Modelling dryland agricultural systems

Abstract

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.