WaterCopilot: a water management AI virtual assistant for the Limpopo River Basin Digital Twin - user guide V0 202410
The Limpopo Digital Twin Water Management AI Virtual Assistant User Guide provides a practical guide for users to effectively navigate WaterCopilot, an AIpowered Copilot developed by the International Water Management Institute (IWMI) in collaboration with Microsoft Research. This guide offers clear...
| Main Authors: | , , , , , , |
|---|---|
| Format: | Informe técnico |
| Language: | Inglés |
| Published: |
International Water Management Institute (IWMI). CGIAR Initiative on Digital Innovation
2024
|
| Subjects: | |
| Online Access: | https://hdl.handle.net/10568/170233 |
| _version_ | 1855519959191388160 |
|---|---|
| author | Vickneswaran, Keerththanan Retief, H. Padilha, R. Dickens, Chris Silva, Paulo Ghosh, Surajit Garcia Andarcia, Mariangel |
| author_browse | Dickens, Chris Garcia Andarcia, Mariangel Ghosh, Surajit Padilha, R. Retief, H. Silva, Paulo Vickneswaran, Keerththanan |
| author_facet | Vickneswaran, Keerththanan Retief, H. Padilha, R. Dickens, Chris Silva, Paulo Ghosh, Surajit Garcia Andarcia, Mariangel |
| author_sort | Vickneswaran, Keerththanan |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | The Limpopo Digital Twin Water Management AI Virtual Assistant User Guide provides a practical guide for users to effectively navigate WaterCopilot, an AIpowered Copilot developed by the International Water Management Institute (IWMI) in collaboration with Microsoft Research. This guide offers clear instructions on using the Copilot to access crucial water-related data for the Limpopo River Basin, including rainfall insights, environmental flow alerts, and water availability.
The guide highlights key features such as a userfriendly interface, multilingual support, and interactive data retrieval, making WaterCopilot accessible to a broad range of users, from researchers and policymakers to individuals with limited technical expertise. It also explains the Copilot’s ability to analyze historical and real-time data, helping users identify patterns and make informed decisions.
In addition, the user guide includes troubleshooting tips and a frequently asked questions (FAQs) section, ensuring a smooth and efficient user experience. By following this guide, users will be empowered to leverage WaterCopilot for sustainable water management within the Limpopo River Basin. |
| format | Informe técnico |
| id | CGSpace170233 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2024 |
| publishDateRange | 2024 |
| publishDateSort | 2024 |
| publisher | International Water Management Institute (IWMI). CGIAR Initiative on Digital Innovation |
| publisherStr | International Water Management Institute (IWMI). CGIAR Initiative on Digital Innovation |
| record_format | dspace |
| spelling | CGSpace1702332025-11-07T08:00:34Z WaterCopilot: a water management AI virtual assistant for the Limpopo River Basin Digital Twin - user guide V0 202410 Vickneswaran, Keerththanan Retief, H. Padilha, R. Dickens, Chris Silva, Paulo Ghosh, Surajit Garcia Andarcia, Mariangel artificial intelligence models water management river basins forecasting The Limpopo Digital Twin Water Management AI Virtual Assistant User Guide provides a practical guide for users to effectively navigate WaterCopilot, an AIpowered Copilot developed by the International Water Management Institute (IWMI) in collaboration with Microsoft Research. This guide offers clear instructions on using the Copilot to access crucial water-related data for the Limpopo River Basin, including rainfall insights, environmental flow alerts, and water availability. The guide highlights key features such as a userfriendly interface, multilingual support, and interactive data retrieval, making WaterCopilot accessible to a broad range of users, from researchers and policymakers to individuals with limited technical expertise. It also explains the Copilot’s ability to analyze historical and real-time data, helping users identify patterns and make informed decisions. In addition, the user guide includes troubleshooting tips and a frequently asked questions (FAQs) section, ensuring a smooth and efficient user experience. By following this guide, users will be empowered to leverage WaterCopilot for sustainable water management within the Limpopo River Basin. 2024-12-30 2025-01-28T14:59:48Z 2025-01-28T14:59:48Z Report https://hdl.handle.net/10568/170233 en Open Access application/pdf International Water Management Institute (IWMI). CGIAR Initiative on Digital Innovation Vickneswaran, K.; Retief, H.; Padilha, R.; Dickens, C.; Silva, P.; Ghosh, S.; Garcia Andarcia, M. 2024. WaterCopilot: a water management AI virtual assistant for the Limpopo River Basin Digital Twin - user guide V0 202410. Colombo, Sri Lanka: International Water Management Institute (IWMI). CGIAR Initiative on Digital Innovation. 10p. |
| spellingShingle | artificial intelligence models water management river basins forecasting Vickneswaran, Keerththanan Retief, H. Padilha, R. Dickens, Chris Silva, Paulo Ghosh, Surajit Garcia Andarcia, Mariangel WaterCopilot: a water management AI virtual assistant for the Limpopo River Basin Digital Twin - user guide V0 202410 |
| title | WaterCopilot: a water management AI virtual assistant for the Limpopo River Basin Digital Twin - user guide V0 202410 |
| title_full | WaterCopilot: a water management AI virtual assistant for the Limpopo River Basin Digital Twin - user guide V0 202410 |
| title_fullStr | WaterCopilot: a water management AI virtual assistant for the Limpopo River Basin Digital Twin - user guide V0 202410 |
| title_full_unstemmed | WaterCopilot: a water management AI virtual assistant for the Limpopo River Basin Digital Twin - user guide V0 202410 |
| title_short | WaterCopilot: a water management AI virtual assistant for the Limpopo River Basin Digital Twin - user guide V0 202410 |
| title_sort | watercopilot a water management ai virtual assistant for the limpopo river basin digital twin user guide v0 202410 |
| topic | artificial intelligence models water management river basins forecasting |
| url | https://hdl.handle.net/10568/170233 |
| work_keys_str_mv | AT vickneswarankeerththanan watercopilotawatermanagementaivirtualassistantforthelimpoporiverbasindigitaltwinuserguidev0202410 AT retiefh watercopilotawatermanagementaivirtualassistantforthelimpoporiverbasindigitaltwinuserguidev0202410 AT padilhar watercopilotawatermanagementaivirtualassistantforthelimpoporiverbasindigitaltwinuserguidev0202410 AT dickenschris watercopilotawatermanagementaivirtualassistantforthelimpoporiverbasindigitaltwinuserguidev0202410 AT silvapaulo watercopilotawatermanagementaivirtualassistantforthelimpoporiverbasindigitaltwinuserguidev0202410 AT ghoshsurajit watercopilotawatermanagementaivirtualassistantforthelimpoporiverbasindigitaltwinuserguidev0202410 AT garciaandarciamariangel watercopilotawatermanagementaivirtualassistantforthelimpoporiverbasindigitaltwinuserguidev0202410 |