Modelling agricultural nitrogen losses to enhance the environmental sustainability under Mediterranean conditions

Abstract

In intensive agricultural systems, irrigation and nitrogen (N) fertilizer are the most important factors that influence crop production and N losses. This work aimed to evaluate the N best management practices using the calibrated and validated Decision Support System for Agro-technology Transfer (DSSAT) model for maize (short and long season), wheat, barley, sunflower and alfalfa in the Violada Irrigation District (VID, Northeast Spain) to reduce the impact of N losses on irrigation return flows quality. In total, 59 farmers’ field plots were investigated from 2014 to 2017 crop seasons distributed in the different soil types in the VID in order to assess the current and optimum N fertilization and the combined irrigation and N fertilization management practices. Considering the whole cultivated crop area in each soil type of the VID and comparing with the current N fertilization, results showed that the optimum N management could reduce the NO3–N leaching below root zone by 51 % and residual NO3–N in soil by 58 %. These reductions could be improved further by 35 % and 3 %, respectively, under the combined N fertilization and irrigation optimum management. The more vulnerable soils for NO3–N leaching (shallow and/or very permeable soils) were also identified. As for the impact of individual crops, the model identified that both long and short season maize were the most polluting crops (84 % of total N leached) due to the heavy fertilization applied by the local farmers that exceed crop requirements by more than 50 %. Moreover, the recommended irrigation and N fertilization could reduce N2O–N emissions by 60 %, the triple than under the recommended N fertilization alone. This study supports the potential of the DSSAT model to incentivize farmers to adjust their N fertilizer and irrigation practices to crop requirement and soil properties to ensure production while improving environmental sustainability.