JWSS - Journal of Water and Soil Science

The FAO Penman-Monteith is a baseline method to estimate reference evapotranspiration. In many cases, it is difficult to access all data, so replacing simpler models with ‎lower input data and appropriate accuracy is necessary. ‎ The purpose of this study is to investigate the capability of the experimental ‎models, gene expression programming, stepwise regression, and Bayesian network in estimating ‎reference evapotranspiration.‎ In this research, daily information of the Boroujerd synoptic station in the period of 1996 -2017 was used as model inputs. ‎Based on the correlation between input and output parameters, six input patterns were ‎determined for modeling. The results showed that the Kimberly-Penman model has the ‎best performance among the experimental models.‎ Gene expression programming with fourth pattern ‎‎and Default Model Operators (R² = 0.98 and RMSE = 0.9), Bayesian Network with sixth pattern (R²=0.91 and RMSE = 1.01), and stepwise regression with sixth pattern have the most accurate patterns at R² = 0.91 and RMSE = 0.9 in the ‎training stage.‎ Comparison of the performance of the three models showed that the gene expression ‎programming model was superior to the other two models with the Average Absolute Relative Error (AARE) of 0.12 and the Mean Ratio (MR) of 0.94.‎ The results showed that gene expression programming had an acceptable ability to estimate ‎reference evapotranspiration under the weather conditions of Boroujerd and could be introduced as a ‎suitable model.‎

Due to the lack of water resources and excessive evaporation in the country, it is necessary to have a detailed irrigation program and a suitable management method. The present research was conducted to investigate the effect of superabsorbent and mulch in Khorramabad in July 2022 in a factorial combination with a completely randomized design in three replications. The first experimental factor was irrigation water treatment in 4 levels including irrigation that provided 100% water requirement (I100), 80% of crop water requirement (I80), 60% of crop water requirement (I60), and 40% of crop water requirement (I40). The second factor included different corrective materials including plant mulch (M), superabsorbent (S), and control treatment (I). The results showed the maximum amount of wet and dry yield and crop height was related to I100-M treatment, i.e. 100 percent water requirement and compost corrective material, which were 89.52 tons per hectare, 29.42 tons per hectare, and 2.27 meters. The maximum wet and biological productivity for I40-S was calculated as 14.24 kg of wet matter per cubic meter of water and 4.75 kg of dry matter per cubic meter of water. The lowest wet and dry yields were related to I40-M, which decreased the yield of the control treatment by 6.5 percent and 0.9 percent. The lowest productivity was related to the I100-S treatment, which was calculated as 3.13 kilograms per cubic meter of water for biological productivity and 9.14 kilograms per cubic meter of water for wet weight productivity. In general, mulch had a better performance in the treatments where the water stress was low, but when the water stress increased, the performance of the mulch treatments decreased. In the superabsorbent matter, the treatments with complete irrigation or with less stress, yield decreased, but the treatments with increased stress showed better results than most of the corrective materials and the control treatment.