1. General Model Information
Name: Cropping Systems Modeling Framework
Main medium: terrestrial
Main subject: biogeochemistry
Organization level: ecosystem
Type of model: ordinary differential equations, not specified
Main application: research, decision support/expert system
Keywords: crop yield, soil erosion, weather, soil water balance, crop growth, crop development, crop sowing, decomposition, crop rotation, field operation, soil tillage system, soil erosion, irrigation, aphid population dynamics, pesticide movement, pesticide degradation, incremental model building, object oriented, module
Dr. F.K. van Evert
6816 PE Arnhem
Evert, F.K. van,Yan, Y.
CropSyst was originally written to facilitate the simulation of crop yield and soil
erosion as a function of climate, soil, crop rotation and soil tillage system in the Pacific Northwest
of the United States. It has since been expanded to include other processes as well and the
framework has been developed into a general cropping systems modeling framework. We used
object-orientation to create both the models and a simulation environment that allows: 1.
incremental model building without rewriting existing code, 2. simultaneous maintenance of more
than one model of any component, 3. interchanging of component models within and between
system models, and 4. construction of a user-friendly interface from which all parameters can be
assigned and all models run. CropSyst 3.0 has several new features. Communication between
component models now takes place via messages with the help of a central mechanism. The
messaging system allows for extremely flexible coupling of components and allows all inputs and
outputs to be range-checked in one place. CropSyst 3.0 is integrated with a database which
contains both experiment data (some of which may be inputs for simulation runs) and simulation
outputs. Simulation models written in other languages can be run under CropSyst by compiling
them into a DLL and "wrapping" them in a CropSyst object. CropSyst 3.0 is written in Borlands
Delphi and takes advantage of that languages exception handling, database connectivity
components, and application building features; it runs under Windows 3.1 and Windows 95.
Author of the abstract:
CAMASE Register of Agro-ecosystems Models
II. Technical Information
Operating System(s): MS Windows 3.1 or MS Windows 95.
Programming Language(s): Borland Delphi 1.0.
III. Mathematical Information
State variables: Crop: above-ground dry matter, below-ground dry matter, grain dry matter. leafarea index, thermal time from sowing. Crop residue: residue on the soil surface, water content ofsurface residue, residue buried less than 10 cm deep. Soil: volumetric water content in each layer(layers are typically 20 cm thick). Sowing: running average of air temperature. Crop rotation: foreach crop in the rotation: identification of model and parameter set for crop, tillage system andsowing. Field operation: fraction of surface residue buried, fraction fo shallowly buried residue thatis buried deeply, change in surface roughness. Soil tillage: identification of date, model andparameter set for each field operation comprised in the tillage system.
Crop: base temperature and thermal timefor each phenological period, radiation useefficiency, dry matter-water ratio, maximum rooting depth, leaf area at emergence, relativegrowth rate of leaf area, life span of leaves, fraction ofdry matter transferred to grain at flowering.Crop residue: maximum water holding capacity. Soil: characteristic water contents. Sowing: seedrate, thousand-kernel weight, either date of planting or minimum running average temperaturerequired to allow sowing. Crop rotation: see above, plus a pointer to the next crop. Field operation:see above. Soil tillage: see above, plus a pointer to the next field operation.
See above.Time interval of simulation: 1 day. Basic spatial unit: m2.
Yan, Y., 1989. A model for predicting soil loss ratio and crop production in Eastern Washington. M.Sc. Thesis, Washington State University, Pullman, WA, USA.
Evert, F.K. van, 1992. Modeling agricultural systems with CropSyst. PhD thesis, Washington State University, Pullman, WA, USA.
V. Further information in the World-Wide-Web
VI. Additional remarks
Model Parentage: Soil water balance: Campbell, G.S. & R. Diaz, 1988. Simplified soil water balancemodels to predict crop transpiration. In: Bidinger, F.R. & C. Johansen (Eds.). Drought researchpriorities for the dryland tropics. ICRISAT, Patancheru, Andhra Pradesh, India, 15-26 Cropgrowth and development: Campbell, G.S. & R. Diaz, 1988. Op.Cit. Field operation: McCool, D.K.Washington State University, personal communication. Crop residue decomposition: Strook, H.F.,K.L. Bristow, L.F. Elliott, R.I. Papendick & G.S. Campbell, 1989. Predicting rates of wheat residuedecomposition. Soil Scie.Soc.Am.J. 35: 91-99 Soil loss: McCool, D.K. Washington StateUniversity, personal communication, and Soil Conservation Service, 1972. National EngineeringHandbook. USDA-SCS, Washington, D.C.
COMMENTS: Finalizing work is being done on components: aphid population dynamics,pesticide movement in soil. Papers in preparation: - Evert, F.K. van, Y. Ying, F. Young & G.S.Campbell. Managing crop yield and soil loss with a simulation model. - Evert, F.K. van, B.G.McConkey, A.E. Grable & G.S. Campbell. Simulation of crop damage by the Russian wheat aphidand the fate of insecticide residues in the environment.
Last review of this document by: T. Gabele: 25. 6. 1997 -
Status of the document:
last modified by
Joachim Benz Mon Jul 2 18:31:37 CEST 2007