Soil Salinity and Tomato Yield Simulation Using SALTMED Model in Drip Irrigation

Abstract

In this research, the SALTMED model was used for soil salinity and yield prediction using data from a tomato field experiment. Surface and subsurface drip irrigation systems were used to study the interaction of irrigation water salinity levels and irrigation management practices in a complete randomized, split-plot design with three replications in which irrigation management strategies were the main plots and different levels of water salinity including 0.68, 2, 4, 6, and 8 dS m−1 were subplots. Irrigation management strategies were irrigation with alternately saline and nonsaline water (m1) and irrigation with saline water in the first half of each irrigation event followed by fresh water in the second half (m2). The results of the surface drip irrigation and subsurface drip irrigation systems were used for calibration and validation of the model, respectively. The results showed that the differences (P<0.05) between the predicted and measured tomato yield and soil salinity in the calibration and validation of the model are not significant. The values of statistical parameters including index of agreement (d) and normalized root-mean-square error (NRMSE) showed that the accuracy of the model was acceptable. Soil salinity in the m1 strategy was predicted with higher accuracy than the m2 strategy for surface and subsurface drip irrigation.