Irrigation
M. Emadi; M. Noshadi; A.A. Ghaemi
Abstract
Introduction: According to expantion of urbanization, it is necessary to create green space as the most important environmental factor in moderate cities. However in recent decades, shortage of water resources is one of the problems facing the expansion of green space especially grass type. Therefore, ...
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Introduction: According to expantion of urbanization, it is necessary to create green space as the most important environmental factor in moderate cities. However in recent decades, shortage of water resources is one of the problems facing the expansion of green space especially grass type. Therefore, the application of management methods such as deficit irrigation is very important. Development of green space requires sufficient water supply and according to the climatic conditions of our country, finding alternative methods and resources for effective irrigation and utilizing all available capacities is one of the main goals of municipalities and water organizations.
Materials and Methods: This research was performed in a greenhouse with an area of 120 square meters located in the college of Agriculture of Shiraz university with longitude 52032’, latitude 29036’,1810 height above sea level, and in flower pots with dimensions of 30 * 30*30 in order to investigate the effect of water stress in the traditional irrigation method on morpho-physiological factors and water productivity in two variety long grass. The research was in the form of split plots based on a random full canton with three replication and three levels (%100 per) (w1), (%75 per) (w2), (%50 per)(w3) of water requirement. The grass used in this design is Festuca, arundinacea Schreb with two variety named Asterix and Talladega which are considered as cold grasses and has a root depth of 15-20 cm. The first 3 cm of sand (to create drain conditions) was placed in the bottom of the flower pot, and then 24 cm of soil was poured on it and compacted until it reached the required density. On April 10, two variety of grass seeds were poured manually on the pots (10 grams of seeds per pot). Then, 100 gr of rotten and screened animal dung was poured on the seeds in each flower pot and irrigated with a hose by a traditional (manual) system. Early cultivation was done manually due to the application of more water and the establishment of grass. In this way, every day for a week, two to three times irrigation and after the seeds germinate (10 days after cultivation), once-daily irrigation and until the seeds germinate completely (20 days after cultivation), the irrigation period was once between 7 until 15 days, and then water stress was imposed. The first grass mowing was done after the grass was completely established (30 days after cultivation). Also, in order to compensate for the shortage of nutrients in the soil after two months (July) 6 gr /m2 of urea fertilizer (0.54 gr/ m2 to each flower pot) was applied. The onset of stress was two months after cultivation (July 10), and the duration of stress was 45 days. To determine the water requirement a separate flowerpot among the other flowerpots was located, and provide the moisture to FC level. Every other day, the water lost by this flower pot compared to the initial weight (FC), the same amount of water was given to the flowerpots with 20% more as for the leaching requirement.
Results and Discussion: Analysis of experimental data was performed by SAS 9.4 statistical software, and Duncan’s multiple range experiments at 5% level were used to compare the means, at the level of 5% probability. Results and data analysis was investigated under water stress in two varieties.
Dryness stress and water use efficiency: Water productivity in both varieties of grass and in different irrigation treatments did not change significantly at 95%. So decline in the amount of irrigation water has not affected water productivity.
Interaction of dryness and grass quality: The results showed that water stress and the interaction of water stress and grass variety on the appearance quality of grass were not significantly different at 95% and in the second ten days of August, the appearance quality was more desirable than in the first half.
Interaction of dryness and relative leaf water content of leaf: The relative water content of the leaf was weekly measured during the stress period. The results of comparing the mean relative water content (RWC) of leaf under water stress in two types of Festuca grass showed that the effect of water stress interaction was significant in Asterix grass variety on the relative water content of leaf at 95% level. The relative water content of the leaves is a good index of the water situation of the leaves, and its reduction in the leaves causes wilting and reduces the freshness and appearance quality of the grass and reducing the relative water content of the leaf has not affected the appearance quality of the grass.
Interaction of dryness and leaf growth rate: The leaf growth rate was measured during the stress period (monthly) in three ten-day periods (August). The results of comparing the means showed that the effect of water stress interaction and two variety of grasses on leaf growth rate was not significant during the first ten days. In the second ten days, the effect of water stress was significant in both Asterix and Talladega grass and growth rate in irrigation treatments of 75 and 50% (percentage) of full irrigation was significantly different from full irrigation.
Conclusion: The results of this study showed that deficit irrigation could increase water use efficiency without reducing the quality of green cover. With less water consumption (half full irrigation), the appearance quality of the grass will be well maintained. The relative water content of the leaf decreased as dryness stress progresses and causing changes in the cell membrane and thus increasing electrolyte permeation from the cell. Considering that dryness stress has not reduced the appearance quality of the grass, reducing the relative water content of the leaf has not affected the appearance quality of the grass. Generally, the growth rate in all three decades was maximum in dryness stress 75% (percentage), which indicates the high photosynthesis of the plant in this stress.
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.
hossein dehghani; Hamidreza Haji Agha Bozorgi; ali asghar ghaemi
Abstract
Introduction: The main problem of salinity, in addition to reducing agricultural and horticulture products is the gradual decline of their cultivation area. Several factors such as climate and irrigation (precipitation, fraction of leaching), soil type and soil salinity, salinity of irrigation water, ...
