State of continental discharge estimation and modelling: challenges and opportunities for Africa
Africa’s diverse climates and sparse hydro-meteorological networks create significant challenges in accurately estimating river discharge. Discharge data are crucial for managing water resources and predicting extremes. Our review assesses the data gap, existing methods, and technologies for river d...
| Autores principales: | , , , , , , , |
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| Formato: | Journal Article |
| Lenguaje: | Inglés |
| Publicado: |
Informa UK Limited
2024
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| Materias: | |
| Acceso en línea: | https://hdl.handle.net/10568/158345 |
| _version_ | 1855537729182367744 |
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| author | Akpoti, Komlavi Mekonnen, Kirubel Leh, Mansoor Owusu, Afua Dembélé, Moctar Tinonetsana, Primrose Seid, Abdulkarim Velpuri, Naga Manohar |
| author_browse | Akpoti, Komlavi Dembélé, Moctar Leh, Mansoor Mekonnen, Kirubel Owusu, Afua Seid, Abdulkarim Tinonetsana, Primrose Velpuri, Naga Manohar |
| author_facet | Akpoti, Komlavi Mekonnen, Kirubel Leh, Mansoor Owusu, Afua Dembélé, Moctar Tinonetsana, Primrose Seid, Abdulkarim Velpuri, Naga Manohar |
| author_sort | Akpoti, Komlavi |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | Africa’s diverse climates and sparse hydro-meteorological networks create significant challenges in accurately estimating river discharge. Discharge data are crucial for managing water resources and predicting extremes. Our review assesses the data gap, existing methods, and technologies for river discharge estimation in Africa. Limited gauging networks on rivers, including in 63 transboundary basins, hinder accurate discharge modelling, affecting resource management and disaster response. Despite the potential of remote sensing, Geographic Information System (GIS), satellite imagery, and machine learning, their large-scale application for river discharge monitoring in Africa is limited. We propose the use of a monitoring system involving local communities in data collection and decision making, supported by global data centres, enhanced regional data sharing, and strengthened transboundary cooperation. For example, incorporating water data products, including discharge data, in data cubes, such as Digital Earth Africa, could improve monitoring. Strategic investments in hydro-meteorological instrumentation are crucial for strengthening climate resilience. |
| format | Journal Article |
| id | CGSpace158345 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2024 |
| publishDateRange | 2024 |
| publishDateSort | 2024 |
| publisher | Informa UK Limited |
| publisherStr | Informa UK Limited |
| record_format | dspace |
| spelling | CGSpace1583452025-10-26T12:57:04Z State of continental discharge estimation and modelling: challenges and opportunities for Africa Akpoti, Komlavi Mekonnen, Kirubel Leh, Mansoor Owusu, Afua Dembélé, Moctar Tinonetsana, Primrose Seid, Abdulkarim Velpuri, Naga Manohar hydrological modelling transboundary waters river basins discharge estimation runoff monitoring remote sensing geographical information systems machine learning satellite imagery citizen science international cooperation climate resilience water resources water management decision making Africa’s diverse climates and sparse hydro-meteorological networks create significant challenges in accurately estimating river discharge. Discharge data are crucial for managing water resources and predicting extremes. Our review assesses the data gap, existing methods, and technologies for river discharge estimation in Africa. Limited gauging networks on rivers, including in 63 transboundary basins, hinder accurate discharge modelling, affecting resource management and disaster response. Despite the potential of remote sensing, Geographic Information System (GIS), satellite imagery, and machine learning, their large-scale application for river discharge monitoring in Africa is limited. We propose the use of a monitoring system involving local communities in data collection and decision making, supported by global data centres, enhanced regional data sharing, and strengthened transboundary cooperation. For example, incorporating water data products, including discharge data, in data cubes, such as Digital Earth Africa, could improve monitoring. Strategic investments in hydro-meteorological instrumentation are crucial for strengthening climate resilience. 2024-11-17 2024-10-31T16:01:58Z 2024-10-31T16:01:58Z Journal Article https://hdl.handle.net/10568/158345 en Open Access Informa UK Limited Akpoti, Komlavi; Mekonnen, Kirubel; Leh, Mansoor; Owusu, Afua; Dembele, Moctar; Tinonetsana, Primrose; Seid, Abdulkarim; Velpuri, Naga Manohar. 2024. State of continental discharge estimation and modelling: challenges and opportunities for Africa. Hydrological Sciences Journal, 69(15):2124-2152. (Special issue: Twenty-first Century Hydrological Challenges and Opportunities in Africa) [doi: https://doi.org/10.1080/02626667.2024.2402938] |
| spellingShingle | hydrological modelling transboundary waters river basins discharge estimation runoff monitoring remote sensing geographical information systems machine learning satellite imagery citizen science international cooperation climate resilience water resources water management decision making Akpoti, Komlavi Mekonnen, Kirubel Leh, Mansoor Owusu, Afua Dembélé, Moctar Tinonetsana, Primrose Seid, Abdulkarim Velpuri, Naga Manohar State of continental discharge estimation and modelling: challenges and opportunities for Africa |
| title | State of continental discharge estimation and modelling: challenges and opportunities for Africa |
| title_full | State of continental discharge estimation and modelling: challenges and opportunities for Africa |
| title_fullStr | State of continental discharge estimation and modelling: challenges and opportunities for Africa |
| title_full_unstemmed | State of continental discharge estimation and modelling: challenges and opportunities for Africa |
| title_short | State of continental discharge estimation and modelling: challenges and opportunities for Africa |
| title_sort | state of continental discharge estimation and modelling challenges and opportunities for africa |
| topic | hydrological modelling transboundary waters river basins discharge estimation runoff monitoring remote sensing geographical information systems machine learning satellite imagery citizen science international cooperation climate resilience water resources water management decision making |
| url | https://hdl.handle.net/10568/158345 |
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