Field evaluation of a commercial variable-rate irrigation decision support system – a study for maize and sweet corn

Abstract

ABSTRACT The agricultural sector is facing a pressing need to adopt variable-rate irrigation decision support systems (VRI–DSS) to address global challenges such as water quality, water scarcity, food security, and climate change. This study evaluated a model-based VRI–DSS for maize and sweetcorn crops in a commercial field with two soil zones and a VRI center pivot. The evaluation involved assessing the farmer’s use of the system and comparing the VRI–DSS outputs using default parameters (e.g. virtual climate data) with outputs using local data. The results showed good agreement between the virtual and local climate data (R2 = 0.94, RMSE = 0.51 °C for air temperature; R2 = 0.79, RMSE = 0.53 mm/day for evapotranspiration), except for rainfall, which was overestimated by 12% by the VRI–DSS. The soil water deficit estimates from the local data also matched well with the neutron probe measurements. The farmer applied less irrigation due to water restrictions, but water use efficiency varied between soil zones for sweetcorn. The evaluation showed that VRI–DSS, with accurate climate data, is a useful tool for estimating variable-irrigation requirements for maize and sweetcorn under one system. However, more field data and local rainfall data are required to validate the decision software system.