Systems models that paved the way for APSIM: CERES-Maize, CM-Ken, AUSIM; PERFECT
Several cropping systems models have appeared since 1980. These can be classed into two types on the basis of whether emphasis is primarily on crop management or on soil/land management. The primary aim of the first type of model is to accurately simulate yield for a wide range of environmental conditions and genotype characteristics, but to do so with affordable information requirements. This is largely achieved in models such as the CERES family by a pragmatic mix of empirical and mechanistic functional relationships. The scope of this type of model includes the climatic and soil variables whose relationships importantly affect crop yields.
In the second type of model, emphasis tends to shift to processes of soil loss and degradation, e.g. EPIC, PERFECT, etc. Crop output has less dependence on weather and soil state than in CERES. A greater proportion of the computations deals with soil and hydrological processes, and less elaboration of production is considered to be an adequate compromise to achieve satisfactory estimates of crop growth and yields.
The cropping systems model, AUSIM (PDF), was developed to achieve reduced compromise in treatment of crop production and soil managegment. These projects required a model that could simulate the performance of maize and sorghum in systems in which pasture or grain legumes occur in rotations or as intercrops. In addition, the model needed to accommodate the effects of no-tillage/mulch as well as conventional cultivation.
Research to provide these capabilities began with the evaluation of CERES-Maize. This model was selected as having an appropriate level of treatment of relevant processes for our application and (b) embodying a large amount of research and modelling experience. The original model performs well in the cool SAT of Eastern Kenya and, after modification, in the hot SAT of northern Australia, The model has subsequently been adapted to simulate grain sorghum production, AUSIM has developed from CERES-Maize to achieve four objectives: (a) to maintain a family of crop growth models with standardized features which all share the same subroutines that are not crop-specific, (b) to have a capability for combining crop growth models to simulate various cropping systems, (c) to improve the methods for modelling a crop, and (d) to improve the models of key soil processes, e.g. AUSIM consists of a suite of standardized crop models together with soil models for water, nitrogen, and phosphorus, all of which respond to weather inputs. In AUSIM, the soil plus the climate routines comprise the most basic functional configuration. Crops can be absent (bare fallow), occur in a sequence, or occur in mixtures. Making the soil the centre of the simulation process allows the soil to acrue the effects of sequences (or mixtures) of crops. Because the soil models are general, all crop variables, including roots, reside in the crop routines. In other words, Crops come and go over time, finding the soil in a particular state and leaving it in another. This is the central feature of AUSIM and its successor, APSIM
Developments in Crop Environment Submodels
An improved method for simulation of the soil water balance was implemented in AUSIM. Paths for improvement are limited by the remoteness of the model from the physical processes that determine water movement. Previously, Darcian flow theory has not been used in crop models because of (a) the high computing requirements of the numerical procedures required and (b) the low availability of soil hydraulic data. However, with judicious choice of numerical methods, the first of these problems can be avoided. This is demonstrated in SWIM (Soil Water Infiltration and Movement) (11), a model which uses a numerical solution of Richard’s equation to route water through a soil profile. SWIM has been implemented in AUSIM to replace the use of USDA-SCS Curve Numbers for determining runoff and the currently-used “cascading” procedure for redistribution between layered stores. Run times are only 1.6 times those of the existing CERES model. The soil hydraulic properties required for solution of the Richards’ equation are the moisture characteristic and the hydraulic conductivity function. Simple models are used to describe these functions with only four parameters. This contributes to efficiency in both the numerics and the process of characterization of the hydraulic properties of each soil horizon. Data bases of the hydraulic properties for a wide range of Australian soils were constructed which subsequently have served AUSIM and, later, APSIM needs.
Whitbread, A., Robertson, M., Carberry, P. and Dimes, J. (2010). Applying farming systems simulation to the development of more sustainable smallholder farming systems in Southern Africa. European Journal of Agronomy 32, 51-58 Abstract PDF
Huth, N.I. and Carberry, P.S. (2009). The APSIM experience in Australia: from research model to farmer application. In: Rapidel, B., Roupsard, O. & Navarro, M. (Eds.) Modelling agroforestry systems. Tropical Agricultural Research and Higher Education Center, CATIE, Turrialba, Costa Rica. pp. 41-50.
