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Designing modular frameworks for crop modelling. Myriam Adam


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A presentation at the WCCA 2011 event in Brisbane.

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Designing modular frameworks for crop modelling. Myriam Adam

  1. 1. Designing modular frameworks for crop modellingImplementation and guidelines for use Myriam ADAM Marc CORBEELS, Frank EWERT, Herman VAN KEULEN, Peter LEFFELAAR, Jacques WERY
  2. 2. 2 /20Why 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)
  3. 3. 3 /20Diversity of objectives  diversityof models and their structures Photosynthesis of leaf canopies1965 (de Wit 1965) ELCROS1970 (de Wit et al. 1970) Pedigree of models of the ‘School of de Wit’ (Adapted from Bouman et al. 1996. Agric. Syst. 52:171-198) MICROWEATHER1975 ARID CROP (Goudriaan 1977) (van Keulen 1975) ARID CROP BACROS PHOTON (SAHEL) (de Wit et al. 1978) (de Wit et al. 1978) (van Keulen et al. 1986)1980 PAPRAN (Seligman & van Keulen 1981) SUCROS1985 (van Keulen et al. 1982) SWHEAT SUCROS87 MACROS WOFOST1990 (van Keulen & Seligman 1987) (van Laar et al. 1992) (van Diepen et al. 1988) (Penning de Vries et al. 1989) (van Keulen & Wolf 1986) SUCROS1 (Goudriaan & van Laar 1994) INTERCOM (Kropff & van Laar 1993)1995 SUCROS2 WOFOST 7.0 (van Laar et al. 1997) (Boogaard et al. 1998) ORYZA (Kropff et al. 1995)2000 ORYZA2000 (Bouman et al. 2001) GECROS2005 (Yin & van Laar 2005)
  4. 4. 4 /20Objective• 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
  5. 5. Decompose a model into parts(different structures) IMPLEMENTATION
  6. 6. 6 /20 Diverse models = Diverse structures Anything in common?Structure of these models is based on the same basic crop processes Phenology spring crop winter crop indeterminate Light interception Production level Homogenous Cascading Water limited Darcy LAI expansion Row Nitrogen Nitrogen fixation limited Biomass production Partitioning RUE Allocation factor Farquhar Source sink strength
  7. 7. 7 /20Applying new software techniques in cropmodelling• Software engineers also decompose their models intosub-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 ofcode and build on the existing expertise
  8. 8. 8 /20 Design used CROSPAL APES APSIMModules RUE Strategy design Strategy design Dynamic linkBasic crop processes pattern pattern libraries (dlls)Component Abstract factory Composite Generic modelCrop and criteria with a strategy structure/ XML Biomass GUI (IStrategy: configuration production interface)Crop models Definition of new Components GCROP linkedSoil-crop concrete factories linked via to the APSIM(i.e. crop simulator) wrapper engine
  9. 9. 9 /20Implications for the users Developers Crop modellers Model users --- CROSPAL GUI APES APES APSIM GUI CompositeFlexi strategies Biomass GUIbility production CROSPAL factories CROSPAL APES strategies strategies PLANT from APSIM dlls and xml+++ RUE
  10. 10. 10 /20Implications 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”
  11. 11. Select relevant parts to assemble acrop model depending on the cropsystem and the simulationobjective Guidelines for use
  12. 12. 12 /20 CROSPAL CROp Simulator: Picking and Assembling Libraries Phenology: Criteria spring crop Phenology: winter crop Phenology: indeterminate LAI expansion Crop type Limiting factorsBiomass production: (water, N, P,K…)RUE Biomass production: Farquhar Scale Biomass partitioning Data availability Management Water limited Nitrogen Nitrogen fixation limited
  13. 13. 13 /20Test different model structures winter crop indeterminate spring crop Objective of Picking the basic crop The “right” simulation growth and modelling solution development processes (crop model) according to criteria Models comparison Sensitivity analysis Expert elicitation Uncertainty matrix Conceptual modelling Underlying the main assumptions
  14. 14. 14 /20 Uncertainty matrix Source of Nature Range Recognized uncertainty The The “unknown ignorance “known known” (to be) known” The “known unknown”Contextual: System definitionboundaries anddefinitionsInput/data Data collection Data availabilityuncertaintiesParameters Sensitivity analysisModel Structure Scenario analysis Data availability/ research ▫ Study the system in a systematic way ▫ Test different modules ▫ Document uncertainties by explicitly formulating the assumptions
  15. 15. 15 /20Models comparison North South Detailed Summarized Farq. RUE Farq. RUE LAI LAI NORTH SOUTH ▫ Investigate the effect of modelling details on potential yield ▫ Identify which structure in which location
  16. 16. 16 /20 Participatory modelling▫ Understand the initial model▫ Integrate new knowledge▫ Test the new model
  18. 18. 18 /20Main 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
  19. 19. 19 /20Use of models for different purposes Developers Crop modellers Model users --- Software engineer Agronomist CROSPAL GUI Modeling Solution Soil-crop system APES APES APSIM GUI CompositeFlexi strategies GUIbility Uncertainty CROSPAL Component factories Basic crop processes CROSPAL APES strategies strategies Underlying assumptions PLANT from APSIM dlls and xml Underlying concept Module+++ Basic research Applied research
  20. 20. APES teamFunding: PRI, CIRAD, SEAMLESSThanks all for your attention Acknowledgements contact: