Kenya water data

Line features representing rivers in Kenya, with a name field that is null in the sample. Published by Orion Terrametrics.

Rivers, streams and drainage network of Kenya showing the extent and hierarchy of surface water features. Use this layer for watershed analysis, flood modelling, irrigation planning, water resource mapping, and environmental impact assessment.

Records flood extent and affected populations by district in Kenya, with each row representing an administrative district such as Laisamis, Lagdera or Wajir South. Columns give total flooded area, flooded cropland, total population, and counts of directly affected people, children and elderly. Published by Orion Terrametrics.

Water resources and water infrastructure in Kenya including rivers, lakes, boreholes, wells and water points. Use this layer for water access analysis, WASH programme planning, drought monitoring, flood risk assessment, and water resource management.

**UNOSAT code FL20230321KEN** This map illustrates satellite detected surface waters in Dagahaley Refugee Camp, Dadaab sub-county, Garissa county, Kenya as observed from a Sentinel-2 image acquired on 26 March 2023 at 07:49 UTC. Within the analyzed area of about 45 km2, about 8 km2 of lands appear to be flooded. Based on Worldpop population data and the detected surface waters in the analyzed area, 8600 people are potentially exposed or living close to flooded areas. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to United Nations Satellite Centre (UNOSAT).

**UNOSAT code FL20230321KEN** Status: Increased water extent observed Further action(s): continue monitoring Summary of findings: Increased water observed along Lagh Dera River in the vicinity of Dagahaley Refugee Camp as of 21 March 2023; Cloud cover over Dagahaley and Ifo Refugee Camp as of 21 March 2023; Potentially flooded areas observed in Dadaab town as of 21 March 2023; Increased water in the whole river basin observed around the Dadaab Refugee Complex as of 21 March 2023.

This map illustrates satellite-detected flood water extent over Dadaab & Lagdera Sub Counties, Garissa County, Kenya. The analysis was conducted analyzing Sentinel-1 image acquired on the 4 May 2018. Within the analysis extent, ~ 43,300 ha of land appear to be inundated and around 23,000 people are living inside this flood water extent. Within the analysis extent, around 23,300 ha of inundated land are located inside Dabaad Sub County, potentially affecting 18,200 people. Several refugee camps, specially the ones located inside Dadaab Sub County, seem to be affected by the floods, being Ifo 2 Refugee Camp the most affected one. It is likely that flood waters have been systematically underestimated along highly vegetated areas along main river banks and within built-up urban areas because of the special characteristics of the satellite data used. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR UNOSAT.

This map illustrates satellite-detected flood water extent along Tana River, Galole and Garsen sub counties, Tana River county, Kenya. The analysis was conducted by analyzing Sentinel-1 imagery acquired on the 4 May 2018. The analysis extent is focused on the river bed of Tana, the surrounding land between the primary road and the limit of the Tana River boundary, specifically where the population is concentrated. Within the analysis extent, around 22,700 ha of land appears to be inundated and more than 21,600 people are living inside this flood water extent. It is likely that flood waters have been systematically underestimated along highly vegetated areas along main river banks and within built-up urban areas because of the special characteristics of the satellite data used. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR UNOSAT.

This map illustrates satellite-detected flood water extent along Tana River, Bura Sub County, Kenya. The analysis was conducted analyzing Sentinel-1 image acquired on the 4 May 2018. The analysis extent is focused on the river bed of Tana and the surrounding land between the primary road and the limit of the Tana River boundary, specifically were the population is concentrated. Within the analysis extent, more than 9,100 ha of land appear to be inundated and more than 9,800 people are living inside this flood water extent. It is likely that flood waters have been systematically underestimated along highly vegetated areas along main river banks and within built-up urban areas because of the special characteristics of the satellite data used. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR UNOSAT.

This map illustrates satellite-detected flood water extent over Garsen, Magarini, Malindi and Lamu West Sub Counties, Kenya. The analysis was conducted analyzing Sentinel-1 image acquired on the 4 May 2018. Within the extent of the map more than 25,000 ha of land appear to be inundated and around 20,000 people are living inside this flood water extent. Within the map extent, around 13,000 ha of inundated land are located inside Garsen sub county, potentially affecting 5,000 people. It is likely that flood waters have been systematically underestimated along highly vegetated areas along main river banks and within built-up urban areas because of the special characteristics of the satellite data used. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR UNOSAT.

