dekad, and summing the dekads of each month. **Resource constraints:** Creative Commons Attribution 4.0 International (CC BY 4.0) **Online resources:** Download the data from Google Cloud Storage
The actual Evapotranspiration and Interception (ETIa) (dekadal, in mm/day) is the sum of the soil evaporation (E), canopy transpiration (T), and evaporation from rainfall intercepted by leaves (I). The value of each pixel represents the average daily ETIa in a given dekad. The data is provided from January 2009 to 2023. **Data publication:** 2020-01-01 **Supplemental Information:** No data value: -9999 Unit: mm Map code : L1-AETI-D Scale Factor : 0.1 Conversion factor: the pixel value in the downloaded data must be multiplied by 0.1 New dekadal data layers are released approximately 5 days after the end of a dekad. A higher quality version of the same data layer is uploaded after 6 dekads have passed. This final version of the dekadal dataset has a higher quality because gap filling and interpolation processes, where needed, have been based on more data observations. **Citation:** FAO 2018. WaPOR Database Methodology: Level 1. Remote Sensing for Water Productivity Technical Report: Methodology Series. Rome, FAO. 72 pages. Licence: CC-BY-4.0 **Contact points:** Metadata Contact: [WaPOR](mailto:wapor@fao.org) Resource Contact: [WaPOR](mailto:wapor@fao.org) **Data lineage:** The calculation of the ETIa is based on the ETLook model described in Bastiaanssen et al. (2012). See the methodology of the three components (E, T and I) for further information. **Resource constraints:** Creative Commons Attribution 4.0 International (CC BY 4.0) **Online resources:** Download the data from Google Cloud Storage
The Evaporation (E) data component is the actual evaporation of the soil surface. The value of each pixel represents the total annual evaporation for that specific year. The data is provided from January 2009 to 2023. **Data publication:** 2020-01-01 **Supplemental Information:** No data value: -9999 Unit: mm Map code : L1-E-A Scale Factor : 0.1 Conversion factor: the pixel value in the downloaded data must be multiplied by 0.1 New dekadal data layers are released approximately 5 days after the end of a dekad. A higher quality version of the same data layer is uploaded after 6 dekads have passed. This final version of the dekadal dataset has a higher quality because gap filling and interpolation processes, where needed, have been based on more data observations. This implies that other temporal aggregations (monthly, seasonal, annual), and layers that depend on those, are updated as well. Practically this means that a final annual aggregation of the most recent full calendar year can only be produced after the end of February. Likewise, the final monthly aggregation of the most recent calendar months can only be produced 2 full months later. **Citation:** FAO 2018. WaPOR Database Methodology: Level 1. Remote Sensing for Water Productivity Technical Report: Methodology Series. Rome, FAO. 72 pages. Licence: CC-BY-4.0 **Contact points:** Metadata Contact: [WaPOR](mailto:wapor@fao.org) Resource Contact: [WaPOR](mailto:wapor@fao.org) **Data lineage:** See evaporation (E) by dekad for further information. The annual total is obtained by taking the E in mm/day, multiplying by the number of days in a dekad, and summing the dekads of each year. **Resource constraints:** Creative Commons Attribution 4.0 International (CC BY 4.0) **Online resources:** Download the data from Google Cloud Storage
The Evaporation (E) data component (dekadal, in mm/day) is the actual evaporation of the soil surface. The value of each pixel represents the average daily actual evaporation for that specific dekad. The data is provided from January 2009 to 2023. **Data publication:** 2020-01-01 **Supplemental Information:** No data value: 255 Unit: mm Map code : L1-E-D Scale Factor : 0.1 Conversion factor: the pixel value in the downloaded data must be multiplied by 0.1 New dekadal data layers are released approximately 5 days after the end of a dekad. A higher quality version of the same data layer is uploaded after 6 dekads have passed. This final version of the dekadal dataset has a higher quality because gap filling and interpolation processes, where needed, have been based on more data observations. **Citation:** FAO 2018. WaPOR Database Methodology: Level 1. Remote Sensing for Water Productivity Technical Report: Methodology Series. Rome, FAO. 72 pages. Licence: CC-BY-4.0 **Contact points:** Metadata Contact: [WaPOR](mailto:wapor@fao.org) Resource Contact: [WaPOR](mailto:wapor@fao.org) **Data lineage:** The calculation of the evaporation is based on the ETLook model described in Bastiaanssen et al. (2012). It uses the Penman-Monteith