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Showing 3 results for Rezaverdinejad

S. Besharat, V. Rezaverdinejad, H. Ahmadi, H. Abghari,
Volume 17, Issue 65 (fall 2013)
Abstract

Different root water uptake models have recently been used. In this article, we use evapotranspiration data and soil water content data obtained from lysimeter measurements and root distribution in soil data obtained from olive tree to evaluate the accuracy of root water uptake models in predicting the soil water content profiles. Depth of lysimeter was 120 cm which was filled with clay-loam. Lysimeter recorded values of input and output of water and accurate value of evapotranspiration was also calculated. Soil water content distribution was measured using a TDR probe in lysimeter during the experiment. Feddes model with the root length density was used to account for the role of root distribution in soil. The flow equations were solved numerically with the measured evapotranspiration data as input, and the predicted soil water content profiles were compared with the measured profiles to evaluate the validity of the root water uptake models. The comparison showed that the average of relative error index for Feddes model was 10 %. Based on the results, about 90% of root uptake in olive tree happened at the depth of 40 centimeter
V. Rezaverdinejad, H. Ahmadi, M. Hemmati, H. Ebrahimian,
Volume 20, Issue 76 (Summer 2016)
Abstract

In this study, two different approaches of infiltration parameters estimation in traditional, variable and fixed alternate furrow irrigation, with and without cutback inflow, were performed and compared. Four usual methods including two-point (Elliott and Walker), Valiantzas one-point, Mailapalli one-point and Rodriguez and Martos optimization methods, as approaches based on advance data, and multilevel optimization method as an approach based on the advance, storage and recession data, were considered. Surface irrigation model: WinSRFR was used to simulate irrigation phases and infiltration value in each method. 13 furrow irrigation field experiments, from two case studies: Karaj and Urmia, were used to perform different methods. Based on the results, the multilevel optimization method predicted the advance and recession phases and runoff-infiltration with high accuracy for traditional, variable and fixed alternate furrow irrigation. The multilevel optimization method for traditional furrow irrigation, showed more accuracy than variable and fixed alternate furrow irrigation in advance and recession phases and the average root mean square error (RMSE) for predicting advance phase for the three furrow irrigation methods was 1.37, 1.8, and 1.57 minutes and for the recession phase was 3.76, 5.0, and 3.03 minutes, respectively. Also the multilevel optimization method for cutback options indicated high performance to advance and recession prediction and the average RMSE of advance and recession prediction were obtained 3.57 and 2.13 minutes for cutback option and 3.8 and 1.3 minutes for no cutback option, respectively. The multilevel optimization method indicated high performance in storage phase, too. The average of relative error (RE) of runoff estimation for traditional, variable and fixed alternate furrow irrigation was calculated 0.5, 0.4 and 0.4 percent, respectively. The runoff average RE of multilevel optimization method with cutback and no cutback option were obtained 1.85 and 0.85 percent, respectively; that showed high performance of this method for no cutback option in comparison with the cutback option. Therefore, the use of data of all irrigation phases to estimate infiltration parameters shows better performance in the prediction of irrigation and water balance components. (run-off and infiltration).


H. Nozari, S. Azadi, V. Rezaverdinejad,
Volume 23, Issue 1 (Spring 2019)
Abstract

Due to the growing population, crop production is one of the essential needs of the society. Since soil and water salinity can have a great impact on the crop yield loss; so, the appropriate irrigation method can be applied to reduce these effects. In this study, the system dynamics model was developed using VENSIM. The model simulated the effect of salinity and water stress on the crop yield, moisture and salinity of the root zone. In order to calibrate and validate the model results, 9 treatments data were collected from the Right Abshar Irrigation Network, on the Zayandehrud basin. After statistical analysis and calculation of RMSE index and the standard error, the fit between the measured and simulated crop yield, the moisture and salinity of root zone was calculated. The average of these indexes for all treatments was 2776.98 kg/ha and 0.07 for crop yield, 0.026 and 0.09 for soil moisture and final, 0.54 dS/m and 0.08 for the salinity of root zone, respectively. The results showed that the model could be calibrated accurately and completely in estimating the crop yield with the reasonable accuracy.


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