Using RZWQM to simulate the fate of nitrogen in field soil–crop environment in the Mediterranean region

Abstract

This paper presents an evaluation of the root zone water quality model (RZWQM) for assessing the fate of N in the soil–crop environment at the field scale in Portugal under two distinct agricultural systems; one consists of a grain corn planted in a silty loam soil with level basins (flood) irrigation and the other a forage corn planted in a sandy soil with sprinkler irrigation. Water balance and crop growth were reported in a previous study [Cameira, M.R., Fernando, R.M., Ahuja, L., Pereira, L.S., 2005. Simulating the fate of water in field soil–crop environment. J. Hydrol. 315, 1–24] using RZWQM. This study reports RZWQM simulated nitrogen transformation, uptake and transport in the two soil–crop systems with emphasis on the calibration of the soil organic matter pools and selected soil N transformation processes (mineralization, hydrolysis and nitrification), using 2 years of data (1996 and 1997). The criterion for model calibration was that the root mean square error (RMSE) of the simulations was lower than the average standard deviation of measured data (MSD) for the simulation period. A third year (1998) was used to validate the model performance under four different fertilization management practices. Predicted corn grain yield was within 1.1% of measured values. The error varied between −10 and 2.4% for forage corn. N uptake was predicted with an error of 2.8% for grain corn and between −13 and −3% for forage corn. For the silty loam soil and during the crop season, nitrate-N in the soil profile was predicted with a RMSE lower than the MSD. For the sandy soil, RMSE was lower than MSD for one fertilizer treatment and slightly higher for the other two treatments. The prediction of the residual nitrate-N in the soil, after crop harvest, presented errors ranging from 18 to 37%. The results show that the model was able to predict N related variables for the two soil–crop systems and for the different boundary conditions (irrigation and fertilization) with a good accuracy.