Irrigation
R. Saeidi
Abstract
IntroductionSalinity stress causes reduction of crop evapotranspiration (ETc) and yield. An unsuitable seed planting date can result in negative atmospheric effects, such as temperature stress, during the crop growth period. Consequently, salinity stress and unfavorable climatic conditions during this ...
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IntroductionSalinity stress causes reduction of crop evapotranspiration (ETc) and yield. An unsuitable seed planting date can result in negative atmospheric effects, such as temperature stress, during the crop growth period. Consequently, salinity stress and unfavorable climatic conditions during this period interact to reduce crop water uptake. The mentioned conditions effect, should be investigated on crop transpiration amount (actual water requirement) and soil surface evaporation losses. This research results will have a determinative effect on the optimal use of water resources. Materials and MethodsThe studied crop in this research was S.C 704 maize. The crop planting was conducted in mini-lysimeters with a diameter of 40 cm and a height of 70 cm. The experiment factors included soil salinity stress and seed planting date. Soil salinity treatments were selected at four levels of 1.7 (S1), 2.5 (S2), 3.8 (S3), 5.9 (S4) dS.m-1. Seed planting date included of 5 May (P1), 25 May (P2) 14 June (P3) and 4 July (P4). Crop growth period for all planting date treatments, was 140 days (FAO-56). Experiment was conducted as factorial based on completely randomized design with 16 treatments and three repetitions. Variance analysis and average comparison of data was done by SPSS software and with Duncan's multi-range test (at 5% probability level). Daily soil moisture amount was measured by a moisture meter. Irrigation time was determined for without water stress conditions. Readily available water limit was determined 0.4. Irrigation volume was calculated according to soil moisture deficit (up to FC limit), soil density, root depth, leaching fraction and soil surface area. To separate the evapotranspiration components, all treatments were performed in two series of mini-lysimeters. In the first series, soil moisture reduction was related to crop evapotranspiration amount. But in the second series, the plastic mulch was placed on soil surface. Soil moisture reduction in the second series, was only related to crop transpiration amount. Difference of data in the first and second series was equal to the evaporation amount. Linear function of Mass and Hoffman (1977) was used as the function of evapotranspiration-salinity, transpiration-salinity, and evaporation-salinity. Results and DiscussionAs salinity increased from S1 to S4 levels, evapotranspiration, transpiration, and evaporation amounts were measured on the planting dates P1, P2, P3, and P4. The measurements were as follows:Evapotranspiration (mm): 619-548 (P1), 621-549 (P2), 624-547 (P3), and 625-544 (P4)Transpiration (mm): 429-309 (P1), 421-295 (P2), 418-281 (P3), and 412-265 (P4)Evaporation (mm): 190-239 (P1), 200-254 (P2), 206-266 (P3), and 213-279 (P4)These ranges reflect the measured amounts for each variable under increasing salinity levels across the different planting dates. Under the influence of salinity stress, soil water potential decreases, leading to a reduction in water uptake by the crop and subsequently decreased crop transpiration. As a result of this reduction in crop water uptake, the remaining water in the soil is utilized for evaporation. In S4 level and on dates of: P1, P2, P3 and P4, crop transpiration portion decreased to 12.9%, 14.1%, 15.6% and 17.2%, respectively, and evaporation portion increased to the same amount. By adjusting the seed planting date to optimize the utilization of favorable atmospheric conditions during crop growth stages, the increase in the portion of evaporation is prevented. In initial stage of growth period, only 0 to 10% of soil surface is covered by crops (FAO-56) causing the evaporation component to have a dominant portion in the crop evapotranspiration parameter. As a result, placing of initial growth stage in warm days of year caused an increase in evaporation losses. It seems that S1P1 treatment was the optimal condition for transpiration increase and evaporation decrease. The estimated functions showed that (in salinity stress conditions) crop transpiration decreased more than ETc. Therefore, the transpiration rate should be considered as the crop's net water requirement instead of ETc (crop evapotranspiration). According to the Mass-Hoffman function, under stress conditions, the decreasing slope of transpiration and evapotranspiration and the increasing slope of evaporation become more pronounced. For instance, in planting dates of P1, P2, P3, and P4, for each unit (dS.m-1) of increase in soil salinity, the evapotranspiration rates decreased by 2.51%, 2.82%, 3.3%, and 3.65%, respectively. Similarly, the transpiration rates decreased by 6.1%, 7.34%, 8.42%, and 9.2%, respectively, while the evaporation rates increased by 5.5%, 6.7%, 7%, and 7.82%. ConclusionSalinity and atmospheric temperature stresses had interaction effects on evapotranspiration and components rates. Postponing the seed planting date and not utilizing optimal weather conditions, especially during spring, can lead to damage to transpiration, which is a favorable aspect; however it is unfavorable in evaporation,. Therefore, in irrigated crops, it is advisable not to plant seeds during the warm months of the year, especially in July and August. Consequently, by controlling soil salinity and selecting the appropriate planting date, water can be optimally utilized.