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Introduction: The main problem of salinity, in addition to reducing agricultural and horticulture products is the gradual decline of their cultivation area. Several factors such as climate and irrigation (precipitation, fraction of leaching), soil type and soil salinity, salinity of irrigation water, uniform distribution of the system and irrigation with saline water affects the soil salinity changes. Therefore, in irrigated agriculture, soil salinity should be reduced and controlled to an optimal level of the economic production. Leaching with proper irrigation management is one of the effective ways to reduce soil salinity.
Materials and Methods: The study was conducted during 2012-2013 in as pistachio garden located in the Safaeieh region of Semnan province. The garden was 100 ha and 2 ha of that was selected for this study with 10 years old pistachio trees equipped to subsurface drip irrigation system. The treatments of this study were three irrigation regimes; control (I1), Irrigation based on irrigation requirement (I2) and I2 plus leaching requirement (I3), three soil depth of 25, 50, and 75 cm from soil surface and time before and after irrigation. The drip line laterals include emitters with 2.26 lph flow rate was buried in 40 cm soil depth. Soil samples to evaluation salt concentration were collected from 25, 50, and 75 soil depth before and after irrigation. To study the impact of different irrigation regimes, soil depth and time (before and after irrigation) and also their bilateral impact a factorial design in randomize block was applied.
Results and Discussion: The results showed that ECe and SAR accumulation decreased after development, growth stage and continued to end growth stage. The results showed that I2 and I3 irrigation regimes were more effective in reducing the amount of sodium from the root zone and the I2 irrigation regime showed better performance in comparison to I3 irrigation regime. Regarding the amount of magnesium in the soil, the I2 irrigation regime was more successful than the I1 and I3 regimens. In I1 irrigation regime, the amount of magnesium at the end growth stage increased compared to the beginning growth stage. Significant decrease in ECe level at the end growth stage compared to the beginning growth stage belonged to the I2 irrigation regime, which suggests that I2 irrigation regime was more successful in ECe leaching during the period of pistachio growth, which attributed to the potential for leaching from the soil surface to the depths below the soil surface. The results showed that excessive water application under saline conditions for any reason, such as leaching not only does not have a beneficial effect on the removal of salts from the root zone, but also may lead to accumulation of salts and damage to the plant. The highest amount of calcium in the soil was recorded 98 days after the first irrigation under the I2 and I3 irrigation regimes which was 52.5 and 58.1 Meq/l, respectively. The lowest amount of this element The I1 and I2 regimens were 40.8 meq/l, respectively, which were recorded in 152 days after the first irrigation. In terms of SAR, the lowest value in the I2 regime was more noticeable than other irrigation regimes. The effects of soil depth of time after the first irrigation showed that there was no significant difference at the depth of 25 cm and 75 cm at the end growth stage compared with the valued recorded in beginning growth stage, but at a depth of 50 cm there was a significant reduction in ECe. The highest ECe value equaled to 14.5 dS/m was recorded at a depth of 75 cm in 98 days after first irrigation. In the I1 irrigation regime at all three depths of 25, 50 and in the I3 irrigation regime at a depth of 75 cm the amount of SAR at the end growth stage were not less than that in beginning growth stage, however, the reduction in SAR was recorded in the I2 irrigation regime at all three depths.
Conclusions: Irrigation regime I2 was successful to control the SAR in different soil depth compared to the other two irrigation regimes, which is very important for the next irrigation season to moderate the harmful effects on blossoms. Moreover, it is suggested that in a field, equipped with a subsurface drip irrigation system, leaching water at the end of the season by surface irrigation or heavy subsurface drip irrigation during the rainfall to leach out the accumulated salt to lower soil layers.
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.
Abstract
In many areas, the main source of surface and groundwater nitrogen pollution is agriculture and simulation models are useful tools in determining the contribution of nitrogen produced by agriculture in pollution of water resources. In this research, leaching of nitrate on a loam-silty to loam soil was ...
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In many areas, the main source of surface and groundwater nitrogen pollution is agriculture and simulation models are useful tools in determining the contribution of nitrogen produced by agriculture in pollution of water resources. In this research, leaching of nitrate on a loam-silty to loam soil was measured and simulated using LEACHN model after calibration. The experimental design was complete randomize block. The planting media consist of 15 PVC lysimeters (soil column) with 40 cm diameter and 120 cm height. In these lysimeters, maize (Singel Cross 704) was planted. The nitrogen treatments were 0.0 (control), 150, 200, 250 and 300 kg N/ha as urea with three replications. The results were showed that at 120 cm soil depth and the end of growing season, the nitrate leachate in 150, 200, 250, and 300 kg ha-1 treatments were increased 132, 174, 134 and 182% relative to control, respectively. Comparison between the measured and simulated results showed that LEACHN overestimated the leached nitrate in drainage water with the relative error between 11.3% (300 kg ha-1 treatment) and 88.6% (control). The order of accuracy in simulations was obtained in 300, 200,150 and 250 kg ha-1, respectively. In general, the evaluation of LEACHN model showed that the accuracy of this model for simulation of nitrate leachate was relatively good.