A technique to evaluate ENSO-based maize production strategies

Abstract

Drought occurs frequently in southern Africa, which causes harm to crop production and food security. Atmospheric and oceanic phenomena such as EL Niño/Southern Oscilation (ENSO) may be used to forecast drought. Crop production strategies could then be adapted to mitigate some of the adverse effects of drought. The aim of this work was to demonstrate a technique to determine the accuracy of ENSO-based drought predictions and to determine the efficiency of subsequent maize production mitigation strategies. The reliability of three predictors were determined by comparing hindcasted and actual drought seasons at Glen, South Africa. The PUTU maize model was then used to simulate yield of a standard production strategy and that of different drought mitigation strategies such as reduced plant population or nitrogen fertilizer application rates. Yield and gross margin of the different strategies were compared. The highest forecast reliability of 77% was obtained when a strongly negative SOI phase during November was used to forecast below normal seasonal rainfall. Agricultural drought forecasts were however unreliable. Not planting at all during drought seasons increased simulated mean gross margin by 11%. Other production strategies seemed rather inefficient.