Irrigation
Nader Karimi; Sayyed-Hassan Tabatabaei; Mohammad Hassan Rahimian; Seyyed Alireza Esmaeilzadeh Hosseini
Abstract
Introduction In arid and semi-arid regions, agricultural sustainability needs to improve the consumption of water and soil resources. Low rainfall, high evaporation, low water quality and less leaching of solutes in the soil due to limited water resources are the main problems in these areas. The ...
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Introduction In arid and semi-arid regions, agricultural sustainability needs to improve the consumption of water and soil resources. Low rainfall, high evaporation, low water quality and less leaching of solutes in the soil due to limited water resources are the main problems in these areas. The quality of water and soil resources in the provinces of Fars, Khuzestan, Yazd, Golestan and Khorasan also shows that most of the wheat farming lands in these provinces are always facing salinity issues. According to the conducted studies, saline water can be successfully used in irrigation, but application of unconventional water by surface irrigation systems with low efficiency due to evaporation and high water salts leads to soil salinity. Micro-irrigation methods increase water use efficiency by reducing water consumption and increasing yield, so that drip irrigation efficiency of 91-80% and irrigation levels of 50-73% have been reported. In recent years, the use of drip irrigation system (such as tape on wheat fields) has been recommended to farmers as a water management solution. Micro-irrigation systems by reducing water consumption and increasing yields, improve water use efficiency. Drip tape irrigation system compared to other surface and sprinkler irrigation methods, due to short irrigation periods and reduction of evaporation losses and deep infiltration even for crops can be proposed as an alternative. Drip tape irrigation in wheat cultivation can increase water use efficiency up to 2 times. Also, in irrigation with salt water, while maintaining humidity in the environment, it reduces salinity stress and by consuming less water and reducing the amount of wetting, it introduces less solutes into the soil. This method has limitations in wheat fields due to costs and also the possibility of soil salinity problems, some of which can be overcome by increasing the distance between the laterals and reducing the consumption of drip irrigation (Tape) per unit area.Materials and Methods In this study, during the 2020-2021 at the Salinity Research Center of Yazd Province (Iran), the effect of lateral distances on the surface and depth distribution of soil salinity was investigated. For this purpose, two irrigation water salinity treatments, including 3 and 8 dS / m and two flood (T1) and drip irrigation systems (Tape) with lateral distances of 60 (T2), 100 (T3) and 140 (T4) cm were considered. Irrigation management treatments included the use of the flooding method (as the dominant method in wheat fields) and the use of the Tape drip irrigation method (as the proposed method with very low water consumption). A distance of 60 cm was considered as the optimal distance with complete water overlap, a distance of 100 cm was considered as an economic distance with the possibility of deep moisture distribution and a distance of 140 cm was considered as a large lateral distance. To investigate the salinity distribution and the accumulation of salts in the soil, regular soil sampling of different treatments was the end of the season.Results and Discussion In all irrigation treatments (saline and non-saline), despite the constant volume of water consumption per unit area of all treatments, in T3 and T4 treatments, irrigation depth increased compared to T2 treatment and reduced soil salinity in the wetting area (irrigated area). By increasing the horizontal distance of each point of the field from the lateral, the irrigation depth and leaching fraction decrease and consequently, the soil salinity of these points can also increase. Under non-saline irrigation conditions (salinity of 3 dS/m), soil salinity at intervals of zero (below the lateral), 15 and 30 cm, between 5.5 and 6.1 dS/m has been observed. Values below the threshold of tolerance to salinity of wheat plant and, in this regard, does not pose a risk to the plant. At a distance of 45, 60 and 70 cm from the water pipe, the salinity of the soil is higher than the threshold and if there is a plant in this area of the field, it will face serious damage.Conclusion The results showed that although the Tape method in saline conditions (8 dS/m) compared to non-saline conditions (3 dS/m) leads to higher accumulation of solutes in the soil and increases the possibility of plant damage, but according to the final results of this study, by increasing the distances of irrigation laterals and proportionally increasing the depth of irrigation and keeping the salts away from the planting bed, a more suitable environment for plant growth can be prepared and higher economic benefits of this measure can be obtained. Also, in terms of controlling soil salinity, the conditions have been such that treatment with lateral distance of 140 cm compared to treatments of 60 and 100 cm has led to lower amounts of soil salinity in the subsurface and has provided better conditions for the plant. Thus, by increasing the distances of laterals from 60 to 140 cm and, consequently, increasing the depth of irrigation, it was possible to transfer solutes to lower depths of the soil.
Saghar Fahandej saadi; Masoud Noshadi
Abstract
Introduction: Although the soil salinity as an effective factor on soil and water management is typically assessed by measuring the soil electrical conductivity (ECe), this conventional laboratory method is time-consuming and costly. Therefore, near-infrared spectroscopy (NIR) as a fast, cheap and non-destructive ...
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Introduction: Although the soil salinity as an effective factor on soil and water management is typically assessed by measuring the soil electrical conductivity (ECe), this conventional laboratory method is time-consuming and costly. Therefore, near-infrared spectroscopy (NIR) as a fast, cheap and non-destructive method to assess soil salinity level can be considered as a valuable alternative method. Reviews of literature on the application of NIR spectroscopy for soil salinity prediction have shown that there is no sufficient information about the effect of soil texture on results accuracy; therefore, in this study the soil salinity was predicted under different soil salinity levels and various soil textures. The effect of different pre-processing methods was also investigated to improve the predicted soil salinity.
Materials and Methods: Twenty three surface soil samples were collected from different places in Fars province, then; some soil properties such as percentage of particles size and ECe were measured. These samples were artificially salted by adding the water in different salinity levels to the soil samples. The ECe of these soils were between 2.1 to 307.5 dS/m and then all samples dried to reach the field capacity level. Soil reflectance spectra were obtained in 350-2500 nm wavelength range. The absorbance and derivative of reflectance spectra were calculated based on the reflectance spectra. In order to determine the effect of smoothing technique, as a pre-processing method, 4 various methods (moving average, Gaussian, median and Savitzky-Golay filters) in 12 different segment sizes (3,5,7,9,11,13,15,17,19,21,23 and 25) were applied and the processed spectra introduced to Partial Least Square Regression (PLSR) model to predict soil salinity in two calibration and validation steps. At the first step, the soil salinity was predicted for all samples using of reflectance, absorbance and derivative of reflectance spectra under 4 pre-processing methods and 12 segment sizes. According to the R2 and RMSE indices, the best type of spectra, the effect of various pre-processing methods and the best segment size in prediction of soil salinity were determined as absorbance spectra, moving average and Savitzky-Golay filters for segment size of 25 and 15, respectively. In the second step, the effect of soil texture on prediction accuracy was investigated. For this purpose, soil samples were divided into the coarse and fine textures and soil salinity was predicted for each of these groups using different pre-processing methods and different segment sizes.
Results and Discussion: In prediction of soil salinity by absorbance, reflectance and derivative of reflectance spectra, the R2 values in validation step were 0.742, 0.706 and 0.670; and RMSE values were 29.92, 31.96 and 33.9 (dS.m-1), respectively. The absorbance spectra were the best spectra type in prediction of soil salinity. Therefore, in next step, absorbance spectra were used only for predicting the salinity in fine and coarse soil textures. Results showed that the prediction in coarse texture was better than that of the fine texture (R2= 0.836 and R2=0.756, respectively). It was also revealed that the highest R2 occurred in coarse texture and the accuracy of prediction was reduced in fine textures. The results showed that the performance of different pre-processing methods is related to the spectrum type. Although the pre-processing methods had no positive effect in using of reflectance spectra, but it improved the predicted values which were obtained using of absorbance and derivative of reflectance spectra. The best results were occurred when the absorbance spectra were used. Moving average method increased the accuracy of prediction more than the other pre-processing methods, and according to the results this method, for the segment size of 25, was the best technique in soil salinity prediction.
