Options for digital twin application in developing country river basin management: a review
A Digital Twin (DT) is a digital representation of reality. This report explores the implementation of DT in the context of basin scale water management, with a particular focus on developing countries. The review begins with an examination of the background of DT and then delves into successful app...
| Autores principales: | , , , , , |
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| Formato: | Artículo preliminar |
| Lenguaje: | Inglés |
| Publicado: |
CGIAR Initiative on Digital Innovation
2023
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| Materias: | |
| Acceso en línea: | https://hdl.handle.net/10568/134763 |
| _version_ | 1855542441344499712 |
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| author | Botai, Joel O. Ghosh, Surajit Matheswaran, Karthikeyan Dickens, Chris Langa, Nkateko Garcia Andarcia, Mariangel |
| author_browse | Botai, Joel O. Dickens, Chris Garcia Andarcia, Mariangel Ghosh, Surajit Langa, Nkateko Matheswaran, Karthikeyan |
| author_facet | Botai, Joel O. Ghosh, Surajit Matheswaran, Karthikeyan Dickens, Chris Langa, Nkateko Garcia Andarcia, Mariangel |
| author_sort | Botai, Joel O. |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | A Digital Twin (DT) is a digital representation of reality. This report explores the implementation of DT in the context of basin scale water management, with a particular focus on developing countries. The review begins with an examination of the background of DT and then delves into successful applications of DT particularly in developing nations. It also explores the potential of integrating Virtual Reality (VR) technologies as a part of DT, emphasizing the importance of stakeholder needs assessment for effective deployment. The review highlights the significance of data infrastructure architecture and data governance in the context of Digital Twins. The review concentrates on the published literature and the application of Digital Twins to river basins, emphasizing their role in decision-making at this level and outlining various use cases for water management. Furthermore, it assesses the expected impact of DT through the lens of the Sustainable Development Goals (SDGs). The review concludes by exploring the integration of Artificial Intelligence (AI) in the context of DT for river basins. Overall, this review summarizes the potential benefits and challenges of implementing DT for water management in developing countries. |
| format | Artículo preliminar |
| id | CGSpace134763 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2023 |
| publishDateRange | 2023 |
| publishDateSort | 2023 |
| publisher | CGIAR Initiative on Digital Innovation |
| publisherStr | CGIAR Initiative on Digital Innovation |
| record_format | dspace |
| spelling | CGSpace1347632025-11-07T07:59:44Z Options for digital twin application in developing country river basin management: a review Botai, Joel O. Ghosh, Surajit Matheswaran, Karthikeyan Dickens, Chris Langa, Nkateko Garcia Andarcia, Mariangel digital technology river basin management developing countries artificial intelligence machine learning datasets governance frameworks decision making models water resources water management sustainable development goals water quality environmental flows stakeholders A Digital Twin (DT) is a digital representation of reality. This report explores the implementation of DT in the context of basin scale water management, with a particular focus on developing countries. The review begins with an examination of the background of DT and then delves into successful applications of DT particularly in developing nations. It also explores the potential of integrating Virtual Reality (VR) technologies as a part of DT, emphasizing the importance of stakeholder needs assessment for effective deployment. The review highlights the significance of data infrastructure architecture and data governance in the context of Digital Twins. The review concentrates on the published literature and the application of Digital Twins to river basins, emphasizing their role in decision-making at this level and outlining various use cases for water management. Furthermore, it assesses the expected impact of DT through the lens of the Sustainable Development Goals (SDGs). The review concludes by exploring the integration of Artificial Intelligence (AI) in the context of DT for river basins. Overall, this review summarizes the potential benefits and challenges of implementing DT for water management in developing countries. 2023-11-21 2023-11-28T15:00:31Z 2023-11-28T15:00:31Z Working Paper https://hdl.handle.net/10568/134763 en Open Access application/pdf CGIAR Initiative on Digital Innovation Botai, Joel O.; Ghosh, Surajit; Matheswaran, Karthikeyan; Dickens, Chris; Langa, Nkateko; Garcia Andarcia, Mariangel. 2023. Options for digital twin application in developing country river basin management: a review. Colombo, Sri Lanka: International Water Management Institute (IWMI). CGIAR Initiative on Digital Innovation. 20p. |
| spellingShingle | digital technology river basin management developing countries artificial intelligence machine learning datasets governance frameworks decision making models water resources water management sustainable development goals water quality environmental flows stakeholders Botai, Joel O. Ghosh, Surajit Matheswaran, Karthikeyan Dickens, Chris Langa, Nkateko Garcia Andarcia, Mariangel Options for digital twin application in developing country river basin management: a review |
| title | Options for digital twin application in developing country river basin management: a review |
| title_full | Options for digital twin application in developing country river basin management: a review |
| title_fullStr | Options for digital twin application in developing country river basin management: a review |
| title_full_unstemmed | Options for digital twin application in developing country river basin management: a review |
| title_short | Options for digital twin application in developing country river basin management: a review |
| title_sort | options for digital twin application in developing country river basin management a review |
| topic | digital technology river basin management developing countries artificial intelligence machine learning datasets governance frameworks decision making models water resources water management sustainable development goals water quality environmental flows stakeholders |
| url | https://hdl.handle.net/10568/134763 |
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