AAGW3 - Kindie Tesfaye - Application of Linking Crop Modeling with GIS for Technology Targeting

Transcript

1. Application of Linking Crop Modeling with GIS for Technology Targeting Kindie Tesfaye, Kai Sonder, Uran Chung Africa Agriculture GIS Week 11-15 March 2013 Addis Ababa
2. The issue • Most technologies in agriculture are developed based on site-level experimentation • Need to upscale the technologies to areas of similar nature • CIMMYT is carrying out the Drought Tolerance Maize for Africa (DTMA) Project in 13 countries • Drought to tolerance varieties have been developed through yield trial experiments in ESA. • There is a need to target these DT varieties/ technologies in the 13 project countries
3. Objective to identify potential areas where the newly released variety could perform well
4. Methodology
5. Modeling approach DSSAT Crop Model Site/farm level simulation Site soil Daily site climate Crop Model calibration Model evaluation Evaluated DSSAT model 27 FAO soil groups Crop management Monthly gridded data Regional/global crop productivity under various climate models and technologies Evaluated DSSAT model daily pixel climate Weather generator Crop per MME GIS GIS Model Calibration & Evaluation Spatial modeling Dataase
6. Spatial modeling: DSSAT model Elliott, 2012 Site level Spatial level
7. Model calibration and evaluation • Benchmark variety (SC513 • New DT varieties (CZH0616) • 72 site years for calibration • 96 site years for evaluation • Iterative calibration procedure • DT calibration – Leaf senescence – Root distribution – Temperature thresholds
8. Spatial simulation • SPAM rained area of maize for masking • 5 arc-minute pixels • Simulation runs for 30 years
9. Calibration and evaluation
10. Mean simulated Yield–high input
11. Mean simulated Yield–medium input
12. Yield changes- high input
13. Medium input
14. Concluding Remarks • Well calibrated and evaluated crop models linked with GIS could be useful tools in technology targeting and scenario analysis • Calibration and evaluation of models at high spatial scale is still a challenge and requires cross-institutional and inter-disciplinary collaboration.
15. Thank you!