Conclusion: According to the R2 and RMSE indices, the prediction of soil salinity by absorbance spectra was more accurate than the prediction using reflectance and derivative of reflectance spectra (R2= 0.742, 0.706 and 0.670, respectively). Although the predicted soil salinity in coarse soils were more accurate than that in fine soils. Using of absorbance spectra to predict the soil salinity in all soil textures was efficient. The results showed that using of pre-processing methods improved the soil salinity prediction by absorbance and derivative of reflectance spectra, and the moving average and Savitzky-Golay filter were the best pre-processing methods.
Yousef Hasheminejhad; Mahdi Homaee; Ali Akbar Noroozi
Abstract
Introduction: Monitoring and management of saline soils depends on exact and updatable measurements of soil electrical conductivity. Large scale direct measurements are not only expensive but also time consuming. Therefore application of near ground surface sensors could be considered as acceptable time- ...
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Introduction: Monitoring and management of saline soils depends on exact and updatable measurements of soil electrical conductivity. Large scale direct measurements are not only expensive but also time consuming. Therefore application of near ground surface sensors could be considered as acceptable time- and cost-saving methods with high accuracy in soil salinity detection. . One of these relatively innovative methods is electromagnetic induction technique. Apparent soil electrical conductivity measurement by electromagnetic induction technique is affected by several key properties of soils including soil moisture and clay content.
Materials and Methods: Soil salinity and apparent soil electrical conductivity data of two years of 50000 ha area in Sabzevar- Davarzan plain were used to evaluate the sensitivity of electromagnetic induction to soil moisture and clay content. Locations of the sampling points were determined by the Latin Hypercube Sampling strategy, based on 100 sampling points were selected for the first year and 25 sampling points for the second year. Regarding to difficulties in finding and sampling the points 97 sampling points were found in the area for the first year out of which 82 points were sampled down to 90 cm depth in 30 cm intervals and all of them were measured with electromagnetic induction device at horizontal orientation. The first year data were used for training the model which included 82 points measurement of bulk conductivity and laboratory determination of electrical conductivity of saturated extract, soil texture and moisture content in soil samples. On the other hand, the second year data which were used for testing the model integrated by 25 sampling points and 9 bulk conductivity measurements around each point. Electrical conductivity of saturated extract was just measured as the only parameter in the laboratory for the second year samples.
Results and Discussion: Results of the first year showed a significant correlation between electrical conductivity and apparent conductivity with a regression coefficient of 0.78. Although multiple linear regression by inclusion of soil moisture and clay content as independent variables improved the regression coefficient to 0.80 but the effect of clay content was not significant in this multiple model. Sensitivity analysis by maintaining one variable at its average value and changing the second variable also showed greater sensitivity of the model to soil moisture in comparison with soil clay content. Generally under estimation of soil moisture and over estimation of soil clay content produced about 63 to 65 percent Mean Bias Error (MBE) while over estimation of soil moisture and under estimation of soil clay content produced about 35- 37 percent of MBE. So the model is quite sensitive to both parameters and they cannot be estimated in the field by feeling and the other field methods. Simple linear regression model between ECe and EMh was tested on the second year because the errors in estimating soil moisture could be imposed a significant error on estimating soil salinity. Once the model was tested for estimation of soil salinity in the central point based on EMh reading at the center and then it was tested for estimation of soil salinity based on the average EMh of 9 points in each location. Results showed that the correlation between soil salinity and apparent soil electrical conductivity could be improved to 0.98 using the average of 9 measurements instead of 1 measurement.
Conclusion: Based on the results the electromagnetic induction device is sensitive to soil moisture. Although its sensitivity to clay content is less than the sensitivity to moisture content, but the total model error as a result of over estimating soil moisture is about equal to its error resulted from under estimating clay content and vice versa. So the field and feeling methods could not be implemented as inputs for the multiple regression models but these methods have enough accuracy to divide soil samples into two groups of dry and wet soils or sandy or clayey soils, on the other hand measurements of these parameters imposes more cost and time to soil salinity surveys. Results also showed that the repeated EM measurements around each sampling point could improve the strength of the regression. Therefore regarding to the sensitivity of the technique to soil moisture three methods are suggested to improve accuracy of calibration: a)- measurement and calibration under the same moisture conditions; b)- field approximation of soil moisture and dividing soil samples into two groups of dry and moist soils and deriving two different groups of calibration equations.
