1. General Model Information

Name: Crop and Soil system model

Acronym: CROPS

Main medium: terrestrial
Main subject: agriculture, meteorology, hydrology
Organization level: Population, Ecosystem
Type of model: difference equations (1D), partial differential equations (finite differences,1D)
Main application: research, education, simulation/optimisation tool
Keywords: crop model, photosynthesis, evaporation, transpiration, soil, root uptake, agro-ecosystem


Y. Luo
Bldg. 917, Datun Road, Anwai,
100101 Beijing,
P. R. China

Phone: +86 10 64856514
Fax: +86 10 64856514
email: luoy@igsnrr.ac.cn


Y. Luo


CropS A Crop and Soil System Model

Simulation models of agricultural systems, when coupled with appropriate data sources, have a great potential for bringing agricultural research and development into the age of information technology. Within agricultural disciplines, crop production involves a complexity of interactions between crop genotype, the soil and aerial environment, and management practices. And it is because of this complexity, only can the synthetic simulation model edict the behavior of the agricultural system. This research is being undertaken to set up a synthetic Crop and Soil system (CropS) model that is suit to the natural condition of the north China plain. This stage report addresses the progress of this work.

In chapter 1, the reasons why the reported work should be done were addressed. The current situation of research and application of simulation model of agricultural system was briefed. It was concluded that research and application of the synthetic simulation models is far lack behind the international development in our country. No general models can be transplanted without validation for the great difference of soil, crop, and climate among locations. Therefore, it is imperative for us to develop models suitable for natural situation, for example that of the north China plain. For models imported from aboard, extensive field validation and re-development work should be done before its successful application in solving problems in the target area.

In chapter 2, the theoretical fundamentals of agricultural water saving was addressed. It was emphasized that improving the water use ratio and water use efficiency are the two key points in development of agricultural water saving. Especially, the author discussed the crop water use efficiency and its relation to the environmental factors at the levels of leaf, canopy and yield, respectively, and further analyzed the possible ways of lifting the WUE. The author emphasized that the theoretical fundamentals and technology of agricultural water saving are a synthetic system of different disciplines.

In chapter 3, the formula of Green-Ampt equation of layered soil was given. On one hand, it was assumed that the soil profile of both texture and initial soil water content were homogeneous by the original version of Green-Ampt equation, but in the field situation, the most popular soil profile is layered. One another hand, the Green-Ampt equation is generally applied to determine the relation between rainfall or irrigation and runoff other than the soil water profile dynamics. The work in this chapter was also planned to investigate the feasibility of soil water profile prediction by the Green-Ampt equation. An irrigation infiltration process was recorded and simulated with both the Green-Ampt equation of layered soil and the continuous equation of unsaturated soil water flow. Two points were addressed from the simulation results.

  1. When infiltration stopped, the simulated soil profiles by the mentioned approaches were quite different.
  2. After redistribution for some time (17h for this case), the difference diminished. This indicated that it is suitable to utilize the Green-Ampt model to simulate the soil water dynamics in a long period. Especially, when the irrigation or rainfall amount is only available, the Green-Ampt model is even more flexible to use.

In chapter 4, some macro-models of water uptake by root were evaluated with the precisely recorded data of evapotranspiration and root density distribution, as well as the soil moisture profile with the neutron probe. The models included the Molz-Remson(1970), Feddes(1978), and the Selim-Iskandar(1978). Meanwhile, author modified the Molz-Remson and Selim-Iskandar models with the Feddes reduction function and the Feddes model with the root density distribution. Soil water depletion process was simulated with the continuous equation with the root uptake as a sink term expressed by the models above respectively. The comparison of the simulated and measured soil water profiles indicated that great discrepancy existed by all the models except the modified Feddes model with relative error of 5.6% over the whole profile. The success of the modified Feddes model is supported by the general accepted opinion that the root uptake of water is jointly determined by both the root density and soil water potential profile.

In chapter 5, some sub-models of CropS model were established and integrated to realize the functions of simulating soil dynamics, evaporation and transpiration, root water uptake, photosynthesis, and CO2 flux over the canopy. The soil water dynamics was simulated with the continuous soil water flow equations of layered soil; the evaporation and transpiration were modeled with the Shuttleworth and Wallace formula; the crop root water uptake water simulated with the modified Feddes model as described in chapter 4. The photosynthesis-stomata resistance model of canopy was derived from the Yu model at the leaf scale. The CO2 flux from the canopy to the screen level can be determined by the difference of CO2 concentrations and the resistance between them. As an alternative, Dickinson's model was also given for determining the canopy resistance.

In chapter 6, the CropS model was evaluated with the field data of micrometeorology, crop, and soil. Also, CropSability of simulating the CO2 flux was evaluated by the measured CO2 concentrations at two heights with CI301PS gas analyzer. The modeled evapotranspiration was compared with that calculated by Bowen ratio approach, the modeled soil water profile with that measured by neutron probe. The comparisons showed very good agreements between the estimated and measured ones. The CO2 flux estimated by CropS was compared with that calculated by the Bowen ratio approach. Their daily change processes were very similar, but discrepancy existed in the point view of quantity. This was possibly caused by the inability of modeling the CO2 flux from soil of CropS.

In chapter 7, an application case study of CropS model was presented. CropS model was applied to estimate the water consumption of winter wheat and to evaluate the irrigation efficiency in the Yucheng area of Shandong province. The following conclusions were obtained. First, during the growth season of 1998-1999, the water consumption was approximately 434mm in water depth. That before the reviving took about 20%, and that during the reviving and grain filling 67%. Secondly, leakage at the 100cm below the ground was closely related to the field capacity of soil, irrigation water amount each time and the priori water storage. The higher the priori soil water storage and the irrigation water amount were, the larger the percolation and the lower the irrigation efficiency. Finally, the widely adopted irrigation management pattern, one winter irrigation, one irrigation during the reviving period, and one in the grain filling period, should be carefully implemented and the irrigation water amount determined according to field monitoring. Otherwise, the fairly high priori soil water storage would cause large percolation in the irrigation during the reviving, and the following irrigation prevented the reuse of the percolated water by means of upward supply.

II. Technical Information

II.1 Executables:

Operating System(s): DOS

II.2 Source-code:

Programming Language(s): C

II.3 Manuals:

Crop and Soil System model: USER's Manual

II.4 Data:

daily meteolgical data, soil profile data, irrigation data, crop data
all can be processed in a presettled excel sheet

III. Mathematical Information

III.1 Mathematics

III.2 Quantities

evaporation, transpiration, CO2 content in canopy air, CO2 flux, soil water profile (content or potential) infiltration rate, leakage rate

III.2.1 Input

meteological data: wind speed, dry and wet buld temperature, net radiation, CO2 content in air
soil profile: layers, depths of layers, saturated content, field capacity, wilting point, saturated hydraulic conductivity

crop height and LAI

III.2.2 Output

evaporation, transpiration, CO2 flux, CO2 content in crop canopy air, soil water profile, infiltration rate, leakage time interval depends upon the time scale of input meteo data

IV. References

V. Further information in the World-Wide-Web

VI. Additional remarks

Last review of this document by: Y. Luo, Wed Nov 28 04:43:39 2001
Status of the document: Contributed by Y. Luo
last modified by Tobias Gabele Wed Aug 21 21:44:41 CEST 2002

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