345-17 Ccafs Regional Agricultural Forecasting Toolbox (CRAFT).

Poster Number 200

See more from this Division: Special Sessions
See more from this Session: AgMIP Poster Session
Wednesday, November 5, 2014
Long Beach Convention Center, Exhibit Hall ABC
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Vakhtang Shelia1, James W. Hansen2, Pramod Aggarwal3, Vaishali Sharda4, Premal Mehta5, Kavita Pandey5, Vipin Soni5 and Gerrit Hoogenboom6, (1)AgWeatherNet, Washington State University, Prosser, WA
(2)International Research Institute for Climate and Society, Palisades, NY
(3)CGIAR, Delhi, India
(4)AgWeatherNet, Prosser, WA
(5)ARC, Delhi, India
(6)Washington State University, Prosser, WA
The CGIAR Research Program on Climate Change, Agriculture and Food Security(CCAFS) has initiated the development of a new personal computer-based decision support system for short-term and long-term yield forecasting, agricultural risk analysis associated with increasing extreme events and climate change impact  studies. The CCAFS Regional Agricultural Forecasting Toolbox(CRAFT) includes the client application with a user-friendly interface and the database implementation. It is designed to use gridded data schemes for spatial variability through the use of 5 and 30 arc minutes resolution grids. Using schematization three levels at different spatial scales are considered at a country, state/province and district level. For the simulations it uses gridded data for weather , soil conditions, cultivar and other management levels. The corresponding datasets  must be prepared using ArcGIS and imported into the database. CRAFT is integrated with external engines; one for crop modeling for spatial crop simulations and one for seasonal climate forecasts using the Climate Predictability Tool(CPT) developed by the International Research Institute for Climate and Society(IRI). This allows for the  support of multi crop model capabilities using the AgMIP approach. Currently the Cropping System Model(CSM) of DSSAT has been implemented while APSIM is under development. There are plans for incorporating the InfoCrop and SARRA-H models. CRAFT simulates yield for each grid cell based on the predefined inputs and using statistical forecasting based on the seasonal predictors yields are adjusted. Through spatial aggregation and probabilistic analysis of the forecast uncertainty for both short-term and long-term periods predicted yield can be determined for a region at different spatial resolutions. CRAFT includes hindcast analysis, de-trending and post-simulation calibration of model predictions from historic agricultural statistics. Analyses of the simulation results can be conducted through comparing different scenarios, reviewing the output statistics and visualization with thematic maps. Several case studies conducted by CCAFS stakeholders are promising.
See more from this Division: Special Sessions
See more from this Session: AgMIP Poster Session