Masoud Noshadi; Hosein Valizadeh
Abstract
Introduction: Soil salinity is one of the major limitations of agriculture in the warm and dry regions. Soil sodification also damages soil structure and reduce soil permeability. Therefore, control of soil salinity and sodium is very important. Vetiver grass has unique characteristics that can be useful ...
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Introduction: Soil salinity is one of the major limitations of agriculture in the warm and dry regions. Soil sodification also damages soil structure and reduce soil permeability. Therefore, control of soil salinity and sodium is very important. Vetiver grass has unique characteristics that can be useful in phytoremediation.
Materials and Methods: This research was conducted to investigate the effects of irrigation with different salinities on vetiver grass and the effects of this plant on the control of soil salinity and soil reclamation.The experimental design was randomized complete block design. Irrigation water salinities were 0.68(blank), 2, 4, 6, 8 and 10 dS/m, respectively, which artificially were constructed using sodium chloride and calcium chloride. At first, vetiver was transplanted and then moved to the farm. The amount of soil moisture was measured by the neutron probe. Irrigation depth was applied to refill soil water deficit up to field capacity. To evaluate the soil salinity in above salinity treatments, soil was sampled in each plot from 0-30, 30-60 and 60-90 cm depths and for each layer, electrical conductivity of saturated extract (ECe), sodium, potassium and chloride concentrations was measured .To measure the sodium, potassium and chloride concentrations in the leaves and roots of vetiver plant, samples were dried in oven. The dried samples were powdered and passed through the sieve (No. 200) and they were reduced to ash in 250 ◦C. 5 ml HCl was added to one gram of the ash, and after passing through filter paper, the volume of sample was brought to 50 ml by boiled distilled water. After preparing plant samples, the sodium, potassium and chloride concentrations were measured by Flame Photometer.
Reults and discussion: The results showed that the vetiver grass was able to decrease soil salinity at different salinity levels except highest water salinity (10 dS/m) and prevented salt accumulation in the soil. However, in the salinity 10 dS/m, soil salinity was not well controlled, but soil salinity was lower than the irrigation salinity. In these water salinities, the mean ECes in 0-90 cm soil depth were increased 25.0, 60.4, 79.2, 87.5 and 215.5 percent, respectively, relative to a control treatment, which was much less than the increasing of irrigation water salinities. These increases in ECe were significant at 5% level of probability. The accumulated values of sodium in vetiver leaves showed significant difference between S0 treatment and the other treatments (S3, S4 and S5) at the 5% level of probability. The sodium contents in vetiver leaves were 22.2, 33.3, 70.4, 103.7 and 122.2% and in vetiver roots were 32.7, 66.5, 129.3, 218.2 and 281.8% higher than the control treatments (S0), respectively. Sodium contents in vetiver roots were 103.7, 121.2, 154.4, 174.1, 218.2 and 250% more than sodium contents in vetiver leaves in S0, S1, S2, S3, S4 and S5 treatments, respectively. Sodium contents were increased 14.3, 28.6, 64.3, 100.0 and 114.3 percent in vetiver leavesand 28.6, 64.3, 125.0, 214.3 and 275.0 percent in the vetiver roots , relative to the control treatment, respectively, at above salinity levels, which indicated an improvement of sodium accumulation in leaves and roots with increasing salinity levels. Chloride concentrations at irrigation water salinities S1, S2, S3, S4 and S5 treatments (2-10 dS/m) were 22.9, 35.6, 74.5, 107.2 and 121.9% in vetiver leaves and 27.02, 59.7, 118.9, 195.06 and 255.7% in vetiver roots more than control treatment, respectively. The mean values of sodium and chloride in all salinity levels in the roots were 170.3 and 164.1 percent more than the leaves, respectively.There were no significant differences in accumulated potassium in vetiver leaves and roots between different treatments, but vetiver leaves and roots absorbed and accumulated high value of potassium. The potassium contents were 4.38, 4.64, 4.18, 3.89, 3.82 and 3.68 mg/g in vetiver leaves and 3.12, 3, 3.62, 3.69, 3.84 and 3.68 mg/g in vetiver roots, in S0, S1, S2, S3, S4 and S5 treatments, respectively.