Carberry, P.S.; Hochman, Z., Hunt, J.R.. Dalgliesh N.P., McCown, R.L., Whish J.P.M., Robertson, M.J., Foale, M.A., Poulton, P.L., van Rees, H. (2009) Re-inventing model-based decision support with Australian dryland farmers: 3. Relevance of APSIM to commercial crops. Crop and Pasture Science 60, 1044–1056. PDF
Delve, RJ; Probert, ME (2004) Modelling nutrient management in tropical cropping systems. ACIAR Proceedings No. 114, 138p. BOOK PDF
Probert, ME; Dimes, JP (2004) Modelling Release of Nutrients from Organic Resources Using APSIM. In: Delve, RJ; Probert, ME (eds.), ACIAR Proceedings No. 114, pp 25-31. BOOK PDF
Carberry, PS; Gladwin, Christy Twomlow; Steve (2004) Linking Simulation Modelling to Participatory Research in Smallholder Farming Systems. In: Delve, RJ; Probert, ME (eds.), ACIAR Proceedings No. 114, pp 32-46. BOOK PDF
Probert, ME, Delve, RJ; Kimani, SK; Dimes, JP (2004) The APSIM Manure Module: Improvements in Predictability and Application to Laboratory Studies. In: Delve, RJ; Probert, ME (eds.), ACIAR Proceedings No. 114, pp 76-84. BOOK PDF
Chivenge, P; Dimes, J; Nhamo, N; Nzuma, JK; Murwira, HK (2004) Evaluation of APSIM to Simulate Maize Response to Manure Inputs in Wet and Dry Regions of Zimbabwe. In: Delve, RJ; Probert, ME (eds.), ACIAR Proceedings No. 114, pp 85-92. BOOK PDF
Probert, ME (2004) Capability in APSIM to Model Phosphorus Responses in Crops. In: Delve, RJ; Probert, ME (eds.), ACIAR Proceedings No. 114, pp 92-100. BOOK PDF
Kinyangi, J; Delve, RJ; Probert, ME (2004) Testing the APSIM Model with Data from a Phosphorus and Nitrogen Replenishment Experiment on an Oxisol in Western Kenya. In: Delve, RJ; Probert, ME (eds.), ACIAR Proceedings No. 114, pp 101-109 BOOK PDF
Micheni, AN; Kihanda, FN; Warren, GP; Probert, ME (2004) Testing the APSIM Model with Experimental Data from the Long-term Manure Experiment at Machang’a (Embu), Kenya. In: Delve, RJ; Probert, ME (eds.), ACIAR Proceedings No. 114, pp 110-117 BOOK PDF
Dimes, JP; Revanuru, S (2004) Evaluation of APSIM to Simulate Plant Growth Response to Applications of Organic and Inorganic N and P on an Alfisol and Vertisol in India. In: Delve, RJ; Probert, ME (eds.), ACIAR Proceedings No. 114, pp 118-125 BOOK PDF
Delve, RJ; Probert, ME; Dimes, JP (2004) Improved Capabilities in Modelling and Recommendations: Summary. In: Delve, RJ; Probert, ME (eds.), Proceedings No. 114, pp 135-138. BOOK PDF
Probert, ME; Dimes, JP (2004) Modelling Release of Nutrients from Organic Resources Using APSIM. IN: Delve, RJ; Probert, ME (eds).
ACIAR Proceedings No. 114, pp 25-31. BOOK PDF
Carberry, PS; Gladwin, Christy Twomlow; Steve (2004) Linking Simulation Modelling to Participatory Research in Smallholder Farming Systems. In: Delve, RJ; Probert, ME (eds.), ACIAR Proceedings No. 114, pp 32-46. BOOK PDF
Probert, ME, Delve, RJ; Kimani, SK; Dimes, JP (2004) The APSIM Manure Module: Improvements in Predictability and Application to Laboratory Studies. In: Delve, RJ; Probert, ME (eds.), ACIAR Proceedings No. 114, pp 76-84. BOOK PDF
Chivenge, P; Dimes, J; Nhamo, N; Nzuma, JK; Murwira, HK (2004) Evaluation of APSIM to Simulate Maize Response to Manure Inputs in Wet and Dry Regions of Zimbabwe. IN: Delve, RJ; Probert, ME, ACIAR Proceedings No. 114, pp 76-84. ACIAR Proceedings No. 114, pp 85-92. BOOK PDF
Probert, ME (2004) Capability in APSIM to Model Phosphorus Responses in Crops. ACIAR Proceedings No. 114, pp 92-100. BOOK PDF
Kinyangi, J; Delve, RJ; Probert, ME (2004) Testing the APSIM Model with Data from a Phosphorus and Nitrogen Replenishment Experiment on an Oxisol in Western Kenya. In: Delve, RJ; Probert, ME (eds.), ACIAR Proceedings No. 114, pp 101-109 BOOK PDF
Huth, NI; Carberry, PS; Poulton, PL; Brennan, LE; Keating, BA (2003). A framework for simulating agroforestry options for the low rainfall areas of Australia using APSIM. Europ. J. Agronomy 18, 171, 185. PDF
Keating, BA.; Carberry, P. S.; Hammer, G. L.; Probert, Mervyn E.; Robertson, M. J.; Holzworth, D.; Huth, N. I.; Hargreaves, J. N. G.; Meinke, H.; Hochman, Z.; McLean, G.; Verburg, K.; Snow, V. O.; Dimes, J. P.; Silburn, M.; Wang, E.; Brown, Stuart; Bristow, K. L.; Asseng, S.; Chapman, S. C.; McCown, R. L.; Freebairn, D. M., and Smith, C. J. (2003) An overview of APSIM, a model designed for farming systems simulation. European Journal of Agronomy 18:267-288. PDF
McCown, R.L., Carberry P, Hochman Z, Hargreaves D. (2003) A new role for hard science in soft Farming Systems Research: Learnings from ten years of facilitating farmers’ experimenting using a cropping systems simulator. Australian Farming Systems Conference, Toowoomba, Queensland, 7-11 Sep., 2003.
