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MOSAICC:An inter-disciplinary system of models
to evaluate the impact of climate change on agriculture
Francois Delobel and Oscar RojasAmman, 15 Dec 2013
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• Downscaled climate projection from SDSM
• Impacts on Crop Yields (rainfed and irrigated)
• Hydrological and economic impacts also evaluated (WB)
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• 1 GCM (HadCM3)• 2 scenarios (A2, B2)• 4 time slices (2000, 2030,
2050, 2080)• 6 agroecological zones• 50 Crops= Huge amount of data
generated= Huge time processing
(including parametrization)
Replication?Transferability?
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Concept
• Need for a tool to facilitate the user experience by simplifying data processing and simulation runs
• Include additional models• Transferable (capacity reinforcement)• At no cost (freeware)
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Concept
MOSAICC: Modelling System for Agricultural Impacts of Climate Change•Capacity development tool for•Assessing climate change impacts on agriculture at national level (trends)•By national experts (ministries, universities, research institutions)•Using own data•In a perspective of decision support
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Downscaled climate projections under various climate scenarios
Crop yield projections
under climate scenarios
Simulation of the country’s hydrology and estimation of
water resources
Economic impact and analysis of policy response at national
level
Concept
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Model selection
• Expert consultation (Jan 2010)• Robustness rather than sophistication (low
data input, commonly available), flexibility, wide application, open source
• 1 Statistical Downscaling tool, 2 crop models, 1 Hydrological model and 1 Economic model
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Statistical Downscaling Portal
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Statistical Downscaling Portal
• Created for the ENSEMBLE project by the Santander Meteorology group, University of Cantabria
• Methods: Analogs, weather typing, regression, neural networks
• Cross validation• 8 ESM from CMIP5
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STREAM
• Developed by IVM, Free University of Amsterdam and WaterInsight
• Conceptual empirical hydrological model. • Core: a GIS-based rainfall runoff model which
enables the simulation of river discharges and water availability in large river basins.
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STREAM
• Extensions:– Dams;– Data input check
and calculation (from DEM)
– Automatic calibration
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WABAL
• Crop specific water balance model
• Initially used in crop forecasting (AgroMetShell, FAO)
• Produces various variables such as the Water Satisfaction Index (WSI)
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AQUACROP
• FAO cropwater productivity model to simulate yield response to water
• Focuses on water• Uses canopy cover instead of leaf area index• Balances simplicity, accuracy and robustness• Planning tool• Calibrated for cotton, maize, potato, tomato,
wheat, rice, surgar beet, quinoa, soybean etc.
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AQUACROP
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Yield projection calculation
• The crop model is used to the yield variations due to the weather conditions
• A yield function (regression model) is established between recorded yields and model outputs
• The yield function is applied to projected weather conditions to obtain crop yield projections
• Possible use of scenarios on technological progress (not modelled)
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DCGE
• Dynamic Computable General Equilibrium model, developed by IVM, Free University of Amsterdam
• Model the future evolution of the national economy of a country and the changes induced by variations of crop yields under climate change scenarios.
• Generic, adaptable to local conditions (production factors, activities, commodities, consumer types etc) according to the data availability
• Requires the assemblage of a social accounting matrix (SAM)
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DCGE
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Utilities
• Interpolation (kriging, AURELHY)• Growing season beginning and length• ET0 calculation
• Definition of study area (GIS tool)• DEM processing for hydrological modelling
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AURELHY
• Topography-based interpolation method (Meteo France)
• Combines predictions from regression models based on “landscape variables” and kriging
• Able to reproduce effects of landforms on local climates (Foehn etc)
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AURELHY
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Integration
• Server• Spatial database• Web interfaces (user profiles, work modes,
experiment definition and management, data management)
• Shell (data preparation, experiment execution, output storage)
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IntegrationClimate
Historical weather
dataDownscaled
climate projections
HydrologyCrops
Economy
IPCC GCMLow resolution
projections
Historical discharge
data
Water resourcesprojections
Historical water usestatistics
Historical crop yieldstatistics
Yield projections
Current stateof economy
Macroeconomicscenarios
Economic impacts
Crop characteristics
Soil data
Technological progressscenarios
Soil and Land use
data
Dam characteristics
Modellersinterface
End-userinterface
Server
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Interfaces
• Home page – log-in
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Interfaces• Functions (utilities and models)
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Interfaces• Data management
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Interfaces• Experiment management
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Advantages
• Participatory approach• Remote access• Nothing to install (web browser)• Easy data exchange• Low computing time• No data format or unit conversion• Data tracking down the flow
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Decision support
• Relevance of simulations and modelisation– Scenario testing (climate, varieties, crop management,
water use, demography, policies etc.)– Facilitate understanding of processes at stake– Very suitable for climate change studies
• Limitations: – Reduced reality, non
comprehensive, under assumptions
– Uncertainties
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Decision support
• “Essentially, all models are wrong, but some are useful” (G. Box, statistician)
• Data quality: garbage in = garbage out
• Not to be taken alone!
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Distribution
• Delivered to technical institutions through:– Constitution of a working group– Trainings– Support to carry out an integrated
impact study
• Operational in the Philippines and Morocco
• Foreseen: Niger, Peru, Guatemala
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Thank you for your attention
• Info:– www.fao.org/climatechange/mosaicc – [email protected]
• Partners
Mauro Evangelisti Servizi Informatici
Numerical Ecology of Aquatic Systems
AgroMetShell
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Thank you for your attention
• Welcome to Climate Smart Agriculture stand