equation, adapted to remote sensing input data. The Penman-Monteith equation predicts the rate of total evaporation and transpiration using commonly measured meteorological data (solar radiation, air temperature, vapour content and wind speed). It has become the FAO standard for calculating the actual and reference evapotranspiration (see FAO Irrigation and Drainage paper 56, Allen et al. 1998). The following data is used for calculating evaporation: - Daily: incoming solar radiation and weather data (temperature, humidity, wind speed and precipitation); - Dekadal: NDVI, surface albedo and soil moisture stress; - Seasonal: Land Cover; - Static: Digital Elevation Model. Data component developed through collaboration with the FRAME Consortium. More information can be found on the WaPOR Website. **Resource constraints:** Creative Commons Attribution 4.0 International (CC BY 4.0) **Online resources:** Download the data from Google Cloud Storage Evaporation (Africa and Near East - Dekadal - 250m)
The Transpiration (T) data component is the actual transpiration of the vegetation canopy. The value of each pixel represents the total annual transpiration for that specific year. The data is provided from January 2009 to 2023. **Data publication:** 2020-01-01 **Supplemental Information:** No data value: -9999 Unit: mm Map code : L1-T-A Scale Factor : 0.1 Conversion factor: the pixel value in the downloaded data must be multiplied by 0.1 New dekadal data layers are released approximately 5 days after the end of a dekad. A higher quality version of the same data layer is uploaded after 6 dekads have passed. This final version of the dekadal dataset has a higher quality because gap filling and interpolation processes, where needed, have been based on more data observations. This implies that other temporal aggregations (monthly, seasonal, annual), and layers that depend on those, are updated as well. Practically this means that a final annual aggregation of the most recent full calendar year can only be produced after the end of February. Likewise, the final monthly aggregation of the most recent calendar months can only be produced 2 full months later. **Citation:** FAO 2018. WaPOR Database Methodology: Level 1. Remote Sensing for Water Productivity Technical Report: Methodology Series. Rome, FAO. 72 pages. Licence: CC BY 4.0 IGO **Contact points:** Metadata Contact: [WaPOR](mailto:wapor@fao.org) Resource Contact: [WaPOR](mailto:wapor@fao.org) **Data lineage:** See transpiration (T) by dekad for further information. The annual total is obtained by taking the T in mm/day, multiplying by the number of days in a dekad, and summing the dekads of each year. **Resource constraints:** Creative Commons Attribution 4.0 International (CC BY 4.0) **Online resources:** Download the data from Google Cloud Storage
The transpiration (T) data component (dekadal, in mm/day) is the actual transpiration of the vegetation canopy. The value of each pixel represents the average daily actual transpiration for that specific dekad. The data is provided from January 2009 to 2023. **Data publication:** 2020-01-01 **Supplemental Information:** No data value: 255 Unit: mm Map code : L1-T-D Scale Factor : 0.1 Conversion factor: the pixel value in the downloaded data must be multiplied by 0.1 New dekadal data layers are released approximately 5 days after the end of a dekad. A higher quality version of the same data layer is uploaded after 6 dekads have passed. This final version of the dekadal dataset has a higher quality because gap filling and interpolation processes, where needed, have been based on more data observations. **Citation:** FAO 2018. WaPOR Database Methodology: Level 1. Remote Sensing for Water Productivity Technical Report: Methodology Series. Rome, FAO. 72 pages. Licence: CC BY 4.0 IGO **Contact points:** Metadata Contact: [WaPOR](mailto:wapor@fao.org) Resource Contact: [WaPOR](mailto:wapor@fao.org) **Data lineage:** The calculation of the transpiration is based on the ETLook model described in Bastiaanssen et al. (2012). It uses the Penman-Monteith equation, adapted to remote sensing input data. The Penman-Monteith equation predicts the rate of total evaporation and transpiration using commonly measured meteorological data (solar radiation, air temperature, vapour content and wind speed). It has become the FAO standard for calculating the actual and reference evapotranspiration (see FAO Irrigation and Drainage paper 56, Allen et al. 1998). The following data is used for calculating transpiration: - Daily: incoming solar radiation and weather data (temperature, humidity, wind speed and precipitation); - Dekadal: NDVI, surface albedo and soil moisture stress; - Seasonal: Land Cover; - Static: Digital Elevation Model. Data component developed through collaboration with the FRAME Consortium. More information can be found at: http://www.fao.org/in-action/remote-sensing-for-water-productivity/en/ **Resource constraints:** Creative Commons Attribution 4.0 International (CC BY 4.0) **Online resources:** Download the data from Google Cloud Storage
