APSRU PROJECT SUMMARY NO. 88
Project Title: Application of simulation to multiple goal assessment in agricultural systems
Project Supervisor: Dr Holger Meinke, Dr Peter Carberry
Funding Body: GRDC
Admin Contact: Marshall Mackay
Commencement Date: 01/07/99 Completion Date: 30/11/99
Aims:
Research Proposal Summary:
During a three and half month sabbatical leave in early 1998, Dr. Rossing worked with APSRU on developing a methodology that used an iterative optimisation approach to explore crop rotation strategies using the APSIM systems model. Unfortunately, due to family reasons, Dr Rossing had to return early to The Netherlands at a stage when the emerging methodology was only in a prototype stage. While Dr Rossing has continued to progress this research area since his return to The Netherlands, its completion to a deliverable point requires further close interaction between APSRU researchers and Dr Rossing. This proposal is aimed at supporting a Dr Rossing for a 3 month visit to APSRU in order to bring the development of the methodology to fruition.
Optimisation of cropping systems requires algorithms that can deal with the lack of mathematical tractability of the function to be optimised. Such algorithms are found in the class of stochastic global optimisation algorithms and include algorithms such as Nelder-Mead, Powell and, more recently, simulated annealing (SA) and genetic algorithms (GA). In recent years, SA and GA have been used successfully to find global optima in problems that have proved intractable using mathematical programming approaches. While successful in finding global, rather than local optima, SA and GA are also extremely demanding on computation time, requiring many thousands of function evaluations (= simulation model runs) before converging. Thorough model analysis resulting in intelligent choice of parameters to be optimised may remedy part of this problem. For instance, in Dr Rossings early work with APSRU two alternatives are being investigated for optimisation of a cropping system consisting of cotton, sorghum, wheat, chickpea, summer fallow and winter fallow: (1) optimisation of the threshold value of available soil water for planting, versus (2) optimisation of crop type planted. Extensive experience exists at WAU in the area of global. While the methods employed in this proposal, such as global optimisation algorithms (in particular genetic algorithms) and dynamic simulation models, have been around for one (GA) or more decades, their application to cropping systems is innovative. Linear programming approaches such as MIDAS and MUDAS consider only a small number of pre-defined rotations. Linear programming is not capable of capturing the suit of crop types in eastern Australian cropping systems nor is it suitable for effectively representing the pervading yield uncertainty due to rainfall events. The proposal contains traits of both strategic basic research by exploring the merger of a dynamic model of cropping systems of north-east Australia and optimisation, and applied research by attempting to use the simulation model to demonstrate trade-offs between economic and resource base indicators.
Potential Outcomes:
Project Publications: