Managing mixed wheat–sheep farms with a seasonal forecast
AbstractSeasonal rainfall forecasts have been shown to have significant skill in many parts of the world. In this study, seasonal forecasts were used together with a crop simulation model and a simple pasture growth curve to inform several decisions on year-to-year farm management, including on land-allocations in a mixed wheat–sheep farming system. In seasons where “above-median” rainfall was forecast, N fertiliser applications in cropping were increased to support the higher grain yield potential, sheep stocking rates were increased to take advantage of higher pasture growth and unused pasture land was made available for cropping. In seasons where “below–median” rainfall was forecast, N fertiliser applications in cropping were reduced to minimise costs, and traditional conservative sheep stocking rates were used. Application of the Predictive Ocean Atmosphere Model for Australia (POAMA) seasonal rainfall forecast yielded additional profit of up to A$66ha−1 per annum, equivalent to A$200,000y−1 for an average size farm in Western Australia. The largest benefit from applying a forecast in wheat–sheep farms comes from the increase of more profitable cropping during “above-median” rainfall seasons. This is well above the benefit of previous single-commodity forecast applications, and therefore has widespread potential to improve decision making on mixed crop–livestock farms. With the projected decline of rainfall in the Australian and other rain-fed crop–livestock regions of the world, skilful seasonal forecasting systems will become increasingly valuable as they will assist farm managers to capture the benefits in the declining number of potentially high-production seasons and minimise the input costs in the increasing number of low-production seasons.
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Bibliographic InfoArticle provided by Elsevier in its journal Agricultural Systems.
Volume (Year): 113 (2012)
Issue (Month): C ()
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Web page: http://www.elsevier.com/locate/agsy
Dynamical seasonal forecast; Forecast skill; Rainfall variability; Wheat–sheep farms; APSIM; POAMA;
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