University of Tehran Press Iranian Journal of Soil and Water Research 2008-479X 50 6 2019 10 23 Parameterization and Evaluation of the DSSAT-CANEGRO Model for Sugarcane CP57-614 in Khuzestan Climate Condition Parameterization and Evaluation of the DSSAT-CANEGRO Model for Sugarcane CP57-614 in Khuzestan Climate Condition 1331 1340 73206 10.22059/ijswr.2018.259986.667944 FA Mahboobe Ghasemi Ph.D. Student of Irrigation and Drainage, Shahid Chamran University of Ahvaz, Ahvaz, Iran Abdali Naseri Professor of Irrigation and Drainage, Shahid Chamran University of Ahvaz, Ahvaz, Iran 0000-0002-5833-5802 Hadi Moazed Retired professor of Irrigation and Drainage, Shahid Chamran University of Ahvaz, Ahvaz, Iran Journal Article 2018 09 25 The purpose of this study was to calibrate and evaluate DSSAT-CANEGRO Modelusing field data from two datasets for cultivar CP57-614, in Khuzestan. The experimental plan was performed at three levels of irrigation water (full and deficit irrigation) with three replicates in a completely randomized block design during cultivation years of 85-86 and 94-95. First of all, model calibration was done to find out the important input parameters by GLUE method. DSSAT-CANEGRO Model consists of 20 Genetic parameters. In order to reduce some parameters, parameterization was conducted using field data. The comparison between predicted and measured data showed that the model efficiency was 0.69 to 0.75 for aerial dry mass, 0.67 to 0.7 for stalk dry mass and 0.18 to 0.25 for sucrose. The results indicated that the sucrose prediction by CANEGRO model is weak as compared to other parameters. This is due to measuring sucrose at the end of grown season. The purpose of this study was to calibrate and evaluate DSSAT-CANEGRO Modelusing field data from two datasets for cultivar CP57-614, in Khuzestan. The experimental plan was performed at three levels of irrigation water (full and deficit irrigation) with three replicates in a completely randomized block design during cultivation years of 85-86 and 94-95. First of all, model calibration was done to find out the important input parameters by GLUE method. DSSAT-CANEGRO Model consists of 20 Genetic parameters. In order to reduce some parameters, parameterization was conducted using field data. The comparison between predicted and measured data showed that the model efficiency was 0.69 to 0.75 for aerial dry mass, 0.67 to 0.7 for stalk dry mass and 0.18 to 0.25 for sucrose. The results indicated that the sucrose prediction by CANEGRO model is weak as compared to other parameters. This is due to measuring sucrose at the end of grown season. https://ijswr.ut.ac.ir/article_73206_09e5dbdf8a3bd6dccce5621459b11e26.pdf