Introducing IMPACT 3: Modeling Philosophy and Environment

1. Introducing IMPACT 3: Modeling Philosophy and Environment Sherman Robinson Daniel Mason-D’Croz Shahnila Islam

2. Global Futures and IMPACT • Objective: Use IMPACT for ex-ante analysis of potential agricultural technologies to help policy makers prioritize agricultural investments • Phase 1: IMPACT Developments: • Welfare Module • Benefit-Cost Analysis • Technology Adoption Module • Tracking progress against MDGs • Challenges identified in Phase 1: • Insufficient geographic disaggregation • Need to model more CG-mandate crops • 2000 base year outdated • Model needed to be recoded to allow for better integration with new modules under development (water, livestock, fish, biofuels)

3. What is IMPACT 3? • More than a new FAO download and cleaner code • A modeling-data platform built on modularity and interoperability • Harmonized Data • Data drivenmodel specifi-cation • More flexible tomeet user needs

4. Why Data Harmonization? • IMPACT integrates various models, which often use similar input data • Better data sharing, common definitions, and clear responsibility of data processing removes redundancy and improves quality control

5. Why Data Harmonization? • IMPACT integrates various models, which often use similar input data • Better data sharing, common definitions, and clear responsibility of data processing removes redundancy and improves quality control SPAM

6. Why Data Harmonization? • IMPACT integrates various models, which often use similar input data • Better data sharing, common definitions, and clear responsibility of data processing removes redundancy and improves quality control SPAM IMPACT

7. IMPACT Data-Model Environment • FAO • Climate Data • SPAM • IMPACT Models • Geospatial and Subnational Data • Exogenous IMPACT Parameters Land-Use Model • Crop Models • Hydrology

8. Share Data • Geospatial and Subnational Data • Irrigation • Subnational Statistics • Crop suitability maps • Population Density • Exogenous IMPACT Parameters • Yield, Area Growth • Elasticities • Prices (AMAD) • Population • GDP • FAO • Crop Production • Livestock Production • Supply-Utilization • Food Balance Sheets • Water Stress • Climate Data • GCMS • Generated Weather

9. Models • Hydrology Model • Water Basin Management Model • Water Stress Model • Food Model • Crops • Livestock • Sugar • Oilseeds • SPAM - Spatial Production Allocation Model • Land-Use Model • DSSAT Crop Models • Biofuel Model

10. FAO Data

11. Processing FAO Data • FAO Bulk Download for 3-year average around 2005 (04-06) • Harmonized SPAM/IMPACT commodity, and geographic definitions • Bayesian Work Plan • Iterate with new information

12. Data Harmonization and Quality • Too many cooks • Climate change is modeled in Water and Crop models for IMPACT • Need to use same initial and processed climate data • Ensure crop shocks and water shocks are compatible

13. Climate Change Consistency

14. Data Harmonization and Quality • Building common geographical definitions • Standardize mapping of data • Share data (initial and processed)

15. Geospatial Data Users

16. Modularity – Data Partitioning • IMPACT model is now data driven • General code built on specific data structures • Each dataset has unique problems • Detox drivers vs. self-driving car • Data Processingis source-specific • Model Inputs aremodel-specific

17. Modularity – IMPACT Partitioning • IMPACT model is now data driven • General code built on specific data structures • Each dataset has unique problems • Detox drivers vs. self-driving car • Data Processingis source-specific • Model Inputs aremodel-specific

18. Benefits of Data Independence • Cleaner Model Code • Facilitate model transfer and training • Data Processing and Model design are independent tasks • Model can run different data sources and aggregations without modification