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Showing 2 results for Hemmati

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).


A. Hemmati, H. Asadi Rahmani,
Volume 22, Issue 4 (Winter 2019)
Abstract

In order to study the effects of rhizobium bacteria and arbuscular mycorrhizal fungi on water use efficiency and the grain yield of bean, under drought stress conditions, two-year year field experiments were conducted during 2015 and 2016 growing seasons. The experimental design was a split plot arranged in an RCBD with 4 replications. Three irrigations including S1= 95-100% AW (Normal irrigation), S2= 75-80% AW(Moderate drought stress) and
S3= 55-60% AW (severe drought stress) were assigned to the main plots and six bio fertilizer treatments including T1=177 rhizobium bacteria strain, T2=160 rhizobium bacteria strain used for seed inoculation, T3= mycorrhizal arboscular fungi used for soil inoculation, T4= T1+T2, T5= T1+T2+T3 and T6= control (no seed and soil inoculation) were randomized to the subplots. Based on the combined analysis of variances for two years, there were significant differences (p˂0.05) in the grain yield, yield components and water use efficiency between the irrigation stress and bio fertilizer treatments. The highest grain yield (2371 kg ha-1) and water use efficiency (522 g m-3) were obtained in the S2T2 treatment. In this treatment, 160 and 177 rhizobium bacteria (T2) in moderate drought stress (S2) were used. These results suggested that inoculation with the rhizobium of seed bean in arid and semi-arid areas could improve yield, water use efficiency and resistance to drought stress by increasing the growth in the root and shoot of the plant.


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