Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6368316 | Agricultural Systems | 2016 | 11 Pages |
â¢In fully irrigated systems, simulated yield variability was caused by solar radiation.â¢Varying N fertilizer according to seasonal forecast could save 26 USD ha/seasonâ¢Under limited irrigation, guiding management using a seasonal forecast can result in a net return of 65 USD/ha.â¢Under rainfed situations, guiding crop management using forecasts can result in a net return of 123 USD/ha.
Half of global wheat production occurs in irrigated cropping regions that face increasing water shortages. In these regions, seasonal forecasts could provide information about in-season climate conditions that could improve resource management, helping to save water and other inputs. However, seasonal forecasts have not been tested in irrigated systems. In this study, we show that seasonal forecasts have the potential to guide crop management decisions in fully irrigated systems (FIS), reduced irrigation systems (supplementary irrigation; SIS), and systems without irrigation (rainfed; RFS) in an arid environment. We found that farmers could gain an additional 2 USD haâ 1 seasonâ 1 in net returns and save up to 26 USD haâ 1 seasonâ 1 in N fertilizer costs with a hypothetical always-correct-season-type-forecast (ACF) in a fully irrigated system compared to simulated optimized N fertilizer applications. In supplementary irrigated systems, an ACF had value when deciding on sowing a crop (plus supplementary irrigation) of up to 65 USD haâ 1 seasonâ 1. In rainfed systems, this value was up to 123 USD haâ 1 when deciding whether or not to sow a crop. In supplementary irrigated and rainfed systems, such value depended on initial soil water conditions. Seasonal forecasts have the potential to assist farmers in irrigated, supplementary irrigated, and rainfed cropping systems to maximize crop profitability. However, forecasts currently available based on Global Circulation Models (GCM) and the El Niño Southern Oscillation (ENSO) need higher forecast skill before such benefits can be fully realized.