Interception is the process where rainfall is captured by the leaves. Part of this captured rainfall will evaporate again. The Interception (I) data component represents the evaporation of intercepted rainfall from the vegetation canopy. The value of each pixel represents the total annual interception for that specific year. The data is provided from January 2009 to 2023. **Data publication:** 2020-01-01 **Supplemental Information:** No data value: -9999 Unit: mm Map code : L1-I-A Scale Factor : 0.1 Conversion factor: the pixel value in the downloaded data must be multiplied by 0.1 New dekadal data layers are released approximately 5 days after the end of a dekad. A higher quality version of the same data layer is uploaded after 6 dekads have passed. This final version of the dekadal dataset has a higher quality because gap filling and interpolation processes, where needed, have been based on more data observations. This implies that other temporal aggregations (monthly, seasonal, annual), and layers that depend on those, are updated as well. Practically this means that a final annual aggregation of the most recent full calendar year can only be produced after the end of February. Likewise, the final monthly aggregation of the most recent calendar months can only be produced 2 full months later. **Citation:** FAO 2018. WaPOR Database Methodology: Level 1. Remote Sensing for Water Productivity Technical Report: Methodology Series. Rome, FAO. 72 pages. Licence: CC BY 4.0 IGO **Contact points:** Metadata Contact: [WaPOR](mailto:wapor@fao.org) Resource Contact: [WaPOR](mailto:wapor@fao.org) **Data lineage:** See interception (I) by dekad for further information. The annual total is obtained by taking the I in mm/day, multiplying by the number of days in a dekad, and summing the dekads of each year. **Resource constraints:** Creative Commons Attribution 4.0 International (CC BY 4.0) **Online resources:** Download the data from Google Cloud Storage
The Interception (I) data component (dekadal, in mm/day) represents the evaporation of intercepted rainfall from the vegetation canopy. Interception is the process where rainfall is captured by the leaves. Part of this captured rainfall will evaporate again. The value of each pixel represents the average daily evaporated interception for that specific dekad. The data is provided from January 2009 to 2023. **Data publication:** 2020-01-01 **Supplemental Information:** No data value: 255 Unit: mm Map code : L1-I-D Scale Factor : 0.1 Conversion factor: the pixel value in the downloaded data must be multiplied by 0.1 New dekadal data layers are released approximately 5 days after the end of a dekad. A higher quality version of the same data layer is uploaded after 6 dekads have passed. This final version of the dekadal dataset has a higher quality because gap filling and interpolation processes, where needed, have been based on more data observations. **Citation:** FAO 2018. WaPOR Database Methodology: Level 1. Remote Sensing for Water Productivity Technical Report: Methodology Series. Rome, FAO. 72 pages. Licence: CC BY 4.0 IGO **Contact points:** Metadata Contact: [WaPOR](mailto:wapor@fao.org) Resource Contact: [WaPOR](mailto:wapor@fao.org) **Data lineage:** Evaporation of intercepted rainfall requires energy that is not available for transpiration or evaporation. Interception is a function of the vegetation cover and precipitation. Interception is relatively high with a small amount of precipitation, with the fraction intercepted decreasing quickly as precipitation increases. The maximum interception is determined by the LAI. The following data is used for calculating interception: - Daily: incoming solar radiation and weather data (temperature, humidity and precipitation); - Dekadal: NDVI. Data component developed through collaboration with the FRAME Consortium. More information can be found at: http://www.fao.org/in-action/remote-sensing-for-water-productivity/en/ **Resource constraints:** Creative Commons Attribution 4.0 International (CC BY 4.0) **Online resources:** Download the data from Google Cloud Storage
