Climate Information Systems (CIS) for Aquaculture: Development of a Temperature-Based Early Warning Alert System for Fish Farmers in Zambia
This paper presents a temperature-based early warning alert system for fish farmers in Zambia. The decision support tool indicating the conditions under which air temperatures may result in a normal, high risk or emergency scenario, combined with the monitoring and management mitigations recommended...
| Autores principales: | , , , , , , , , , , |
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| Formato: | Ponencia |
| Publicado: |
Accelerating Impacts of CGIAR Climate Research for Africa
2023
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| Materias: | |
| Acceso en línea: | https://hdl.handle.net/10568/137805 |
| _version_ | 1855517192499494912 |
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| author | Stander, Henk Greengrass, Catherine Oladejo, Sunday Watson, Bruce Nel, Aldi Salie, Khalid Mudege, Netsayi N. Kakwasha, Keagan Lundeba, Mary Hossain, Rumana Peerzadi Siamudaala, Victor |
| author_browse | Greengrass, Catherine Hossain, Rumana Peerzadi Kakwasha, Keagan Lundeba, Mary Mudege, Netsayi N. Nel, Aldi Oladejo, Sunday Salie, Khalid Siamudaala, Victor Stander, Henk Watson, Bruce |
| author_facet | Stander, Henk Greengrass, Catherine Oladejo, Sunday Watson, Bruce Nel, Aldi Salie, Khalid Mudege, Netsayi N. Kakwasha, Keagan Lundeba, Mary Hossain, Rumana Peerzadi Siamudaala, Victor |
| author_sort | Stander, Henk |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | This paper presents a temperature-based early warning alert system for fish farmers in Zambia. The decision support tool indicating the conditions under which air temperatures may result in a normal, high risk or emergency scenario, combined with the monitoring and management mitigations recommended under each scenario. During model development, five models were compared, including linear regression, stochastic regression, deep learning, random forest, and decision tree. The data was modelled for a pond designed according to best aquaculture practices, and therefore, pond size and pond depth are constants. |
| format | Ponencia |
| id | CGSpace137805 |
| institution | CGIAR Consortium |
| publishDate | 2023 |
| publishDateRange | 2023 |
| publishDateSort | 2023 |
| publisher | Accelerating Impacts of CGIAR Climate Research for Africa |
| publisherStr | Accelerating Impacts of CGIAR Climate Research for Africa |
| record_format | dspace |
| spelling | CGSpace1378052025-11-11T16:46:12Z Climate Information Systems (CIS) for Aquaculture: Development of a Temperature-Based Early Warning Alert System for Fish Farmers in Zambia Stander, Henk Greengrass, Catherine Oladejo, Sunday Watson, Bruce Nel, Aldi Salie, Khalid Mudege, Netsayi N. Kakwasha, Keagan Lundeba, Mary Hossain, Rumana Peerzadi Siamudaala, Victor aquaculture agriculture climate information services This paper presents a temperature-based early warning alert system for fish farmers in Zambia. The decision support tool indicating the conditions under which air temperatures may result in a normal, high risk or emergency scenario, combined with the monitoring and management mitigations recommended under each scenario. During model development, five models were compared, including linear regression, stochastic regression, deep learning, random forest, and decision tree. The data was modelled for a pond designed according to best aquaculture practices, and therefore, pond size and pond depth are constants. 2023-11 2024-01-16T18:35:19Z 2024-01-16T18:35:19Z Presentation https://hdl.handle.net/10568/137805 Open Access application/pdf Accelerating Impacts of CGIAR Climate Research for Africa Stander H, Greengrass C, Oladejo S, Watson B, Nel A, Salie K, Mudege NN, Kakwasha K, Lundeba M, Hossain RP, Siamudaala V. 2023. Climate Information Systems (CIS) for Aquaculture: Development of a Temperature-Based Early Warning Alert System for Fish Farmers in Zambia. AICCRA Presentation. Accelerating Impacts of CGIAR Climate Research for Africa (AICCRA). |
| spellingShingle | aquaculture agriculture climate information services Stander, Henk Greengrass, Catherine Oladejo, Sunday Watson, Bruce Nel, Aldi Salie, Khalid Mudege, Netsayi N. Kakwasha, Keagan Lundeba, Mary Hossain, Rumana Peerzadi Siamudaala, Victor Climate Information Systems (CIS) for Aquaculture: Development of a Temperature-Based Early Warning Alert System for Fish Farmers in Zambia |
| title | Climate Information Systems (CIS) for Aquaculture: Development of a Temperature-Based Early Warning Alert System for Fish Farmers in Zambia |
| title_full | Climate Information Systems (CIS) for Aquaculture: Development of a Temperature-Based Early Warning Alert System for Fish Farmers in Zambia |
| title_fullStr | Climate Information Systems (CIS) for Aquaculture: Development of a Temperature-Based Early Warning Alert System for Fish Farmers in Zambia |
| title_full_unstemmed | Climate Information Systems (CIS) for Aquaculture: Development of a Temperature-Based Early Warning Alert System for Fish Farmers in Zambia |
| title_short | Climate Information Systems (CIS) for Aquaculture: Development of a Temperature-Based Early Warning Alert System for Fish Farmers in Zambia |
| title_sort | climate information systems cis for aquaculture development of a temperature based early warning alert system for fish farmers in zambia |
| topic | aquaculture agriculture climate information services |
| url | https://hdl.handle.net/10568/137805 |
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