(http://afsa.asn.au/cgi-bin/afsapapers/display.cgi?search=1&searchtext=99) PDF
Robertson, M. J., Carberry, P. S., Huth, N.I., Turpin, J.E., Probert, M.E., Poulton, P.L., Bell, M., Wright, G.C., Yeates, S.J. and Brinsmead, R.B., 2002. Simulation of growth and development of diverse legume species in APSIM. Aust. J. Agric. Res., 53:429-446.
Hochman, Z., Carberry, P.S., McCown, R.L., Dalgliesh, N.P., Foale, M.A. and Brennan, L.E. (2002). APSIM in the Marketplace: a Tale of Kitchen Tables, Boardrooms and Courtrooms. Acta Horticulturae 566. 21-33
Carberry, P. S.; Probert, Mervyn E.; Dimes, J. P.; Keating, Brian A., McCown, R. L. (2002) Role of modelling in improving nutrient efficiency in cropping systems. Plant and Soil. 245, 193-203 PDF
McCown, R.L., Keating B, Carberry P, Hochman Z, Hargreaves D. (2002) The co-evolution of the Agricultural Production Systems Simulator (APSIM) and its use in Australian dryland cropping research and farm management intervention. In: Ahuja, LR, Ma, L, and Howell, TA (eds.), Agricultural System Models in Field Research and Technology Transfer, Lewis: Boca Raton, FLA, pp149-175. PDF
Probert, ME; Keating, BA (2000) What soil constraints should be included in crop and forest models? Agriculture, Ecosystems, & Environment 82, 273-281 PDF
Hammer, G., Keating, B.A., Meinke, H., Carberry, P.S., Freebairn, D., Probert, M.E., and Holzworth, D.(1999) An integrated systems approach to improving agricultural systems using the agricultural productions systems simulator, APSIM. In Donatelli, M., Stockle, C., Villalobus, F., and Villar Mir, J.M. (eds), Proceedings of the international symposium, Modelling cropping systems, Lleida, 21-23 June 1999, Spain.
Probert, ME; Dimes, JP;Keating, BA; Dalal, RC; Strong, WM (1998) APSIM’s water and nitrogen modules and simualtion of the dynamics of water and Toolsnitrogen in fallow systems Agric. Systems 56:1-28 PDF
Hargreaves, D.M.G., Dobson, P., McCown, R.L., Hochman, Z. and Poulton, P.L. (1998) FARMSCAPE Online: using the internet for supporting interactions among farmers, advisers and researchers. (Poster Paper). In: Agronomy – Growing Greener Future: Proceedings of the 9th Australian Society of Agronomy Conference, Wagga Wagga, NSW, 20-23 July 1998. (Eds D.L. Michalk and J.E. Pratley), pp.679-80. (Australian Society of Agronomy: Wagga Wagga, NSW)
Probert, M.E., Carberry, P.S., McCown, R.L. and Turpin, J.E. (1998) Simulation of legume-cereal rotations using APSIM. Australian Journal of Agricultural Research, 49, 317-27. PDF
Keating, B.A., Hammer, G.L., Carberry, P.S., Freebairn, D.M., Meinke, H.M. and McCown, R.L. (1997) APSIM’s contribution to the simulation of agricultural systems. Agronomy Abstracts. p.21.
