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Understanding the implications of replacing fallows with cover crops on plant-available water (PAW) and soil mineral nitrogen (N) and their carry-over effects on subsequent cash crops is critical for understanding their potential for ecological intensification in water-limited environments. We modelled the impacts of different cover crop functional types over historical climate to predict how climate variability influences soil water and N acquisition and subsequent availability to a maize crop in a dryland farming system of subtropical Australia. Following local validation of simulation models (APSIM) with 3-site-years of field data, 70 years of crop-fallow rotations were simulated comparing conventional fallow against a diverse range of cover crops comprising monocultures and mixtures of grass vs. legume vs. brassica. Cover crops consistently reduced soil water and mineral N at maize sowing compared to conventional fallow. In dry to normal precipitation years, this induced a maize yield penalty of up to − 18% relative to fallow, primarily due to reduced water availability. In wet years, increased in maize grain yield (+4%) was predicted following legume and grass-associated cover crop mixtures with concomitant reductions in N leaching and soil surface runoff of up to 40%. Cash crop yields following grass-cover crops were more stable and carried lower downside risks; multi-species (grass-legume-brassica) cover crop mixtures carried higher yield penalties and greater downside risks due to high biomass accumulation and high soil water extraction. These long-term predictions in water-limited environments indicate that increasing cover crop complexity by using mixtures with diverse functional traits can lead to a greater risk of yield losses and increased yield instability unless they are managed differently to monoculture cover crops. Therefore, for successful integration of cover crops into dryland agroecosystems, cover crops should be considered as a flexible choice grown under favourable precipitation and economic scenarios rather than for continuous fallow replacement. • Applied APSIM to assess potential dryland fallow replacement cover crop options. • Cover crops reduced yields by 12% relative to fallow in dry to normal years. • Predicted yield gains in wet years following fababean and multi-species mixture. • Dryland cover crops should be considered as an opportunistic practice. [ABSTRACT FROM AUTHOR]

As a rainfed, short-season crop, mungbean is a particularly attractive summer rotation option for Australian farmers, but the rate of mungbean adoption in Australia is low due to its high yield instability. A lack of research conducted on modern mungbean in Australia has hindered farmers' ability to understand how to best manage the crop and close the yield gap. The aim of this study was to provide recommendations for optimal sowing windows (balancing maximum yield potential with minimum risk—i.e. instability and crop failure). We simulated 60 years of growing mungbean at 180 different sowing times, four different initial soil water levels and at seven sites across Queensland and New South Wales using the new Agricultural Production Systems sIMulator Next Generation (APSIM NextGen) Mungbean model. We then calculated the impact of sowing date on mungbean water use efficiency and on the soil water deficit for the subsequent crop in the rotation. Higher initial soil water levels decreased risk (instability and failure) at all sites. Arid sites with high evaporative demand had optimal sowing windows later (February) in the growing season. More temperate sites yielded better with higher levels of stability when sown between November and January. Sowing in September/October is not recommended in any site as it coincided with low yield stability and water use efficiency. Not all sites had a clear optimal sowing window. We conclude, therefore, that in some environments, sowing time can only marginally reduce risks in growing mungbean. We identified optimal sowing window that can reduce risks of a failed crop by 20 % and increase stability without losing yield potential. The timing of the optimal sowing window for a given site appears to be influenced by avoiding periods with high evaporative demand during the reproductive phase. Modelling has been critical for exploring the trade-offs between maximizing and stabilizing mungbean yields over a wide range of environments and growing seasons to determine the optimal sowing windows across the main growing environments in Australia. • Optimal sowing windows were identified for mungbean in Australia. • Aridity and Vapor Pressure Deficit influenced the timing of optimal sowing windows. • Spring sowing corresponds to high yield instability and low water use efficiency. [ABSTRACT FROM AUTHOR]