The interception (I) data component (dekadal, in mm/day) represents the evaporation of intercepted rainfall from the vegetation canopy. Interception is the process where rainfall is captured by the leaves. Part of this captured rainfall will evaporate again. The value of each pixel represents the average daily evaporated interception for that specific dekad. The data is provided from January 2009 to 2023. **Data publication:** 2020-01-01 **Supplemental Information:** No data value: 255 Unit: mm Scale Factor : 0.1 Map code : L2-I-D Conversion factor: the pixel value in the downloaded data must be multiplied by 0.1 New dekadal data layers are released approximately 5 days after the end of a dekad. A higher quality version of the same data layer is uploaded after 6 dekads have passed. This final version of the dekadal dataset has a higher quality because gap filling and interpolation processes, where needed, have been based on more data observations. **Citation:** FAO 2018. WaPOR Database Methodology: Level 2. Remote Sensing for Water Productivity Technical Report: Methodology Series. Rome, FAO. 72 pages. Licence: CC-BY-4.0 **Contact points:** Metadata Contact: [WaPOR](mailto:wapor@fao.org) Resource Contact: [WaPOR](mailto:wapor@fao.org) **Data lineage:** Evaporation of intercepted rainfall requires energy that is not available for transpiration or evaporation. Interception is a function of the vegetation cover and precipitation. Interception is relatively high with a small amount of precipitation, with the fraction intercepted decreasing quickly as precipitation increases. The maximum interception is determined by the LAI. The following data is used for calculating interception: - Daily: incoming solar radiation and weather data (temperature, humidity and precipitation); - Dekadal: NDVI. Data component developed through collaboration with the FRAME Consortium. More information can be found at: http://www.fao.org/in-action/remote-sensing-for-water-productivity/en/. Until December 2019 the base input layers (NDVI, albedo, and fAPAR) for the Level 2 (100m) products were derived from the Proba-V satellite. Proba-V was decommissioned in June 2020. From January 2020 onwards the base input layers of NDVI, albedo and fAPAR for level 2 are derived from the Copernicus Sentinel-2 mission. **Resource constraints:** Creative Commons Attribution 4.0 International (CC-BY-4.0) **Online resources:** Download the data from Google Cloud Storage Interception (Africa and Near East - Dekadal - 100m)
Interception is the process where rainfall is captured by the leaves. Part of this captured rainfall will evaporate again. The Interception (I) data component represents the evaporation of intercepted rainfall from the vegetation canopy. The value of each pixel represents the total annual interception for that specific year. The data is provided from January 2009 to 2023. **Data publication:** 2020-01-01 **Supplemental Information:** No data value: -9999 Unit: mm Scale Factor : 0.1 Map code : L2-I-A Conversion factor: the pixel value in the downloaded data must be multiplied by 0.1 New dekadal data layers are released approximately 5 days after the end of a dekad. A higher quality version of the same data layer is uploaded after 6 dekads have passed. This final version of the dekadal dataset has a higher quality because gap filling and interpolation processes, where needed, have been based on more data observations. This implies that other temporal aggregations (monthly, seasonal, annual), and layers that depend on those, are updated as well. Practically this means that a final annual aggregation of the most recent full calendar year can only be produced after the end of February. Likewise, the final monthly aggregation of the most recent calendar months can only be produced 2 full months later. **Citation:** FAO 2018. WaPOR Database Methodology: Level 2. Remote Sensing for Water Productivity Technical Report: Methodology Series. Rome, FAO. 72 pages. Licence: CC-BY-4.0 **Contact points:** Metadata Contact: [WaPOR](mailto:wapor@fao.org) Resource Contact: [WaPOR](mailto:wapor@fao.org) **Data lineage:** See interception (I) by dekad for further information. The annual total is obtained by taking the I in mm/day, multiplying by the number of days in a dekad, and summing the dekads of each year. Until December 2019 the base input layers (NDVI, albedo, and fAPAR) for the Level 2 (100m) products were derived from the Proba-V satellite. Proba-V was decommissioned in June 2020. From January 2020 onwards the base input layers of NDVI, albedo and fAPAR for level 2 are derived from the Copernicus Sentinel-2 mission. **Resource constraints:** Creative Commons Attribution 4.0 International (CC-BY-4.0) **Online resources:** Download the data from Google Cloud Storage
