Designing modular frameworks for crop modelling. Myriam Adam
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Transcript of Designing modular frameworks for crop modelling. Myriam Adam
Designing modular frameworks
for crop modellingImplementation and guidelines for use
Myriam ADAM Marc CORBEELS, Frank EWERT, Herman VAN
KEULEN, Peter LEFFELAAR, Jacques WERY
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Why having modular frameworks?• Large collection of crop models
• Increasing interest in model reuse
• Are they directly applicable? How to adapt them for the specific application/objective?
Need of guidelines for model selection for
a given crop, in a given context and for a given question (system studied)
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/20Diversity of objectives diversity of models and their structures
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1965
1970
1975
1980
1985
1990
1995
2000
ELCROS(de Wit et al. 1970)
BACROS(de Wit et al. 1978)
PAPRAN(Seligman & van Keulen 1981)
ARID CROP(van Keulen 1975)
ARID CROP(SAHEL)
(van Keulen et al. 1986)
PHOTON(de Wit et al. 1978)
MICROWEATHER(Goudriaan 1977)
SWHEAT(van Keulen & Seligman 1987)
ORYZA(Kropff et al. 1995)
ORYZA2000(Bouman et al. 2001)
WOFOST(van Diepen et al. 1988)
(van Keulen & Wolf 1986)
WOFOST 7.0(Boogaard et al. 1998)
SUCROS(van Keulen et al. 1982)
SUCROS87(van Laar et al. 1992)
SUCROS1(Goudriaan & van Laar 1994)
SUCROS2(van Laar et al. 1997)
MACROS(Penning de Vries et al. 1989)
INTERCOM(Kropff & van Laar 1993)
Pedigree of models of the ‘School of de Wit’
(Adapted from Bouman et al. 1996. Agric. Syst. 52:171-198)
GECROS(Yin & van Laar 2005)2005
Photosynthesis of leaf canopies(de Wit 1965)
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Objective• Develop framework to facilitate the assembly of
crop models depending on the crop system and on the simulation objective (when to use which model?)
▫ IMPLEMENTATION▫ Decompose the models into parts (different structures)▫ Incorporate the different parts in a framework
▫ USE▫ Develop criteria and approaches to select relevant parts to
assemble a crop model depending on the crop system and the simulation objective
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Decompose a model into parts (different structures)
IMPLEMENTATION
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Phenologyspring crop
winter crop indetermi
nate
Diverse models = Diverse structuresAnything in common?
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Light interception Production level
Biomass production Partitioning
Allocation factor
LAI expansion
RUE
Water limited
Nitrogen limited
Nitrogen fixation
Homogenous
Row
Cascading
Darcy
Source sink strength
Farquhar
Structure of these models is based on the same basic crop processes
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Applying new software techniques in crop modelling
•Software engineers also decompose their models into sub-models
•Applying object-oriented techniques enables to :▫ Interchange of code among models▫ Test of alternatives hypotheses▫ Share expertise
Applying their techniques to more easily reuse parts of code and build on the existing expertise
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Design used
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CROSPAL APES APSIM
Modules Basic crop processes
Strategy design pattern
Strategy design pattern
Dynamic link libraries (dlls)
Component Crop
Abstract factory and criteria with a GUI
Composite strategy (IStrategy: interface)
Generic model structure/ XML configuration
Crop modelsSoil-crop (i.e. crop simulator)
Definition of new concrete factories
Components linked via wrapper
GCROP linked to the APSIM engine
Biomass production
RUE
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Implications for the users
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Flexibility
---
+++
Model users Developers Crop modellers
CROSPAL strategies
APES strategies
CROSPAL factories
APES
GUI
CROSPAL GUI
APSIMGUI
APES Composite strategies
PLANT from APSIM
dlls and xml
Biomass production
RUE
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Implications for the users
•How to combine the different parts?
•How to deal with the flexibility?
•Need of criteria or systematic approaches to define “the logic to assemble the appropriate modules”
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Select relevant parts to assemble a crop model depending on the crop system and the simulation objective
Guidelines for use
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CROSPALCROp Simulator: Picking and Assembling Libraries
Criteria
Crop typeLimiting factors
(water, N, P,K…)
ScaleData availability
Management
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Phenology: spring crop
Biomass partitioning
LAI expansion
Biomass production: RUE
Phenology: winter crop
Water limited
Nitrogen limited
Nitrogen fixation
Phenology: indeterminate
Biomass production: Farquhar
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Test different model structures
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The “right”modelling solution
(crop model)
Objective of simulation
Picking the basic crop growth and
development processes according
to criteria
Uncertainty matrixUnderlying the main
assumptions
Expert elicitationConceptual modelling
Models comparison Sensitivity analysis
spring crop
winter crop indeterminate
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Uncertainty matrix
▫ Study the system in a systematic way▫ Test different modules▫ Document uncertainties by explicitly formulating the
assumptions
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Source of uncertainty
NatureThe
“known known”
Range The “unknown (to be) known”
Recognized ignorance
The “known unknown”
Contextual: boundaries and definitions
System definition
Input/data uncertainties
Data collection Data availability
Parameters Sensitivity analysis
Model Structure Scenario analysis Data availability/ research
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Models comparison
▫ Investigate the effect of modelling details on potential yield
▫ Identify which structure in which location
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North South Detailed Summarized Farq. RUE Farq. RUELAI LAI NORTH SOUTH
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Participatory modelling
▫Understand the initial model▫Integrate new knowledge▫Test the new model
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CONCLUSIONS
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Main conclusions
Definition of guidelines to facilitate exchange of models (or parts of models)
Better documentation of modules but also of modelling decision-making process (e.g. use of uncertainty matrix)
Modular modelling is prone to error seeking for scientific understanding vs.
credible set of outputs
Role of the crop modeller and conceptual models
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Use of models for different purposes
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Flexibility
---
+++Basic research Applied research
Model users Developers
CROSPAL strategies
APES strategies
CROSPAL factories
APES
GUI
CROSPAL GUI
APSIMGUI
APES Composite strategies
PLANT from APSIM
dlls and xml
Software engineer
Modeling Solution
Component
Module
Agronomist
Soil-crop system
Basic crop processes
Underlying concept
Uncertainty
Underlying assumptions
Crop modellers
Acknowledgements
contact: [email protected]
APES team
Funding: PRI, CIRAD, SEAMLESS
Thanks all for your attention