, Volume 229, Issue 1, pp 71-82

N rate and transport under variable cropping history and fertilizer rate on loamy sand and clay loam soils: II. Performance of LEACHMN using different calibration scenarios

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Testing of existing agronomic models is needed to ensure their validity and applicability to different soils, cropping systems and environments. Data collected from a 3-year field experiment of maize (zea mays L.) on a loamy sand and a clay loam soil were used to validate the research version of the LEACHMN model for water flow and N fate and transport. Three calibration scenarios with increasing levels of generalization for transformation rate coefficients were used based on: (i) each year, treatment and soil type (ii) 3-year average values for each treatment and soil type, and (iii) average over years and soil types. Model accuracy was tested using both graphical and statistical methods including 1:1 scale plot, root mean square error and normalized root mean square error, and correlation coefficient values. The model accurately predicted drainage water flow rate and volume under both sites. Calibrated N transformation rate constants for each treatment, year and soil type provided satisfactory predictions of growing season cumulative NO3–N leaching losses, and accurate predictions of growing season cumulative maize N uptake at both sites. The use of 3-year average rate constant values for each site resulted in fairly satisfactory predictions of NO3–N leaching losses on the clay loam site, but inaccurate predictions on the loamy sand site. The model provided accurate predictions of cumulative maize N uptake for both sites. Using the rate constant values averaged over years and soil types resulted mostly in inaccurate predictions. Use of year and soil type-specific N rate coefficients results in accurate LEACHMN predictions of N leaching and maize N uptake. When rate coefficients are generalized over years for each soil type, satisfactory model predictions may be expected when N dynamics are not strongly affected by yearly variations in organic N inputs.