The transpiration (T) data component (dekadal, in mm/day) is the actual transpiration of the vegetation canopy. The value of each pixel represents the average daily actual transpiration for that specific dekad. The data is provided from January 2009 to 2023. **Data publication:** 2020-01-01 **Supplemental Information:** No data value: 255 Unit: mm Scale Factor : 0.1 Map code : L2-T-D Conversion factor: the pixel value in the downloaded data must be multiplied by 0.1 New dekadal data layers are released approximately 5 days after the end of a dekad. A higher quality version of the same data layer is uploaded after 6 dekads have passed. This final version of the dekadal dataset has a higher quality because gap filling and interpolation processes, where needed, have been based on more data observations. **Citation:** FAO 2018. WaPOR Database Methodology: Level 2. Remote Sensing for Water Productivity Technical Report: Methodology Series. Rome, FAO. 72 pages. Licence: CC-BY-4.0 **Contact points:** Metadata Contact: [WaPOR](mailto:wapor@fao.org) Resource Contact: [WaPOR](mailto:wapor@fao.org) **Data lineage:** The calculation of the transpiration is based on the ETLook model described in Bastiaanssen et al. (2012). It uses the Penman-Monteith equation, adapted to remote sensing input data. The Penman-Monteith equation predicts the rate of total evaporation and transpiration using commonly measured meteorological data (solar radiation, air temperature, vapour content and wind speed). It has become the FAO standard for calculating the actual and reference evapotranspiration (see FAO Irrigation and Drainage paper 56, Allen et al. 1998). The following data is used for calculating transpiration: - Daily: incoming solar radiation and weather data (temperature, humidity, wind speed and precipitation); - Dekadal: NDVI, surface albedo and soil moisture stress; - Seasonal: Land Cover; - Static: Digital Elevation Model. Data component developed through collaboration with the FRAME Consortium. More information can be found at: http://www.fao.org/in-action/remote-sensing-for-water-productivity/en/. Until December 2019 the base input layers (NDVI, albedo, and fAPAR) for the Level 2 (100m) products were derived from the Proba-V satellite. Proba-V was decommissioned in June 2020. From January 2020 onwards the base input layers of NDVI, albedo and fAPAR for level 2 are derived from the Copernicus Sentinel-2 mission. **Resource constraints:** Creative Commons Attribution 4.0 International (CC-BY-4.0) **Online resources:** Download the data from Google Cloud Storage
The Transpiration (T) data component is the actual transpiration of the vegetation canopy. The value of each pixel represents the total annual transpiration for that specific year. The data is provided from January 2009 to 2023. **Data publication:** 2020-01-01 **Supplemental Information:** No data value: -9999 Unit: mm Scale Factor : 0.1 Map code : L2-T-A Conversion factor: the pixel value in the downloaded data must be multiplied by 0.1 New dekadal data layers are released approximately 5 days after the end of a dekad. A higher quality version of the same data layer is uploaded after 6 dekads have passed. This final version of the dekadal dataset has a higher quality because gap filling and interpolation processes, where needed, have been based on more data observations. This implies that other temporal aggregations (monthly, seasonal, annual), and layers that depend on those, are updated as well. Practically this means that a final annual aggregation of the most recent full calendar year can only be produced after the end of February. Likewise, the final monthly aggregation of the most recent calendar months can only be produced 2 full months later. **Citation:** FAO 2018. WaPOR Database Methodology: Level 2. Remote Sensing for Water Productivity Technical Report: Methodology Series. Rome, FAO. 72 pages. Licence: CC-BY-4.0 **Contact points:** Metadata Contact: [WaPOR](mailto:wapor@fao.org) Resource Contact: [WaPOR](mailto:wapor@fao.org) **Data lineage:** See transpiration (T) by dekad for further information. The annual total is obtained by taking the T in mm/day, multiplying by the number of days in a dekad, and summing the dekads of each year. Until December 2019 the base input layers (NDVI, albedo, and fAPAR) for the Level 2 (100m) products were derived from the Proba-V satellite. Proba-V was decommissioned in June 2020. From January 2020 onwards the base input layers of NDVI, albedo and fAPAR for level 2 are derived from the Copernicus Sentinel-2 mission. **Resource constraints:** Creative Commons Attribution 4.0 International (CC-BY-4.0) **Online resources:** Download the data from Google Cloud Storage
