Modelling dryland agricultural systems

Rodriguez, Daniel, de Voil, Peter and Power, B. (2017). Modelling dryland agricultural systems. In Muhammad Farooq and Kadambot H. M. Siddique (Ed.), Innovations in dryland agriculture (pp. 239-256) Cham, Switzerland: Springer . doi:10.1007/978-3-319-47928-6_9

Author Rodriguez, Daniel
de Voil, Peter
Power, B.
Title of chapter Modelling dryland agricultural systems
Title of book Innovations in dryland agriculture
Place of Publication Cham, Switzerland
Publisher Springer
Publication Year 2017
Sub-type Research book chapter (original research)
DOI 10.1007/978-3-319-47928-6_9
Open Access Status Not yet assessed
ISBN 9783319479286
Editor Muhammad Farooq
Kadambot H. M. Siddique
Chapter number 9
Start page 239
End page 256
Total pages 18
Total chapters 20
Language eng
Abstract/Summary Irrespective of levels of endowment or investment, both large scale commercial and smallholder farmers face different though equally challenging and complex problems and opportunities, requiring new science and tools. We started modelling dryland agricultural systems in the early 1990s. Since then, value of the technology has been shown across multiple applications and disciplines, though particularly in (i) the synthesis and integration of knowledge about the functioning and dynamics of rainfed agricultural systems, where biotic processes interact with climatic, soil and biological drivers at a range of temporal and spatial scales; and (2) informing (and overcoming) the complexities in the management and improvement of dryland agricultural systems, both at the level of crop (G×M), cropping systems, farming systems, and farm business design. Here we provide a summary of our achievements in the use of modelling tools in dryland agricultural systems, and provide examples of the important opportunities for the development and application of integrative approaches in farming systems design to support the medium to long-term transformational changes required in our dryland agricultural systems. Particular emphasis is given to the role of modelling tools to quantify benefits and trade-offs in the management of crops and farm businesses in highly-variable climates; and the medium and longer term benefits from changes in strategies, farming systems designs and allocation of limited resource. We also propose that field crops research will increasingly require cross-links between disciplines integration and participatory approaches to allow for the sustainable intensification of agricultural production, and that the modelling agricultural systems will continue to be a crucial tool in making better informed decisions across a range relevant scales, the crop, the farm, the landscape and region.
Keyword Agricultural production systems simulator
Cropping systems
Farming systems
Smallholder farmers
Water use efficiency
Q-Index Code B1
Q-Index Status Provisional Code
Institutional Status UQ

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