McCown, R.L., Hammer, G.L., Hargreaves, J.N.G., Holzworth, D.P. and Freebairn, D.M. (1996) APSIM: a novel software system for model development, model testing and simulation in agricultural systems research. Agricultural Systems, 50, 255-71. PDF
Carberry, P.S., Adiku, S.G.K., McCown, R.L. and Keating, B.A. (1996) Application of the APSIM cropping systems model to intercropping systems. In: O. Ito, C. Johansen, J.J. Adu-Gyamfi, K. Katayama, J.V.D.K. Kumar Rao and T.J. Rego (Eds.), Dynamics of roots and nitrogen in cropping systems of the Semi-Arid Tropics. Japan International Research Center for Agricultural Sciences, International Agricultural Series No. 3., p. 637-648.
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Carberry, P.S., McCown, R.L., Muchow, R.C., Dimes, J.P., Probert, M.E., Poulton, P.L. and Dalgliesh, N.P. (1996) Simulation of a legume ley farming system in northern Australia using the Agricultural Production Systems Simulator. Australian Journal of Experimental Agriculture, 36, 1037-48. PDF
McCown, R.L., Hammer, G.L., Hargreaves, J.N.G., Holzworth, D.P. and Freebairn, D.M. (1996) APSIM: a novel software system for model development, model testing and simulation in agricultural systems research. Agricultural Systems, 50, 255-71. PDF
McCown, R.L., Hammer, G.L., Hargreaves, J.N.G., Holzworth, D. and Huth, N.I. (1995) APSIM: an agricultural production system simulation model for operational research. Mathematics and Computers in Simulation, 39, 225-31. PDF
Keating, B.A., McCown, R.L. and Cresswell, H.P. (1995) Paddock-scale models and catchment-scale problems: the role for APSIM in the Liverpool Plains. In: Agriculture, Catchment Hydrology and Industry; Proceedings of the International Congress on Modelling and Simulation, Volume 1, 27-30 November 1995, The University of Newcastle. (Eds P. Binning, H. Bridgman, and B. Williams), pp.158-65. (Modelling and Simulation Society of Australia: Canberra, ACT) PDF
McCown, R. L., Keating, B. A., Probert, M. E., Freebairn, D. M., and Carberry, P. S. (1994). Developments in Australia in modelling the management of natural resources in agriculture and their relevance to R&D in Africa. In: Proceedings of Univ. Nairobi/Rockefeller Foundation workshop “Natural Resources Systems Modelling Workshop”, May 15-20 1994, Laikipia, Kenya.
McCown, R. L., Carberry, P. S., and Dimes, J. P. (1994). Some recent developments in the role of simulation models in farming systems research. In: Proceedings of workshop “Research and Modelling Approaches to Examine Sugarcane Production Opportunities and Constraints”, Brisbane, Nov. 10-11 1994. PDF
Hammer, G. L., McCown, R. L. and Freebairn, D. M. (1993) APSIM: the agricultural production system simulator ‑ its role and structure. In: Farming ‑ from Paddock to Plate: Proceedings of the 7th Australian Agronomy Conference, Adelaide, 1993. pp.232‑35. (Australian Society of Agronomy: Parkville, Vic) PDF
McCown, R. L., Moore, A. D. and Holzworth, D. (1993) APSIM + GrazPlan: versatile software for simulating grain‑grazing systems. In: Farming ‑ from Paddock to Plate: Proceedings of the 7th Australian Agronomy Conference, Adelaide, 1993. pp.386. (Australian Society of Agronomy: Parkville, Vic) PDF
Adiku, S. K., Carberry, P. S., Rose, C. W., McCown, R. L. and Braddock, R. (1993) Assessing the performance of maize (Zea mays) cowpea (Vigna unguiculata) intercrop under variable soil and climate conditions in the tropics. In: Farming from Paddock to Plate: Proceedings of the 7th Australian Agronomy Conference, Adelaide, 1993. pp.382. (Australian Society of Agronomy: Parkville, Vic) PDF
Carberry, P. S., Muchow, R. C., Williams, R., Sturtz, J. D. and McCown, R. L. (1992) A simulation model of kenaf for assisting fibre industry planning in northern Australia. 1. General introduction and phenological model. Australian Journal of Agricultural Research, 43, 1501‑13.