The evaporation (E) data component (dekadal, in mm/day) is the actual evaporation of the soil surface. The value of each pixel represents the average daily actual evaporation for that specific dekad. The data is provided from January 2009 to 2023. **Data publication:** 2020-01-01 **Supplemental Information:** No data value: 255 Unit: mm Scale Factor: 0.1 Map code: L2-E-D Conversion factor: the pixel value in the downloaded data must be multiplied by 0.1 New dekadal data layers are released approximately 5 days after the end of a dekad. A higher quality version of the same data layer is uploaded after 6 dekads have passed. This final version of the dekadal dataset has a higher quality because gap filling and interpolation processes, where needed, have been based on more data observations. **Citation:** FAO 2018. WaPOR Database Methodology: Level 2. Remote Sensing for Water Productivity Technical Report: Methodology Series. Rome, FAO. 72 pages. Licence: CC-BY-4.0 **Contact points:** Metadata Contact: [WaPOR](mailto:wapor@fao.org) Resource Contact: [WaPOR](mailto:wapor@fao.org) **Data lineage:** The calculation of the evaporation is based on the ETLook model described in Bastiaanssen et al. (2012). It uses the Penman-Monteith equation, adapted to remote sensing input data. The Penman-Monteith equation predicts the rate of total evaporation and transpiration using commonly measured meteorological data (solar radiation, air temperature, vapour content and wind speed). It has become the FAO standard for calculating the actual and reference evapotranspiration (see FAO Irrigation and Drainage paper 56, Allen et al. 1998). The following data is used for calculating evaporation: - Daily: incoming solar radiation and weather data (temperature, humidity, wind speed and precipitation); - Dekadal: NDVI, surface albedo and soil moisture stress; - Seasonal: Land Cover; - Static: Digital Elevation Model. Data component developed through collaboration with the FRAME Consortium. More information can be found at: http://www.fao.org/in-action/remote-sensing-for-water-productivity/en/. Until December 2019 the base input layers (NDVI, albedo, and fAPAR) for the Level 2 (100m) products were derived from the Proba-V satellite. Proba-V was decommissioned in June 2020. From January 2020 onwards the base input layers of NDVI, albedo and fAPAR for level 2 are derived from the Copernicus Sentinel-2 mission. **Resource constraints:** Creative Commons Attribution 4.0 International (CC-BY-4.0) **Online resources:** Download the data from Google Cloud Storage
The evaporation (E) data component is the actual evaporation of the soil surface. The value of each pixel represents the total annual evaporation for that specific year. The data is provided from January 2009 to 2023. **Data publication:** 2020-01-01 **Supplemental Information:** No data value: -9999 Unit: mm Scale Factor: 0.1 Map code: L2-E-A Conversion factor: the pixel value in the downloaded data must be multiplied by 0.1 New dekadal data layers are released approximately 5 days after the end of a dekad. A higher quality version of the same data layer is uploaded after 6 dekads have passed. This final version of the dekadal dataset has a higher quality because gap filling and interpolation processes, where needed, have been based on more data observations. This implies that other temporal aggregations (monthly, seasonal, annual), and layers that depend on those, are updated as well. Practically this means that a final annual aggregation of the most recent full calendar year can only be produced after the end of February. Likewise, the final monthly aggregation of the most recent calendar months can only be produced 2 full months later. **Citation:** FAO 2018. WaPOR Database Methodology: Level 2. Remote Sensing for Water Productivity Technical Report: Methodology Series. Rome, FAO. 72 pages. Licence: CC-BY-4.0 **Contact points:** Metadata Contact: [WaPOR](mailto:wapor@fao.org) Resource Contact: [WaPOR](mailto:wapor@fao.org) **Data lineage:** See evaporation (E) by dekad for further information. The annual total is obtained by taking the E in mm/day, multiplying by the number of days in a dekad, and summing the dekads of each year. Until December 2019 the base input layers (NDVI, albedo, and fAPAR) for the Level 2 (100m) products were derived from the Proba-V satellite. Proba-V was decommissioned in June 2020. From January 2020 onwards the base input layers of NDVI, albedo and fAPAR for level 2 are derived from the Copernicus Sentinel-2 mission. **Resource constraints:** Creative Commons Attribution 4.0 International (CC-BY-4.0) **Online resources:** Download the data from Google Cloud Storage
