CONTEXT: Expectations are mounting on cropping systems to satisfy objectives across social, economic, and environmental dimensions. To identify cropping systems with an enhanced capacity to deliver on these diverse objectives, it is essential to understand both how these systems perform for a wide range of quantifiable performance metrics and the extent of synergies and trade-offs between these metrics, as they describe the underlying system's processes and properties. Such knowledge is presently lacking for dryland cropping systems in the southern grains region of Australia (SGR), one of the largest global grain production regions. OBJECTIVE: This study (1) evaluates the performance of different cropping systems in the SGR for a range of performance metrics and (2) explores the relationships between these metrics for the range of case studies considered. METHODS: Using the process-based crop model, APSIM, we simulated the water-limited production potential of different cropping systems across diverse environments, from which performance metrics were computed to describe key system processes and properties. A total of 16 systems, with varying cropping diversity and intensity, were evaluated using 14 performance metrics spanning six objectives. Three case studies collectively represent key variabilities in climate and soil within the SGR. RESULTS AND CONCLUSIONS: No single cropping system consistently outperformed others across all performance metrics. The 'baseline' systems, which reflect the most commonly adopted system in given regions, were generally not the top performers across several key metrics, highlighting some potential opportunities for performance improvements. Systems achieving higher productivity (e.g., water use efficiency (WUE)), were generally associated with improved environmental outcomes across all study areas, including lower CO2-e emissions and decreased relative soil loss. In addition, while higher WUE was linked to greater gross margins (GM) in the low- and high-rainfall zones, this relationship was not as evident in the mid-rainfall zone. Synergies were strongest for the high rainfall zone case study, where the correlation coefficients were 0.94 between WUE and GM, and -0.72 between WUE and CO2-e emissions. Trade-offs and synergies were influenced by both siteand system-specific factors. SIGNIFICANCE: Our findings highlight that identified synergies between economic and environmental metrics could serve to enhance confidence in growers regarding strategic cropping decisions. Our findings offer regionspecific insights that can help inform decisions towards more sustainable and profitable cropping systems, while some relationships that were found to be independent of system and sites may be applicable to other cropping regions in similar dryland farming worldwide.