3. Why (Ex-Ante) Model for AR?
Better understanding of the current crop
production system’s sustainability
Assess the potential of sustainable
intensification options and their scalability
beyond the study area and baseline survey
data
4. Data without models is chaos.
… but models without data is fantasy!
Source Unknown (but probably a crop modeler)
5. Hey, Jawoo!
We’ve got all these
baseline survey done!
What data do you need
for the modeling stuff?
White et al., 2013. Integrated description of agricultural field
experiments and production: The ICASA Version 2.0 data standards.
Computers and Electronics in Agriculture 96 (2013) 1–12
6. Come on, Jawoo!
That looks like too much
overwhelming! What are
the minimum data you
need?
7. What do we have for Dedza&Ntcheu?
From AR Baseline Survey + Docs + WUR Survey
Site information
Treatments (Innovations)
Soil properties (Dedza: Loamy, Ntcheu: Sandy)
Cropping calendar (Oct – Jan)
From HarvestChoice
Soil profiles
30-year daily weather (1980-2010; 0.5-deg grid)
8. * Simulated using 30-year historical weather data, first 3 years discarded for initialization spin-up, 13 years selected when maize was simulated
9. * Simulated using 30-year historical weather data, first 3 years discarded for initialization spin-up, 13 years selected when maize was simulated
10. * Simulated using 30-year historical weather data, first 3 years discarded for initialization spin-up, 13 years selected when maize was simulated
14. Concluding Remarks
This is just the beginning;
many interesting ex-ante modeling
opportunities/applications ahead!
Constraints analysis (What if…)
Priority setting across innovation
options
Cost-benefit/gross-margin analysis
Climate-smart/proofing
Identifying spaces for scaling-up
15. Thank You
Africa Research in Sustainable Intensification for the Next Generation
africa-rising.net
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