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Chickpea (Cicer arietinum L.) has been traditionally grown in India but is a relatively new export crop in Australia where its cultivation is expanding into new areas. The objective of this study was to identify homoclimes (i.e. similar chickpea-growing environments) in the major chickpea-growing areas of the 2 countries, using the Agricultural Production Systems Simulator (APSIM) chickpea model. The model, which processes climatic, soil, and plant information on a daily time step, was first validated and then used to simulate flowering, maturity, and grain yield of Amethyst, a mid-season cultivar, and Barwon, a full-season cultivar, on low (100 mm), medium (150 mm), and high (190 mm) water-holding capacity soils, using historical climatic data of 67 Australian and 24 Indian locations. The mean of annual outputs of flowering, maturity, and grain yield of the 2 cultivars on 3 soils was then clustered using Ward’s hierarchical complete linkage clustering procedure. At a 90% level of similarity, all the locations could be grouped into 6 homoclime clusters. The Australian locations appeared more diverse as they were present in all the clusters, whereas the Indian locations were present only in clusters 1, 2, and 6. While there were clear geographical patterns of spread of these clusters, in Australia they were not entirely related to latitude. The cluster 1 and 2 locations, which represent the largest chickpea-growing area in Australia, had homoclime locations in common with northern India. The clustering of locations appeared generally consistent with the known adaptation of chickpea in different environments of the 2 countries and therefore suggests that the methodology could be potentially used for complementing conventional approaches of introducing or exchanging germplasm, as well as determining appropriateness of breeding/testing sites.

Using economic analysis to prioritise improvements in environmental conditions is particularly difficult when multiple benefits are involved. This includes 'bundling' issues in agricultural pollution management, where a change in management action or farming systems generates multiple improvements, such as reductions in more than one pollutant. In this study, we conceptualise and compare two different approaches to analysing cost-effectiveness when varying bundles of benefits are generated for a single project investment. Each approach requires data to be transformed in some way to allow the analysis to proceed. The index approach requires the transformation on the benefits side so that the effects of multiple pollutant changes can be combined into a measure for each project which can then be compared to costs. By comparison, the disaggregation approach requires the transformation on the costs side where costs for each project have to be apportioned across the different pollutants involved. The paper provides novel insights with an application to agricultural water quality improvements into the Great Barrier Reef in Australia, demonstrating that while both approaches are effective in prioritising projects by cost-effectiveness, the disaggregation approach provides more insightful results and values that may be relevant for use as upper value guidelines in future project selection.

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Great Barrier Reef (GBR) catchments have been extensively modified over the past 150 years for agricultural production, leading to a decline in water quality entering the GBR lagoon. A joint Queensland and Australian government initiative produced the Reef Water Quality Protection Plan (Reef Plan) in 2003 in response to the decline in water quality, updating the plan in 2009 and most recently in 2013. The Reef Plan outlines a clear set of water quality and management practice targets for sediment, nutrients and pesticides. Improvement in water quality is achieved through government and landholder investment into improved agricultural management practices. A Paddock to Reef Integrated Monitoring and Modelling, Reporting program (Paddock to Reef) has been established to measure and report progress towards meeting Reef Plan goals and targets, and to assess the benefits of improved land management practices on water quality discharged to the reef lagoon. The program integrates five lines of evidence including: monitoring of practice effectiveness, prevalence of adoption of improved practices and catchment indicators through time, paddock and catchment modelling, and catchment and marine monitoring and remote sensing. Paddock to Reef is an innovative program where paddock and catchment modelling is an essential component used to report on progress towards meeting reef water quality targets. An important innovation is the linking from paddock through to catchment scale models to assess the impact of changes in management practices on end of system loads