MOSAICC:An inter-disciplinary system of models to evaluate the impact of climate change on agriculture, By Francois Delobel and Oscar Rojas ,Land and Water Days in Near East & North Africa, 15-18 December 2013, Amman, Jordan

1. MOSAICC:
An inter-disciplinary system of models
to evaluate the impact of climate
change on agriculture
Francois Delobel and Oscar Rojas
Amman, 15 Dec 2013

2. • Downscaled climate
projection from
SDSM
• Impacts on Crop
Yields (rainfed and
irrigated)
• Hydrological and
economic impacts
also evaluated (WB)

3. • 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?

4. 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)

5. 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

6. Economic impact and analysis
of policy response at national
level
Crop yield
projections
under climate
scenarios
Concept
Simulation of the country’s
hydrology and estimation of
water resources
Downscaled climate projections under
various climate scenarios

7. 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

8. Statistical Downscaling Portal

9. 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

10. 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.

11. STREAM
• Extensions:
– Dams;
– Data input check
and calculation
(from DEM)
– Automatic
calibration

12. WABAL
• Crop specific water
balance model
• Initially used in crop
forecasting
(AgroMetShell, FAO)
• Produces various
variables such as the
Water Satisfaction
Index (WSI)

13. 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.

14. AQUACROP

15. 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)

16. 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)

17. DCGE

18. Utilities
• Interpolation (kriging, AURELHY)
• Growing season beginning and length
• ET0 calculation
• Definition of study area (GIS tool)
• DEM processing for hydrological modelling

19. 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)

20. AURELHY

21. Integration
• Server
• Spatial database
• Web interfaces (user profiles, work modes,
experiment definition and management, data
management)
• Shell (data preparation, experiment
execution, output storage)

22. Integration
IPCC GCM
Low resolution
projections
Server
Climate
Historical
weather
data
Modellers
interface
Downscaled
climate
projections
Historical
crop yield
statistics
Historical
water use
statistics
Crop
characteristics
Crops
Hydrology
Yield projections
Water resources
projections
Soil data
Technological
progress
scenarios
Current state
of economy
Economy
Macroeconomic
scenarios
Economic
impacts
Historical
discharge
data
Soil and
Land use
data
Dam
characteristics
End-user
interface

23. Interfaces
• Home page – log-in

24. Interfaces
• Functions (utilities and models)

25. Interfaces
• Data management

26. Interfaces
• Experiment management

27. 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

28. 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

29. 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!

30. 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

31. Demo
• Morocco server
http://81.192.163.58/

32. Thank you for your attention
• Info:
– www.fao.org/climatechange/mosaicc
– MOSAICC@fao.org
• Partners
Mauro Evangelisti
Servizi Informatici
Numerical Ecology of
Aquatic Systems
AgroMetShell

33. Thank you for your attention
• Welcome to Climate Smart Agriculture stand