Evaluation of SWAP model in estimating soil water content, salinity and yield of three forage maize cultivars under saline water use conditions

Document Type : Research Paper


1 PhD student in Irrigation and Drainage, Department of Irrigation and Reclamation Engineering, faculty of Agricultural Engineering & Technology, university of Tehran, Karaj, Iran.

2 Associate Professor, Department of Irrigation and Reclamation Engineering, Faculty of Agricultural Engineering and Technology, Collage of Agriculture and Natural Resources, University of Tehran, Karaj, Iran.

3 M.Sc. Graduated, Department of Irrigation and Reclamation Engineering, Faculty of Agricultural Engineering and Technology, Collage of Agriculture and Natural Resources, University of Tehran, Karaj, Iran.


In order to evaluate the SWAP model a study was conducted in 2017 in the farm of the Department of Irrigation and Reclamation Engineering, University of Tehran, located in Karaj as a factorial experiment in a randomized complete block design. The treatments consisted of three maize hybrids SC-704, SC-400 and SC-260 (V1, V2 and V3, respectively) and three levels of irrigation water salinity 0.7, 3 and 5 dS m-1 (S1, S2 and S3, respectively). In each maize cultivar, for the model calibration, the crop yield data measured in the field from the salinity level of irrigation water 3 dS m-1 and for its validation, the salinity levels of 0.7 and 5 dS m-1 were used. Also, to evaluate the model in estimating soil moisture and salinity, field data of V1S2 (calibration) and V1S3 (validation) were used. Based on the obtained results, SWAP model has a good performance in estimating soil moisture so that in the validation stage in three soil layers (0-20, 20-40 and 40-60 cm) with RMSE (Root Mean Square Error) of 0.03, 0.03 and 0.04 cm cm-3 respectively and has a good accuracy in predicting soil salinity of 0-20 cm surface layer (RMSE = 0.67 mg cm-3) but with increasing soil depth, the accuracy of the model decreases so that RMSE of 1.16 and 1.19 mg cm-3 were obtained in two layers of 20-40 and 40-60 cm, respectively. The SWAP model detected the inherent differences between different cultivars of maize and the best simulation results were obtained for SC 704.


Main Subjects

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