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Ali Abdzad Gohari; Amir Nik Akhtar; Niazali Ebrahimipak; Arash Tafteh
Abstract
Soil and Water Research Institute (SWRI) has presented NIAZAB system to estimate and determine crops water requirement, water consumption, and irrigation planning at the scale of region, district, and plains in Iran. The current research was conducted in order to use NIAZAB system (including Tafteh, ...
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Soil and Water Research Institute (SWRI) has presented NIAZAB system to estimate and determine crops water requirement, water consumption, and irrigation planning at the scale of region, district, and plains in Iran. The current research was conducted in order to use NIAZAB system (including Tafteh, Pasquale and Reas methods) in determining the amount of water used for soybean cv. Williams, based on the inverse solution of the production function. The experimental treatments in this research included no fertilizer and application of of 150 kg N ha-1 and different irrigation treatments including 100%, 80%, 60%, and 40% of water requirement. Experimental design was split plot in the form of randomized complete blocks with three replications, and was conducted in Hajiabad Region, Hormozgan Province, in 2020 and 2021. The values estimated by the system and measured showed that, in the first year, the average relative error (ARE) in eatimation of evapotranspirationin by Tafteh, Pasquale and Reas methods were 7.49%, -0.05%, and 9.14%, respectively. In the second year, these values were 6.47%, -1.29%, and 9.06%, respectively. The ARE in the physical water productivity in the mentioned methods was -8.23%, -0.73%, and -10.08% in the first year, and -7.10%, 0.58%, and -10.07% in the second year, respectively. In Tafteh, Pasquale, and Reas methods, the root mean square error (RMSE) were 43, 35, and 49 mm, respectively, and the normalized root mean square error (RMSEn) were 0.093%, 0.076%, and 0.105%, respectively. Considering the results, NIAZAB system estimated the amount of irrigation water and evapotranspiration with acceptable approximation and it can be used for estimation of water consumption in the studied area.
2
Sara bulukazari; Hossein Babazadeh; Nyazali Ebrahimipak; Seyed Habib Mousavi-Jahromi; Hadi Ramezani_etedali
Abstract
In exploitation of low-quality water in arid and semi-arid regions, irrigation management is essential to increase water use efficiency. Determination of crop-water-salinity production function is an essential tool for proper irrigation management. In this study, the AquaCrop model was first evaluated ...
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In exploitation of low-quality water in arid and semi-arid regions, irrigation management is essential to increase water use efficiency. Determination of crop-water-salinity production function is an essential tool for proper irrigation management. In this study, the AquaCrop model was first evaluated by considering 4 soil and water salinity levels and 4 deficit irrigation levels for the major cereal crops including wheat, barley, and corn in Qazvin Plain. The results showed that the coefficients of determination for wheat, barley, and corn yield were 0.97, 0.86 and 0.91, respectively. Therefore, the model can evaluate the performance in salinity and deficit irrigation conditions with a good approximation. To determine the optimal production functions of each crop, the results of the plant model were compared with three models of linear and nonlinear regression, and artificial neural network. The neural network model was able to estimate the performance compared to the AquaCrop model with lower error and higher correlation (0.99). These values in the linear function for wheat, barley, and corn were 0.98, 0.95, and 0.78 and in the nonlinear function as 0.92, 0.86 and 0.81, respectively. Also, the error calculated in the neural network method for wheat, barley, and maize was 40.16, 62.09, and 57.08 kg, respectively, which were less than the linear model by 75 %, 70 %, and 95 %; and less than the exponential model by 90 %, 85 %, and 93%, respectively. The best trained network for determining the water-salt production function for barley and wheat 5 Nero and for corn 7 Nero was introduced in the single layer structure. Sensitivity analysis on wheat and barley showed that this model had low sensitivity to irrigation and salinity parameters and only corn plant showed a moderate range sensitivity to salinity parameter.
m m; h b; f k; n e
Abstract
The agricultural sector is known as the largest consumer of water. Due to limited water resources, water productivity needs to be enhanced in this sector. The concept of water productivity has attracted the attention of policy makers in food and water sector at large scale. Remote sensing is used in ...