The actual evapotranspiration and interception (ETIa) is the sum of the soil evaporation (E), canopy transpiration (T), and evaporation from rainfall intercepted by leaves (I). The value of each pixel represents the average daily ETIa in a given dekad. The data is provided from January 2009 to 2023. **Data publication:** 2020-01-01 **Supplemental Information:** No data value: -9999 Unit: mm Scale Factor : 0.1 Map code : L2-AETI-D Conversion factor: the pixel value in the downloaded data must be multiplied by 0.1 New dekadal data layers are released approximately 5 days after the end of a dekad. A higher quality version of the same data layer is uploaded after 6 dekads have passed. This final version of the dekadal dataset has a higher quality because gap filling and interpolation processes, where needed, have been based on more data observations. **Citation:** FAO 2018. WaPOR Database Methodology: Level 2. Remote Sensing for Water Productivity Technical Report: Methodology Series. Rome, FAO. 72 pages. Licence: CC-BY-4.0 **Contact points:** Metadata Contact: [WaPOR](mailto:wapor@fao.org) Resource Contact: [WaPOR](mailto:wapor@fao.org) **Data lineage:** The calculation of the ETIa is based on the ETLook model described in Bastiaanssen et al. (2012). See the methodology of the three components (E, T and I) for further information. Until December 2019 the base input layers (NDVI, albedo, and fAPAR) for the Level 2 (100m) products were derived from the Proba-V satellite. Proba-V was decommissioned in June 2020. From January 2020 onwards the base input layers of NDVI, albedo and fAPAR for level 2 are derived from the Copernicus Sentinel-2 mission. **Resource constraints:** Creative Commons Attribution 4.0 International (CC-BY-4.0) **Online resources:** Download the data from Google Cloud Storage
The actual evapotranspiration and interception (ETIa) is the sum of the soil evaporation (E), canopy transpiration (T), and evaporation from rainfall intercepted by leaves (I). The value of each pixel represents the ETIa in a given year. The data is provided from January 2009 to 2023. **Data publication:** 2020-01-01 **Supplemental Information:** No data value: -9999 Unit: mm Scale Factor : 0.1 Map code : L2-AETI-A Conversion factor: the pixel value in the downloaded data must be multiplied by 0.1 New dekadal data layers are released approximately 5 days after the end of a dekad. A higher quality version of the same data layer is uploaded after 6 dekads have passed. This final version of the dekadal dataset has a higher quality because gap filling and interpolation processes, where needed, have been based on more data observations. This implies that other temporal aggregations (monthly, seasonal, annual), and layers that depend on those, are updated as well. Practically this means that a final annual aggregation of the most recent full calendar year can only be produced after the end of February. Likewise, the final monthly aggregation of the most recent calendar months can only be produced 2 full months later. **Citation:** FAO 2018. WaPOR Database Methodology: Level 2. Remote Sensing for Water Productivity Technical Report: Methodology Series. Rome, FAO. 72 pages. Licence: CC-BY 4.0 **Contact points:** Metadata Contact: [WaPOR](mailto:wapor@fao.org) Resource Contact: [WaPOR](mailto:wapor@fao.org) **Data lineage:** See ETIa by dekad for further information. The annual total is obtained by taking the ETIa in mm/day, multiplying by the number of days in a dekad, and summing the dekads of each year. Until December 2019 the base input layers (NDVI, albedo, and fAPAR) for the Level 2 (100m) products were derived from the Proba-V satellite. Proba-V was decommissioned in June 2020. From January 2020 onwards the base input layers of NDVI, albedo and fAPAR for level 2 are derived from the Copernicus Sentinel-2 mission. **Resource constraints:** Creative Commons Attribution 4.0 International (CC-BY-4.0) **Online resources:** Download the data from Google Cloud Storage
Shapefile of inland water bodies in Africa. This dataset originates from the Digital Chart of the World 1:1000000, 1998. The waterbodies for Africa have been characterized (as lake, lagoon, reservoir etc.) and named (if the names were easily available). The data layer contains all the waterbodies that had a name and were not characterized as river. **Data creation:** 2002-05-31 **Supplemental Information:** For a wider distribution and to support other projects at FAO this map is also distributed in a DVD as part of a publication entitled: "Jenness, J.; Dooley, J.; Aguilar-Manjarrez, J.; Riva, C. African Water Resource Database. GIS-based tools for inland aquatic resource management. 2. Technical manual and workbook. CIFA Technical Paper. No. 33, Part 2. Rome, FAO. 2007. 308 p." **Contact points:** Resource Contact: [Jippe Hoogeveen](mailto:Jippe.Hoogeveen@fao.org) Metadata Contact: [AQUASTAT](mailto:aquastat@fao.org) **Data lineage:** The dataset consists of the following information: - GIS generated codes (FID, AF_WTR_ID);- Area of the waterbody (SQKM);- Name of waterbody (NAME_OF_WA);- Type of waterbody (TYP_OF_WA). **Resource constraints:** This work is made available under the Creative Commons Attribution 4.0 International licence (CC-BY-4.0) **Online resources:** Download - Water bodies of Africa (ESRI shapefile)
