Rapid population increases, along with water resources deficiency, have made agricultural experts and researchers use various management techniques to improve water productivity. The term, "more crop per drop" has since came to the center of attention. One of the primary objectives in Iranian national agricultural policies is providing food security, which can be reached via this approach. There is a crucial need for improvements in production of rain-fed agriculture since there are huge rainfed cultivated areas that suffer from low yields. Hence, in this research, supplemental irrigation and sowing dates, which are two effective factors on productivity of rainfed lentils in Qazvin Plain, are investigated. The treatments included two sowing dates and four irrigation levels. The sowing dates were April 4 and April 14, and the irrigation treatments were: no irrigation, single irrigation at seedling stage, single irrigation at pod filling stage, and double irrigation at both of these stages. A factorial experiment in a completely randomized block design with three replications was conducted in agricultural research field of Imam Khomeini International University for two cropping seasons in 2011-2012. The results showed that the effects of the two factors on grain yield and biomass were highly significant at the 1% level, both separately and simultaneously. The sowing date of April 4 led to a rise in yield components. Although the double irrigation treatment with 1,329.4 kg=ha had the most grain yield, the single irrigation treatment at seedling stage with the irrigation water productivity of 1.878 kg=m 3 was the best approach when water productivity was considered. In summary, the results indicated that single irrigation at the seedling stage had better water productivity than the double irrigation treatment. This conclusion is consistent with the production functions and other research results.

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Soil salinity is an important parameter in irrigation, drainage, and environmental studies. Determining the electrical conductivity of soil saturated paste extract (ECe) is a well-known method, but its use is limited because its production process is time-consuming and difficult. The 1:5 solution electrical conductivity (EC 1:5) is an alternative simplified method. The aim of this study was to evaluate ECe-from-EC 1:5 conversion models. A total of 123 samples from 3 soil layers were analysed. The research was planned in two phases: 1) model evaluation in soil layers, 2) model evaluation in ECe categorized data. Results show that the linear model was the best model in the second layer (R 2 = .66, mean absolute percentage error [MAPE] = 0.058), and the exponential model was the best in the other layers (R 2 = .65 to 0.67, MAPE = 0.085 to 0.060). Also, exponential and linear regressions were the best ECe estimation models in the ECe < 4 and ECe > 4 categories, respectively. In addition, the conversion factor (f) for converting ECe and EC 1:5 was obtained as 3.7-13.9, 2.8-5.0, and 3.4-5.8 for three soil layers, respectively. Results show that the use of general recommendation tables for f will lead to considerable error, and the factor must be determined specifically for each region.

Sustainable agriculture can contribute to food security in arid and semi‐arid regions if soil salinity in the root zone is kept under control. Recently, experts have been concentrating their research towrds alternative and environmentally friendly solutions. In this study, dry drainage was evaluated as a sustainable and cost‐effective alternative technique, by means of both field experiments and a numeric approach based on the HYDRUS‐2D modelling environment. Results showed that soil salinity in the cropped area increased from the soil surface to the bottom, and soil salinity movement (transport direction) was from the cropped to uncropped area. Increasing the ratio of cropped to uncropped width led to an increase in soil salinity of the cropped root zone and lack of stabilization of salinity concentration. Results of modelling showed that there are no significant differences between observed and modelled data, even though HYDRUS‐2D simulated soil water content better than soil salinity. Averages of performance indices for simulated soil water content (SE = 0.08, NRMSE = 0.133) were better in comparison with simulated soil salinity (SE = 0.28, NRMSE = 0.262). Soil surface salinity in the cropped area increased 2.7 times (from 2.1 to 5.7 dS m−1) during the experiment for equal cropped to uncropped width (1 (cropped): 1 (uncropped)), and by increasing cropped width (2 (cropped): 1 (uncropped)) it increased 7.5 times (from 2.3 to 17.3 dS m−1). Copyright © 2017 John Wiley & Sons, Ltd.

Understanding the intraseasonal sensitivity of crop evapotranspiration (ET) to stresses allows for accurate modelling of crop yield. In this research, the effects of water salinity stress and soil nitrogen deficiency on evapotranspiration (in the growth stages) and maize yield in 2017 and 2018 were investigated.Four treatments of saline water levels of 0.5 (S 0 ), 2.1 (S 1 ), 3.5 (S 2 ) and 5.7 (S 3 ) dS m À1 were combined with four nitrogen fertilization levels of 100% (N 0 ), 75% (N 1 ), 50% (N 2 ) and 25% (N 3 ). The maize ET amounts from the S 0 N 0 to S 3 N 3 treatments decreased from 80 to 55 mm (in the initial stage), 202 to 129 mm (in development), 127 to 80 mm (in the mid) and 14.5 to 10.5 mm (in the late). The dry biomass yield of maize from the S 0 N 0 to S 3 N 3 treatments was equal to 15.3 to 9.23 t.ha À1 . The relative yield of maize was modelled by the additive models of Blank, Stewart and Singh and the multipliable models of Jensen, Rao and Minhas. The results showed that the Stewart and Jensen models were selected as the optimal models. By using the optimal models, the relative yield of maize can be modelled based on the evapotranspiration rate (in the growth stages) under salinity stress and nitrogen deficiency.