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The agricultural sector is known as the largest consumer of water. Due to limited water resources, water productivity needs to be enhanced in this sector. The concept of water productivity has attracted the attention of policy makers in food and water sector at large scale. Remote sensing is used in the assessment and management of soil and water resources in recent decades. In the present research, this method was used to estimate water productivity. Evapotranspiration and actual production levels of dry matter were calculated using SEBAL algorithms and five images from the Landsat 5TM satellite in Qazvin Plain. The results of SEBAL algorithm in five images and lysimeter data were compared and evaluated in the region. The coefficient of determination ( 15R2"> ) and their mean absolute difference were 0.9948 and 0.446 mm/day, respectively, which demonstrated the accuracy of remote sensing methods in estimating agricultural water productivity at the basin level. The results showed that water productivity varied from 0.18 to 1.35 in the field. The wheat water productivity values from Landsat 5TM images and lysimeter data were 0.73 and 0.85 kg/m3, respectively, which are relatively close to each other.
Arash Tafteh; Niazali Ebrahimipak; Hossin Babazadeh; Fereydoon Kaveh
Abstract
Management of water distribution in the Qazvin Plain is planned on monthly intervals. Therefore, production functions which can accurately predict yield reduction under deficit irrigation on monthly basis are needed. This study was conducted with the following purpose: assessment of the production functions ...
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Management of water distribution in the Qazvin Plain is planned on monthly intervals. Therefore, production functions which can accurately predict yield reduction under deficit irrigation on monthly basis are needed. This study was conducted with the following purpose: assessment of the production functions using different methods including, minimum, average, multiplicative, Raes method, and product with yield response factor (Ky) power as applied by FAO and Najarchi yield response factors. To estimate tomato yield under different deficit irrigations and evaluation of empirical methods, a study was conducted by using randomized complete block design with irrigation interval treatments including T1, T2, T3, and T4 representing, respectively, 60, 90,120, and 150 mm evaporation from class A pan between consecutive irrigations. The study had three replications and was carried out at the Faizabad Agricultural Research Station, in Qazvin. The results showed that maximum water requirement of tomato plant was 1073 mm, T1 treatment had the maximum yield with 88500 kg/ha and T4 treatment had the minimum yield with 57000 kg/ha. Also, according to statistical comparisons, the proposed method that estimated the plant response factor based on monthly power had the minimum root mean square error (RMSE) and normal root mean square error (NRMSE), while it had the highest agreement index and coefficient of determination (R2).The plant yield response factors were determined in June, July, August, September, and October as, respectively, 0.7, 1.1, 1.1, 1.14 and 0.4. The value of this factor for initial growth, plant development satge, mid-season, and late-season were, respectively, 0.7, 1.1, 1.14, and 0.4, while the average for the whole growing period was determined as 0.89 by using the proposed method. As a result, the proposed method is suggested as a convenient method.
Niazali Ebrahimipak; M MOSTASHARI
Abstract
This study investigated the effect of water stress and different amounts of zinc, manganese, and boron fertilizers on yield components and water use efficiency of sugar beet. The experiment was conducted for three years in Qazvin, Iran, with two-factor factorial design in randomized complete block ...
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This study investigated the effect of water stress and different amounts of zinc, manganese, and boron fertilizers on yield components and water use efficiency of sugar beet. The experiment was conducted for three years in Qazvin, Iran, with two-factor factorial design in randomized complete block and three replicates including irrigation and fertilizer treatments. Irrigation treatments consisted of four intervals i.e. 6, 9, 12 and 15 days (treatments E1 to E4) and fertilizer levels included fertilizers based on soil test (30 kg boric acid/ ha , 40 kg zinc sulfate / ha and 30 kg manganese sulfate /ha,), 30 percent less than the recommended fertilizer (21 kg boric acid/ ha ,28 kg zinc sulfate /ha, 21 kg manganese sulfate /ha) and 30 percent more than the recommended fertilizer (39 kg boric acid / ha , 52 kg zinc sulfate /ha and 39 kg manganese sulfate / ha) treatments, respectively, F1, F2, and F3. Statistical analysis of sugar beet root yield showed significant (at 5% level) differences between irrigation treatments and fertilizer treatments. Treatment E1F3 produced a yield of 64696 kg/ ha, while E4F3 produced 41736 kg/ha that was the lowest yield. Average root yield of F2 treatmentswas more, but, in the case of F1, the amount of sugar level was higher. In the wettest irrigation treatment, root yield increased with increasing fertilizer rates. It is suggested that when water stress conditions occur, use of fertilizer in excess of the recommended levels should be avoided. The volumes of irrigation water applied in irrigation intervals of 6, 9, 12 and 15 days were, respectively, 9659, 8104, 6677, and 5398 cubic meters per hectare. Water productivities for irrigation interval of 15 days and F2, F1, and F3 were, respectively, 8.39, 8.38, and 7.73 kg beetroot per cubic meter of water, reflecting the most efficient use of irrigation water.