The rivers dataset, 2026 edition, is derived from HydroRIVERS line layers, which represent a subset of the HydroSHEDS database based on the 15 arc-second Digital Elevation Model (DEM) from NASA's Shuttle Radar Topography Mission (SRTM). The HydroRIVERS source data, developed on behalf of World Wildlife Fund US (WWF), Washington, DC, USA, in collaboration with McGill University, Montreal, Canada, represents a vectorized line network of all global rivers that have a catchment area of at least 10 km² or an average river flow of at least 0.1 m³/sec, or both. More information at https://www.hydrosheds.org/products/hydrorivers The present dataset additionally incorporates a perennial/intermittent flow-regime classification (from 1 to 6) derived from HydroATLAS indicators and applied to the HydroRIVERS network. The classification distinguishes perennial and intermittent rivers reaches using climatic (Upstream aridity index: ari_ix_uav), hydrological (Minimum monthly discharge: dis_m3_pmn), and topological (Stream flow order: ORD_FLOW) indicators and has been further refined through network-topology smoothing to improve spatial consistency. Other key attributes include: - HYRIV_ID: unique identifier for each river reach; - NEXT_DOWN: identifier of the next downstream reach, supporting network connectivity analyses; - ORD_FLOW: river flow order based on discharge classes; - LENGTH_KM: reach length (km); - DIST_UP_KM and DIST_DN_KM: distance to source and outlet, respectively; - UPLAND_SKM: total upstream drainage area (km²); - CATCH_SKM: local catchment area (km²); - DIS_AV_CMS: long-term average discharge (m³/s). **Data publication:** 2026-06-15 **Supplemental Information:** This dataset is developed as part of a GIS-based information system on water resources. It has been published in the framework of the AQUASTAT - programme of the Land and Water Division of the Food and Agriculture Organization of the United Nations. **Contact points:** Resource Contact: [Jippe Hoogeveen](mailto:jippe.hoogeveen@fao.org) Resource Contact: [Livia Peiser](mailto:livia.peiser@fao.org) Metadata Contact: [AQUASTAT](mailto:aquastat@fao.org) **Data lineage:** For further technical details on data lineage, please refer to the HydRiver Classification report **Resource constraints:** This work is made available under the Creative Commons Attribution 4.0 International licence (CC-BY-4.0) **Online resources:** HydRiver_Phase4_Technical_Report
“Oil and gas concessions” refer to areas allocated by the government to companies who explore for and produce oil, natural gas and other hydrocarbons. The terminology for these areas varies from country to country. “Concession” is used as a general term for licenses, permits, or other contracts that confer rights to private companies to manage and extract oil and natural gas from public lands; terminology varies at the national level, however, and includes mining or mining “permits,” “tenures,” “licenses,” and other terms. This data set displays oil and gas concessions as a single layer assembled by aggregating concession data for multiple countries. The data may come from government agencies, NGOs, or other organizations and varies by date and source. Only active or available concessions are included in this layer. Inactive or expired concessions are excluded as defined by the dataset source. As available, additional data source information is linked below: - Brazil - Colombia - Democratic Republic of the Congo - Ecuador - Peru If you are aware of concession data for additional countries, please email us [here](mailto:gnw@wri.org). Displays boundaries of areas allocated by governments to companies for the exploration of oil, gas, and other hydrocarbons.
Annual freshwater withdrawals refer to total water withdrawals, not counting evaporation losses from storage basins. Withdrawals also include water from desalination plants in countries where they are a significant source. Withdrawals can exceed 100 percent of total renewable resources where extraction from nonrenewable aquifers or desalination plants is considerable or where there is significant water reuse. Withdrawals for agriculture and industry are total withdrawals for irrigation and livestock production and for direct industrial use (including withdrawals for cooling thermoelectric plants). Withdrawals for domestic uses include drinking water, municipal use or supply, and use for public services, commercial establishments, and homes. Data are for the most recent year available for 1987-2002.