Comparison of nitrogen and irrigation strategies in tomato using CROPGRO model. A case study from Southern Italy

The CROPGRO simulation model was calibrated for processing tomato in Southern Italy with a 2002 data set and validated with three independent data sets with acceptable results. Subsequently this model was combined with 53 years of local historical weather data and it was used as a research tool to evaluate the benefits, risks and costs of 23 different interactive irrigation and/or N-management scenarios. Irrigation water was applied (i) on reported dates with 3 and 5 days intervals and application rates of 15 and 25 mm or (ii) with automatic irrigation initiated at residual soil moisture levels in the upper 30 cm of the soil profile of 25, 50, or 75%. Three amount levels of N application (100, 200 and 300 kg ha−1 as ammonium nitrate) were considered. A simple economic analysis, including tomato marketable yield and price, irrigation and nitrogen cost and other fixed production costs, was used to estimate expected net return for each management scenario.Based on simulation results it is concluded that irrigation scenario with low amount but with frequent applications (“3-day 15 mm” scenario) resulted in high value of irrigation water use efficiency; seasonal irrigation application between 600 and 800 mm, that are ordinary in Southern Italy, resulted in low irrigation water and N use efficiencies; a great sensitivity of tomato to N fertilization rates was observed; frequent irrigation applications combined with low N rates reduced crop stress and represented the best scenario from both a production and environmental point of view (low N leaching); the optimal average seasonal irrigation amount to reduce excessive drainage and N leaching should be approximately about 400 mm; the economic evaluation suggested the possibility to reduce irrigation water (no differences between irrigation at 75 and 50% of crop available water in the soil), but not N application, at not less than of 200 kg of N ha−1.The model was confirmed to be a useful decision support system to help the farmers to verify the optimal crop management strategy from several points of view.