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Take home message Shorter season, faster maturing crops can leave residual surface water from unutilised late season rain and/or residual deep water due to shallower roots and quicker maturity Legumes such as lentils, fababeans, field pea, and chickpea often leave 20-40 mm extra residual soil water compared to canola and winter cereals Higher residual water may not remain at sowing of next crop – fallow efficiency differences between crops and seasons can influence this – e.g. low cover after legumes For summer crops, mungbean typically leaves 20mm more residual water than sorghum/maize while cotton leaves 20mm less (i.e. mungbean > sorghum/maize > cotton) Early-sown, slower maturing crops (e.g. early sown winter crops) can dry the profile deeper (>2m) and utilise deep stored soil to support higher yield in dry springs. The legacy of drier soil may warrant changes to crop sequence and management to avoid yield penalties Extra residual water at sowing can increase grain yield of subsequent crops when water is limited during the critical period for yield determination so the marginal WUE (i.e. extra yield per mm of extra soil water available) can be very high (>60kg/ha/mm) As the value of the residual water is seasonally dependent, understanding how management (crop choice, sowing dates, N management) can be adjusted to capture value from such legacies across a sequence of crops is the goal of current farming systems research.

Take home messages - Winter cereals showed improved water use efficiency (WUE) compared to legumes and summer grown crops at both Narrabri and Mungindi - Generally, dollars per mm of crop water used was greater for winter crops ($2.20) than summer grown crops ($1.30) - Although summer crops had lower WUE than winter crops there is a benefit in growing summer crops to manage root lesion nematodes - Crop choice influenced the fallow efficiency (FE). The median fallow efficiency after winter cereals equalled 0.26, whereas fallow efficiency after chickpeas equalled 0.14 - Modelling suggests a high intensity cropping rotation can be the most profitable, if crops are planted on 100mm or more plant available water (PAW).

Farming systems frameworks such as the Agricultural Production Systems simulator (APSIM) represent fluxes through the soil, plant and atmosphere of the system well, but do not generally consider the biotic constraints that function within the system. We designed a method that allowed population models built in DYMEX to interact with APSIM. The simulator engine component of the DYMEX population-modelling platform was wrapped within an APSIM module allowing it to get and set variable values in other APSIM models running in the simulation. A rust model developed in DYMEX is used to demonstrate how the developing rust population reduces the crop's green leaf area. The success of the linking process is seen in the interaction of the two models and how changes in rust population on the crop's leaves feedback to the APSIM crop modifying the growth and development of the crop's leaf area. This linking of population models to simulate pest populations and biophysical models to simulate crop growth and development increases the complexity of the simulation, but provides a tool to investigate biotic constraints within farming systems and further moves APSIM towards being an agro-ecological framework.

PR, IFPRI3; ISI; CRP2, EPTD; PIM, CGIAR Research Program on Policies, Institutions, and Markets (PIM)

In recent years, many sorghum producers in the more marginal (<600 mm annual rainfall) cropping areas of Queensland and northern New South Wales have used skip row configurations in an attempt to improve yield reliability and reduce sorghum production risk.This paper describes modifications made to the APSIM sorghum module to account for the difference in water usage and light interception between alternative crop planting configurations, and then demonstrates how this new model can be used to quantify the long-term benefits of skip sorghum production.Detailed measurements of light interception and water extraction from sorghum crops grown in solid, single and double skip row configurations were collected from on-farm experiments in southern Qld and northern NSW. These measurements underpinned changes to the APSIM-Sorghum model so that it accounted for the elliptical water uptake pattern below the crop row and the reduced total light interception associated with skip row configurations.Long-term simulation runs using long-term weather files for locations near the experimental sites were used to determine the value of skip row sorghum production as a means of maintaining yield reliability. These simulations showed a trade-off between long-term average production (profitability) and annual yield reliability (risk of failure this year). Over the long term, the production of sorghum in a solid configuration produced a higher average yield compared with sorghum produced in a skip configuration. This difference in average yield is a result of the solid configuration having a higher yield potential compared with the skip configurations. Skip configurations limit the yield potential as a safeguard against crop failure. To achieve the higher average yield in the solid configuration the producer suffers some total failures. Skip configurations reduce the chance of total failure by capping the yield potential, which in turn reduces the long-term average yield. The decision on