Lessons on the Value of Seasonal Forecast in Three Different Wheat-Growing Environments: Paraguay, Mexico and the Southeast US.

A continuous increase in global population growth combined with an increase in seasonal climate variability raise concerns regarding uncertainties in meeting future food demand. A seasonal forecasts capability to deliver ahead-of-time information on the in-season climate could assist to improve resource management and crop production under variable climate conditions. This study aims to test the broader use of seasonal forecast in different environments, including irrigated, supplementary irrigated and rainfed systems in three wheat producing regions: Paraguay, Mexico and southeast region of the United States using the El Niño Southern Oscillation (ENSO), General Circulation Models (GCMs) and Ensembles based-forecasts. Applying an ENSO or GCM-based forecast for ENSO-season-type specific nitrogen (N) fertilizer applications resulted in benefits of >100 US$/ha when compared with current farmers’ practice of under-fertilizing in rainfed systems and over-fertilizing in irrigated systems.  When N management based on forecasts was compared with climatology (optimized N application without forecast), the benefits of the forecast was only up to 8 US$/ha, due to low forecast skill. A theoretical correct season-type forecast for wet-season-type, resulted in a positive net return of 123 US$/ha/season in rainfed systems and of 65 US$/ha/season in supplementary irrigated systems when sowing only in wet soils during the wettest tercile seasons in an arid region. GCM-based forecast for specific season-types can benefit irrigated cropping regions by optimizing N fertilizer application to reduce N cost while keeping net returns unchanged. Simple ENSO-based forecast can outperform GCM-based forecast for ENSO-season type if the ENSO signal is strong in a region.  The value of ensemble-based forecast will be explored and discussed for the Southeast US. Using climate information can significantly increase wheat yields and gross margins by tailoring resource management decisions to seasonal forecasts, but currently available forecasts need higher forecast skills before being of any significant benefits.