This map illustrates potentially affected population by flooding in the eastern sub counties of Kenya. The analysis was conducted by analyzing Sentinel-1 imagery acquired on the 4 May 2018. Within the analysis extent, more than 200,000 people are potentially affected by the floods. Magarini sub county in Kilifi County, is the one with more than 40,000 people living inside flood affected areas, followed by Dadaab, Wajir South, Garsen and Malindi sub counties. Note that some sub counties have been partially analyzed depending on the area covered by satellite imagery. It is likely that flood waters have been systematically underestimated along highly vegetated areas, along main river banks and within built-up urban areas because of the special characteristics of the satellite data used. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR UNOSAT.

This map illustrates satellite-detected flood water extent over Wajir county, Kenya. The analysis was conducted by analyzing Sentinel-1 imagery acquired on the 4 May 2018. Within the analysis extent, around 111,800 ha of land appears to be inundated and more than 46,300 people are living inside this flood water extent.Within the analysis extent, the sub county of Wajir West presents 68,000 ha of land inundated and more than 6,100 people potentially affected while Wajir South presents ~ 26,300 ha of land inundated and ~ 19,000 people potentially affected. It is likely that flood waters have been systematically underestimated along highly vegetated areas along main river banks and within built-up urban areas because of the special characteristics of the satellite data used. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR UNOSAT.

**UNOSAT code: FL20240426KEN** This map illustrates cumulative satellite-detected water using NOAA-VIIRS acquired between the 24th and the 28th of April 2024. about 3,800 km² of land appear to be flooded. Based on Worldpop population data from 2020 and the flood water extent, ~190,000 people are potentially exposed or living close to flooded areas. 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). Important note: Population data used for this estimate is from 2020. Current population count is not available.

Water features across the area: rivers, streams, canals, lakes, ponds, and water bodies tagged with `waterway`, `water`, or `natural=water`. Useful for flood-risk modelling, watershed analysis, and environmental basemap context. Coverage reflects where volunteer mappers have been active. Urban areas are usually well represented, remote areas may be sparse. Cross-check critical decisions with local field knowledge. - Source: OpenStreetMap, a free, collaborative world map - Tags: waterway, water, natural - Part of the country exports on HDX by HOT

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 in near real time from January 2009 to 2022. **Data publication:** 2020-01-01 **Supplemental Information:** No data value: -9999 Unit: mm Scale Factor : 0.1 Map code : L3-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 3. 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 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 in near real time from January 2009 to 2022. **Data publication:** 2020-01-01 **Supplemental Information:** No data value: -9999 Unit: mm Scale Factor : 0.1 Map code : L3-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 3. 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 in near real time from January 2009 to 2023. **Data publication:** 2020-01-01 **Supplemental Information:** No data value: 255 Unit: mm Scale Factor : 0.1 Map code : L3-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 3. 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/ **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 in near real time from January 2009 to 2023. **Data publication:** 2020-01-01 **Supplemental Information:** No data value: -9999 Unit: mm Scale Factor : 0.1 Map code : L3-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 3. 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 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 in near real time from January 2009 to 2023. **Data publication:** 2020-01-01 **Supplemental Information:** No data value: -9999 Unit: mm Scale Factor : 0.1 Map code : L3-AETI-M 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 3. 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 monthly 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 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 in near real time from January 2009 to 2023. **Data publication:** 2020-01-01 **Supplemental Information:** No data value: 255 Unit: mm Scale Factor : 0.1 Map code : L3-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 3. 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/ **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 in near real time from January 2009 to 2022. **Data publication:** 2020-01-01 **Supplemental Information:** No data value: -9999 Unit: mm Scale Factor : 0.1 Map code : L3-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 3. 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. **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 in near real time from January 2009 to 2023. **Data publication:** 2020-01-01 **Supplemental Information:** No data value: 255 Unit: mm Scale Factor : 0.1 Map code : L3-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 3. 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/ **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 in near real time from January 2009 to 2022. **Data publication:** 2020-01-01 **Supplemental Information:** No data value: -9999 Unit: mm Scale Factor : 0.1 Map code : L3-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 3. 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. **Resource constraints:** Creative Commons Attribution 4.0 International (CC-BY-4.0) **Online resources:** Download the data from Google Cloud Storage