A multi-scale and multi-model gridded framework for forecasting crop production, risk analysis, and climate change impact studies
Regional crop production forecasting is growing in importance in both, the public and private sectors to ensure food security, optimize agricultural management practices and use of resources, and anticipate market fluctuations. Thus, a model and data driven, easy-to-use forecasting and a risk assess...
| Autores principales: | , , , , , , |
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| Formato: | Journal Article |
| Lenguaje: | Inglés |
| Publicado: |
Elsevier
2019
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| Materias: | |
| Acceso en línea: | https://hdl.handle.net/10568/99697 |
| _version_ | 1855514611794575360 |
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| author | Vakhtang, Shelia Hansen, James Sharda, Vaishali Porter, Cheryl Aggarwal, Pramod K. Wilkerson, Carol J Hoogenboom, Gerrit |
| author_browse | Aggarwal, Pramod K. Hansen, James Hoogenboom, Gerrit Porter, Cheryl Sharda, Vaishali Vakhtang, Shelia Wilkerson, Carol J |
| author_facet | Vakhtang, Shelia Hansen, James Sharda, Vaishali Porter, Cheryl Aggarwal, Pramod K. Wilkerson, Carol J Hoogenboom, Gerrit |
| author_sort | Vakhtang, Shelia |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | Regional crop production forecasting is growing in importance in both, the public and private sectors to ensure food security, optimize agricultural management practices and use of resources, and anticipate market fluctuations. Thus, a model and data driven, easy-to-use forecasting and a risk assessment system can be an essential tool for end-users at different levels. This paper provides an overview of the approaches, algorithms, design, and capabilities of the CCAFS Regional Agricultural Forecasting Toolbox (CRAFT) for gridded crop modeling and yield forecasting along with risk analysis and climate impact studies. CRAFT is a flexible and adaptable software platform designed with a user-friendly interface to produce multiple simulation scenarios, maps, and interactive visualizations using a crop engine that can run the pre-installed crop models DSSAT, APSIM, and SARRA-H, in concert with the Climate Predictability Tool (CPT) for seasonal climate forecasts. Its integrated and modular design allows for easy adaptation of the system to different regional and scientific domains. CRAFT requires gridded input data to run the crop simulations on spatial scales of 5 and 30 arc-minutes. Case studies for South Asia for two crops, including wheat and rice, shows its potential application for risk assessment and in-season yield forecasting. |
| format | Journal Article |
| id | CGSpace99697 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2019 |
| publishDateRange | 2019 |
| publishDateSort | 2019 |
| publisher | Elsevier |
| publisherStr | Elsevier |
| record_format | dspace |
| spelling | CGSpace996972023-12-08T19:36:04Z A multi-scale and multi-model gridded framework for forecasting crop production, risk analysis, and climate change impact studies Vakhtang, Shelia Hansen, James Sharda, Vaishali Porter, Cheryl Aggarwal, Pramod K. Wilkerson, Carol J Hoogenboom, Gerrit climate change agriculture food security environmental engineering software Regional crop production forecasting is growing in importance in both, the public and private sectors to ensure food security, optimize agricultural management practices and use of resources, and anticipate market fluctuations. Thus, a model and data driven, easy-to-use forecasting and a risk assessment system can be an essential tool for end-users at different levels. This paper provides an overview of the approaches, algorithms, design, and capabilities of the CCAFS Regional Agricultural Forecasting Toolbox (CRAFT) for gridded crop modeling and yield forecasting along with risk analysis and climate impact studies. CRAFT is a flexible and adaptable software platform designed with a user-friendly interface to produce multiple simulation scenarios, maps, and interactive visualizations using a crop engine that can run the pre-installed crop models DSSAT, APSIM, and SARRA-H, in concert with the Climate Predictability Tool (CPT) for seasonal climate forecasts. Its integrated and modular design allows for easy adaptation of the system to different regional and scientific domains. CRAFT requires gridded input data to run the crop simulations on spatial scales of 5 and 30 arc-minutes. Case studies for South Asia for two crops, including wheat and rice, shows its potential application for risk assessment and in-season yield forecasting. 2019-05 2019-02-26T14:30:01Z 2019-02-26T14:30:01Z Journal Article https://hdl.handle.net/10568/99697 en Open Access Elsevier Vakhtang S, Hansen J, Sharda V, Porter C, Aggarwal P, Wilkerson CJ, Hoogenboom G. 2019. A multi-scale and multi-model gridded framework for forecasting crop production, risk analysis, and climate change impact studies. Environmental Modelling and Software 115: 144-154. |
| spellingShingle | climate change agriculture food security environmental engineering software Vakhtang, Shelia Hansen, James Sharda, Vaishali Porter, Cheryl Aggarwal, Pramod K. Wilkerson, Carol J Hoogenboom, Gerrit A multi-scale and multi-model gridded framework for forecasting crop production, risk analysis, and climate change impact studies |
| title | A multi-scale and multi-model gridded framework for forecasting crop production, risk analysis, and climate change impact studies |
| title_full | A multi-scale and multi-model gridded framework for forecasting crop production, risk analysis, and climate change impact studies |
| title_fullStr | A multi-scale and multi-model gridded framework for forecasting crop production, risk analysis, and climate change impact studies |
| title_full_unstemmed | A multi-scale and multi-model gridded framework for forecasting crop production, risk analysis, and climate change impact studies |
| title_short | A multi-scale and multi-model gridded framework for forecasting crop production, risk analysis, and climate change impact studies |
| title_sort | multi scale and multi model gridded framework for forecasting crop production risk analysis and climate change impact studies |
| topic | climate change agriculture food security environmental engineering software |
| url | https://hdl.handle.net/10568/99697 |
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