Conclusion: In general, the results showed that up to irrigation water salinity 8 dS/m, Vetiver grass had very good ability to control soil salinity and prevented the accumulation of salt in the soil, but at the salinity of 10 dS /m, soil salinity was not well controlled. However, in 10 dS /m, soil salinity was much less than water irrigation salinity.
The mean values of soil salinity in layer 3 (60-90 cm) were 0.48, 0.6, 0.77, 0.86, 0.9 and 1.5 dS/m in S0, S1, S2, S3, S4 and S5 treatments, respectively. ECes were 29.4, 70.0, 80.8, 85.7, 88.8 and 85.0 percent lower than irrigation water salinities 0.68, 2, 4, 6, 8 and 10 dS/m, , respectively. Sodium and chloride accumulated in the leaves and roots of vetiver that showed that Vetiver it is well able to absorb these elements. The accumulations of sodium and chloride in roots were170.3 and 164.1 percent more than leaves, respectively.
M. Hashemi; Ahmad Gholamalizadeh Ahangar; Abolfazl Bameri; F. Sarani; A. Hejazizadeh
Abstract
Introduction: In order to provide a database, it is essential having access to accurate information on soil spatial variation for soil sustainable management such as proper application of fertilizers. Spatial variations in soil properties are common but it is important for understanding these changes, ...
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Introduction: In order to provide a database, it is essential having access to accurate information on soil spatial variation for soil sustainable management such as proper application of fertilizers. Spatial variations in soil properties are common but it is important for understanding these changes, particularly in agricultural lands for careful planning and land management.
Materials and Methods: To this end, in winter 1391, 189 undisturbed soil samples (0-30 cm depth) in a regular lattice with a spacing of 500 m were gathered from the surface of Miankangi land, Sistan plain, and their physical and chemical properties were studied. The land area of the region is about 4,500 hectares; the average elevation of studied area is 489.2 meters above sea level with different land uses. Soil texture was measured by the hydrometer methods (11), Also EC and pH (39), calcium carbonate equivalent (37) and the saturation percentage of soils were determined. Kriging, Co-Kriging, Inverse Distance Weighting and Local Polynomial Interpolation techniques were evaluated to produce a soil characteristics map of the study area zoning and to select the best geostatistical methods. Cross-validation techniques and Root Mean Square Error (RMSE) were used.
Results and Discussion: Normalized test results showed that all of the soil properties except calcium carbonate and soil clay content had normal distribution. In addition, the results of correlation test showed that the soil saturation percentage was positively correlated with silt content (r=0.43 and p
M. Hassanli; H. Ebrahimian; M. Parsinejad
Abstract
Using of saline water for irrigation of crops is known as a strategy of on-farm irrigation water management. In this study, the cyclic using of saline and fresh water and its effect on soil salinity were investigated. Field experiments were carried out in randomized complete block design under drip irrigation ...
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Using of saline water for irrigation of crops is known as a strategy of on-farm irrigation water management. In this study, the cyclic using of saline and fresh water and its effect on soil salinity were investigated. Field experiments were carried out in randomized complete block design under drip irrigation for maize crop with 9 treatments. The treatments were based on alternative irrigation management of saline and fresh water use on three salinity levels 0.4, 3.5 and 5.7 dS/m and freshwater application in every one, three and five saline water application (1:1, 3:1 and 5:1, respectively). The results showed that in 1:1 management, soil salinity at the end of growing season compared with the beginning of growing season did not change considerably (reducing of 1.0% and 17.9% for 1S1:1F and 1S2:1F). In 3S2:1F and 5S2:1F treatments, the amount and frequency of fresh water was not enough to remove salts from the soil and at the end of growing season, salt accumulation was seen in soil profile (increasing of 39.0% and 46.2% in soil salinity). In 3S1:1F and 5S1:1F treatments, soil salinity increased 17.9% and 31.6%, respectively, while increasing of soil salinity in S1 treatment was 40.7%. Thus, by 4 irrigations with fresh water in 3S1:1F treatment and 2 irrigations with fresh water in 5S1:1F treatment, reducing of 22.8% and 9.1% in soil salinity was seen in compared with S1 treatment.
