Risk management tools suitable for drought management are now becoming more common world-wide, ttese tools appear to have high benefit at the broader industry level where the additional aspect of use of seasonal climate forecasting can have considerable benefit. We would argue that use of integrated agricultural management, crop simulation models, and climate forecast systems offers the highest ben efit. ttis is especially the case when applied at the whole farming system scale and across industry value chains, ttis approach has the potential to benefit industries in many areas. For example these systems can produce strategies that include:
• Improved on-farm profitability by better using scarce water resources, increasing water use efficiency and enabling higher production with consequent minimal movement of nutrients and pesticides off-farm,
• Improved planning for early season supply and better scheduling of milling operations leading to more effective use of resources (e.g. milling capacity, haulage capacity, haulage equipment, shipping, together with enhanced on-farm profitability),
• Enhanced industry competitiveness through more effective forward selling of the commoditybased on enhanced knowledge of the amount of supply and improved efficiency of commodity shipments (Everingham et al. 2002).
tte value of integrated climate/crop modelling efforts in strategic management and contingency planning can also be seen when probability distributions of a large number of simulated yields and gross margins can be produced and incorporated into risk assessment tools. Furthermore, the large number of simulations using the modelling approach allows the exploration of climate influences such as ENSO on extreme climate outcomes such as drought, a difficult approach with purely historical series that are typically short in duration (Sivakumar 2002; Pod-esta et al. 2002; Meinke and Stone 2005).
Strategic management decisions that could benefit from more integrated and targeted forecasts can be made at a range of temporal and spatial scales, ttese range from more tactical decisions regarding the scheduling of planting or harvest operations to broader policy decisions regarding land use allocation (eg. grazing systems vs cropping systems).
Hammer et al. (2001) stress that the most useful lessons for strategic management lie in the value of an interdisciplinary systems approach in connecting knowledge from particular disciplines in a manner most suited to decision-makers, tte RES AGRICOLA project is an example of evolution of the 'end-to-end' concept proposed by Mantón et al. (2000). Importantly, it distinguishes three discipline groups that need to interact closely if farmers and others impacted by drought or similar agrometeorological events are going to benefit, ttese fundamentally important discipline groups are: (i) climate sciences, (ii) agricultural systems science (including economics) and (iii) rural sociology (Meinke and Stone 2005).
Improved pay-offs for those impacted by drought are facilitated when such an integrated systems approach is employed that includes farmers, government planners, and scientists across the various disciplines which ensures that the issues that are addressed are relevant to the farmer (Meinke et al. 2001).
Hansen (2002) stressed that the sustained use of such a framework requires institutional commitment and favourable government policies. An example where links could be strengthened is in the area of connecting agricultural simulation with both whole farm economic analyses and broader government policy analyses. Using a case study, Ruben et al. (2000) reviewed the available options for adapting land use systems and labour allocation for typical households in a region in Mali, ttey showed that compensatory strategic policy devices could, at least, partial ly offset consequences of climatic patterns, largely through better-informed price policies which would enable welfare-enhancing adjustments for better-endowed farm households, while poor farmers would benefit from reductions in transaction costs.
Decision-support systems as risk management tools have often been cited as an effective means of providing output of integrated climate-agronomic information in the form of scenario analyses relating to impending drought or within the drought period that can be valuable to users. Such examples include the rainfall analysis computer package: 'Rainman' (Clewett et al. 1994); crop management planning systems: 'Wheatman' (Woodruff 1992), and 'Whopper Cropper (Nelson et al. 2002); grazing management systems: Aussie GRASS (Day et al. 2003); irrigation management systems such as 'Flowcast' (Abawi et al. 2001; Ritchie et al. 2004); and agricultural management systems: CLIMPACTS (Campbell et al. 1999); Crop-Syst (Stoeckle et al. 2003), DSSAT (Jones et al. 2003) that provide sophisticated crop simulation platforms useful for integrating and simulating future climate systems scenarios, and 'UAS' (UAS 1999). Yet, despite the amount of effort developing these systems there is also a perception that these systems have been less than ideal in their overall effectiveness (Stone and Meinke 2005). However, when used in the manner of 'discussion-support' users can engage in discussions with advisors and government agencies regarding drought patterns and crop and grazing management scenarios while maintaining ownership of the overall processes and final decision-making. In this way discussion-support systems move beyond traditional notions of supply-driven decision-support systems and can compliment participative action research, tte critical role of interaction and dialogue among the key participants impacted by drought - strategic planners, policy agencies, farmers, advisors, crop modellers, and climate or meteorological scientists - is paramount (Plant 2000; Podesta et al. 2002; Nelson et al. 2002).
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