core training presentations- 6 impact data-model philosophy
TRANSCRIPT
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Introducing IMPACT 3: Modeling Philosophy and Environment
Sherman RobinsonDaniel Mason-D’CrozShahnila Islam
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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identified in Phase 1:– Insufficient geographic disaggregation– Need to model more CG-mandate crops– 2000 base year outdated– Model needed to be recoded to allow for better integration with new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)
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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 driven
model specifi-cation
– More flexible tomeet user needs
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• 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
Why Data Harmonization?
IMPACT 3 FAO Database
Data ProcessingSpatial disaggregation Balance Demand, and Trade
with Production
Data CleaningCrop Production Livestock
ProductionCommodity
Demand and Trade
FAO Data CollectionBulk Download
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• 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
Why Data Harmonization?
IMPACT 3 FAO Database
Data ProcessingSpatial disaggregation Balance Demand, and Trade
with Production
Data CleaningCrop Production Livestock
ProductionCommodity
Demand and Trade
FAO Data CollectionBulk Download
SPAM
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• 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
Why Data Harmonization?
IMPACT 3 FAO Database
Data ProcessingSpatial disaggregation Balance Demand, and Trade
with Production
Data CleaningCrop Production Livestock
ProductionCommodity
Demand and Trade
FAO Data CollectionBulk Download
SPAMIMPACT
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Shared Data Data Processing Data Users
FAOClimate
Data
Exogenous IMPACT
Parameters
Geospatial and
Subnational Data
SPAMIMPACT Models
HydrologyCrop
Models
Land-UseModel
IMPACT Data-Model Environment
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• FAO– Crop Production– Livestock Production– Supply-Utilization– Food Balance Sheets– Water Stress
• Climate Data– GCMS– Generated Weather
• Geospatial and Subnational Data– Irrigation– Subnational Statistics– Crop suitability maps– Population Density
• Exogenous IMPACT Parameters– Yield, Area Growth– Elasticities– Prices (AMAD)– Population– GDP
Share Data
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• SPAM - Spatial Production Allocation Model
• Land-Use Model• DSSAT Crop Models• Biofuel Model
• Hydrology Model• Water Basin
Management Model• Water Stress Model• Food Model
– Crops– Livestock– Sugar– Oilseeds
Models
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Direct Users of FAO Using Processed FAO
SPAM FAO: Estimation
FAO
Climate Data
Exogenous IMPACT
Parameters
Geospatial and
Subnational Data
IMPACT• Food• Water Stress• Water Demand
Shared Data
FAO Data
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• 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
Processing FAO DataSource Data (FAO, SPAM)
Feedback to data source
Priors on values and estimation errors of
production, demand, and trade
Estimation by Cross-Entropy Method
Check results against priors and identify
potential data problems
New information to correct identified
problems
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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
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Users of Climate Data Use Aggregated Processed Climate Data
Crop Models Hydrology
FAO
Climate Data
Exogenous IMPACT
Parameters
Geospatial and
Subnational Data
IMPACT• Food• Water Demand• Water Stress
Shared Data
Climate Change Consistency
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Data Harmonization and Quality
• Building common geographical definitions• Standardize mapping of data• Share data (initial and processed)
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Users of Geospatial and Subnational Data
Use Aggregated Outputs from direct users
SPAM
Hydrology
Crop Models
Land-Use Model
FAO
Climate Data
Exogenous IMPACT
Parameters
Geospatial and
Subnational Data
IMPACT• Food• Water Demand• Water Stress
Shared Data
Geospatial Data Users
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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 Processing
is source-specific– Model Inputs are
model-specific
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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 Processing
is source-specific– Model Inputs are
model-specific
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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