A M; M KH; A A; P SH
Abstract
In order to study the effect of limited irrigation on increasing the yield and water productivity of soybean, a split plot experiment based on a randomized complete block design with four replications was conducted in two cropping seasons of 2013 and 2014, in Rasht. Three irrigation treatments including ...
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In order to study the effect of limited irrigation on increasing the yield and water productivity of soybean, a split plot experiment based on a randomized complete block design with four replications was conducted in two cropping seasons of 2013 and 2014, in Rasht. Three irrigation treatments including two irrigations (I2): irrigation at flowering and pod formation stages, three irrigations (I3): irrigation at flowering, pod formation and ripening stages, and rainfed (I0): as control treatment were allocated to the main plots and three soybean genotypes including Williams (V1), L17 (V2), and Habbit (V3) to subplots. During the critical growth stages of the plant, based on the irrigation treatment and considering the precipitation and available moisture in the root zone, only one irrigation was applied (I1) in 2013 while Williams and Habbit genotypes were, respectively, at pod formation and at flowering stage. But, in 2014 crop season, considering the lower precipitation, all irrigation treatments were conducted. Yield and yield components were measured at seed ripening time. The results showed that the limited irrigation in both years improved yield and yield components of all soybeans genotypes. The highest average grain yield in both crop seasons were obtained with I1V2 and I3V2 treatments, being 4616 and 4198 kg/ha, respectively. In both cropping seasons of 2013 and 2014, L17 genotype had the highest average grain yield compared with the other two genotypes, being 3932 and 3000 kg/ha, respectively, therefore, it can be recommended for planting in Rasht region. In 2013 and 2014 crop seasons, respectively, I1V2 and I3V2 treatments had the highest water productivity, corresponding to 1.72 and 0.97 kg/m3.
m gh; m kh; m b; p sh
Abstract
Today, use of drip irrigation systems for row crops is widespread. One of these systems is subsurface drip irrigation. Knowing the dimensions of the wetting pattern is essential for drip irrigation system design. To design a proper system, as field experiments are time consuming and expensive, using ...
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Today, use of drip irrigation systems for row crops is widespread. One of these systems is subsurface drip irrigation. Knowing the dimensions of the wetting pattern is essential for drip irrigation system design. To design a proper system, as field experiments are time consuming and expensive, using computer models is recommended. In this regard, the present study examined the performance of three models including empirical Kandelous et al. model, analytical WetUp, and numerical HYDRUS-2D models in subsurface tape irrigation. Treatments included three volumes of water i.e. 10, 15, and 20 liters per meter length of tape and three installation depths of 10, 20, and 30 cm, in three replications. Comparison between the measured and simulated wetting dimensions were made by using four statistical indices i.e. RMSE, nRMSE, CRM, and MAE. RMSE values of horizontal wetting extension for Kandelous et al and HYDRUS-2D models were 0.051 and 0.066 m, respectively, while for vertical wetting extension, the values of RMSE were 0.052 and 0.078 m, respectively. nRMSE values of horizontal wetting extension for Kandelous et al. and HYDRUS-2D models were 15.46% and 19.71 %, respectively, being in class ‘good’. nRMSE values of vertical wetting extension for Kandelous et al and HYDRUS-2D models were 15.99 and 23.74 %, respectively, considered as ‘good’ and ‘fair’, respectively. Statistical indices calculated for WetUp model was not in acceptable range. For horizontal and vertical wetting dimensions, CRM and MAE indices for Kandelous et al model were the lowest values. Overall, the Kandelous et al model had the best estimation.
Hedyeh Pouryazdankhah; Mohammadreza Khaledian
Abstract
In most cases, to predict soil moisture status before installing irrigation system, some simulations are performed by mathematical models to achieve a correct design and supply plant water requirement. Furthermore, nowadays, to increase water use efficiency, no-tillage system is being considered by many ...
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In most cases, to predict soil moisture status before installing irrigation system, some simulations are performed by mathematical models to achieve a correct design and supply plant water requirement. Furthermore, nowadays, to increase water use efficiency, no-tillage system is being considered by many experts, because of its high water saving potential. In this study, the performance of HYDRUS-2D has been assessed for both systems i.e. conventional and no-tillage systems. Hence, a field under corn crop and irrigated with tape drip irrigation was considered for each system, in south of France in a Mediterranean climate. Soil moisture at different depths was measured by a neutron probe before and after irrigation in the experimental fields and was compared with simulated moisture according to two statistical indices, i.e. RMSE and EF. In the conventional tillage system, considering the temporal variability of soil hydraulic properties before irrigations, the model could not satisfactorily simulate the whole 29-day study period; because ploughing caused increase in pores of the soil and, consequently, increased soil hydraulic conductivity (Ks). After the first irrigation, Ks was reduced because of the compaction of the first layer, which resulted in some discrepancies in model simulations, where accounting temporal variability of soil hydraulic properties improved the simulations of model. But, in no-tillage system, by accounting soil hydraulic properties before irrigations as input, the model could simulate the whole study period, because in this system, structure of the soil and, consequently, soil Ks changed negligibly and, therefore, the model could simulate more realistic results.