Keating, BA; Wafula, BM; Watiki, JM. (1992) Development of a modelling capability for maize in semi-arid Eastern Kenya. IN: Probert, ME (ed), A Search for Strategies for Sustainable Dryland Cropping in Semi-arid Eastern Kenya, Proc. of a symposium held in Nairobi, Kenya, 10-11 December 1990, pp. 26-33 PDF
Keating, BA; Wafula, BM; Watiki, JM. (1992) Development of a modelling capability for maize in semi-arid Eastern Kenya. IN: Probert, ME (ed), A Search for Strategies for Sustainable Dryland Cropping in Semi-arid Eastern Kenya, Proc. of a symposium held in Nairobi, Kenya, 10-11 December 1990, pp. 26-33 PDF
McCown, R. L., Hammer, G. L., Freebairn, D. M. and Keating, B. A. (1992) Modelling cropping systems. In: Modelling of Carbon and Nitrogen Cycling and Water Balance in Dryland Crop/Pasture Systems. pp.62 65. (CSIRO Division of Soils: Glen Osmond, S.A.)
Carberry, P. S., McCown, R. L., Dimes, J. P., Wall, B. H., Abrecht, D. G., Hargreaves, J. N. G. and Nguluu, S. (1992) Model development in northern Australia and relevance to Kenya. In: A Search for Strategies for Sustainable Dryland Cropping in Semi arid Eastern Kenya. (Ed. M.E. Probert), pp.34 41. (Australian Centre for International Agricultural Research: Canberra) PDF
Carberry, P. S., Muchow, R. C., Williams, R., Sturtz, J. D. and McCown, R. L. (1992) A simulation model of kenaf for assisting fibre industry planning in northern Australia. 1. General introduction and phenological model. Australian Journal of Agricultural Research, 43, 1501 13. PDF
Keating, BW; Godwin, DC; Watiki, JM (1991) Optimising nitrogen inputs in response to climatic risk. In: Muchow, RC; Bellamy, JA (eds), Climatic Risk in Crop Production: Models and Management for the Semiarid Tropics and Subtropics. CAB International, 1991, pp 329-358. [Description of advantages of CMKEN over CERES Maize.] PDF
McCown, R. L. and Dimes, J. P. (1990) CERES‑Maize: description, assessment and limitations for studies of long‑term nitrogen fertilisation. In: Proceedings of the Workshop on Long‑term Nitrogen Fertilisation of Crops. (Eds I. Vallis and G.A. Thomas), pp.85‑93. (Queensland Department of Primary Industries: Brisbane) PDF
Xu, Z. H., Chapman, A. L., Myers, R. J. K. , Saffigna, P. G. and McCown, R. L. (1990) Alley cropping maize and leucaena in the semi arid tropics: does it reduce or increase climatic risk? In: Climatic Risk in Crop Production: Models and Management in the Semi Arid Tropics and Subtropics. Poster Papers from the International Symposium, Brisbane, July 2 6, 1990. (Eds R.C. Muchow and J.A. Bellamy) pp.70 71. (CSIRO Division of Tropical Crops and Pastures: Brisbane)
Keating, B. A., Wafula, B. M. and McCown, R. L. (1990) Simulation of plant density effects on maize yield as influenced by water and nitrogen limitations. In: Proceedings of the International Congress of Plant Physiology, New Delhi, February 15 20, 1988. (Eds S.K. Sinha, P. V. Sane, S. C. Bhargava and P. K. Agrarwal), pp.547 59. (Society for Plant Physiology and Biochemistry: New Delhi) PDF
Birch, C. J., Carberry, P. S., Muchow, R. C., McCown, R. L. and Hargreaves, J. N. G. (1990) Development and evaluation of a grain sorghum model based on CERES‑Maize in a semi‑arid tropical environment. Field Crops Research, 24, 87‑104.
Carberry, P. S., Muchow, R. C. and McCown, R. L. (1989) Testing the CERES Maize simulation model in a semi arid tropical environment. Field Crops Research, 20, 297 315. PDF
McCown, R.L. and Williams, J. (1989) AUSIM: A cropping systems model for operational research. Simulation Society of Australia and International Association for Mathematics and Computers. In: Simulation 1989, Biennial Conference on Modelling and Simulation, Australian National University, Canberra, 25-27 September 1989. PDF
Hargreaves, J. N. G. and McCown, R. L. (1987) V/I CERES‑Maize ‑ a visual interactive version of CERES‑Maize. CSIRO Australia. Division of Tropical Crops and Pastures. Tropical Agronomy Technical Memorandum, No. 62, 73p. PDF