Irrigation
M. Gaznavi; A. Mosaedi; M. Ghabaei Sough
Abstract
Introduction: Drought is a climatic phenomenon and an integral part of climate fluctuations that occurs periodically and intermittently throughout the world and across all climates. However, the magnitude of this natural hazard in arid and semi-arid regions, such as most parts of Iran, is more acute ...
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Introduction: Drought is a climatic phenomenon and an integral part of climate fluctuations that occurs periodically and intermittently throughout the world and across all climates. However, the magnitude of this natural hazard in arid and semi-arid regions, such as most parts of Iran, is more acute due to the high sensitivity and weakness of these areas, and its effects may persist for years after the occurrence of drought. Drought is a multifaceted phenomenon as precipitation, temperature, evaporation, wind and relative humidity play important roles in the drought characteristics such as occurrence, severity, and magnitude. Climate change and global warming, and in some cases displacement of meteorological stations cause heterogeneity in time series of meteorological data. Therefore, the purpose of this study was to investigate the homogeneity and break point in precipitation time series data and the effects of a break point in drought characteristics in some synoptic stations in Iran. Materials and Methods: In this study, homogeneity of rainfall time series data at two time scales of annual (water year) and plant growth periods in some selected synoptic stations of Iran with different climatic conditions was investigated. For this purpose, four tests including Standardized Normal Homogeneity test (SNH), Buishand’s Range test (BHR), Buishand’s U test (BUR) and Petite’s test were applied and the break points were determined. Then, at the stations with break points in the precipitation data series, the drought severity values were determined using four indices of SPI, SPEI, RDI and eRDI, for two periods, (before and after of the break points). Then drought characteristics based on Markov Chain Model and Transition probability matrix including vulnerability, reliability, reversibility and stationary of three condition of droughts (dry, normal and/or wet condition) were determined for the two time scales periods (annual and plant growth periods). Then, the differences between the characteristics for the two periods were investigated. Also, the characteristics of drought-free time intervals for the two periods based on Run’s theory were determined and compared. Results and Discussion: Based on the homogeneity tests, precipitation data of Arak and Tabriz stations for two scales of annual and plant growth periods have break points. According to the results, in the most cases, the second period's reversibility was lower than the first period. Reliability and vulnerability also decreased and increased in all cases in the second period, respectively, compared with the first period. In most cases, there was an increase in stationary of drought in the second period relative to the first period. The rate of change in the probability of survival of the normal and wet condition in both periods was increasing and in some cases decreasing. Regarding the results of Run’s theory at the growth periods scale, the average and maximum duration of drought periods increased in all cases in the second period. The minimum, average and maximum severity of drought periods also increased in most cases in the second period. The minimum, average, and maximum values increased in most cases in the second period. On an annual basis, the number of drought periods in most cases has increased in the second period. The average and maximum duration of drought periods increased in all cases in the second period. The minimum, average, and maximum severity of drought periods also increased almost in all cases in the second period. Minimum, average, and maximum of drought magnitude values increased in most cases in the second period with respect to the first one. The minimum, average and maximum values of the drought-free durations (interval time without drought conditions) in most cases were lower in the second period. At the annual scale, the minimum duration of drought was one year in all cases and no change was found between the time slices. The average duration in most cases was lower in the second period. Conclusion: The results show that the rainfall data of Arak and Tabriz stations have break points in the time scales of plant growth period and annual periods. The reliability was decreasing while the vulnerability of drought was increasing in the second period, indicating an increase in drought occurrence in recent decades. Moreover, the probability of drought stability (stationary) in the second period increased in most cases. The average and maximum duration of drought periods also increased in the second period. The minimum, average, and maximum drought severity, and the minimum, average, and maximum of magnitude of drought periods were higher during the second period. In most cases, the minimum, average, and maximum of severity and magnitude of drought-free time intervals were lower in the second period. In general, difference in the characteristics of drought before and after of precipitation break point can be due to increased evapotranspiration, as a result of global warming, intensifying the effects of drought. Moreover, based on the results of the eRDI index, the climatic conditions became drier in both stations and time periods. In other words, it can be stated that the effective rainfall has decreased to some extent in recent years compared to the early years of the study period. Further studies are needed to assess the changes in drought characteristics in all synoptic stations in the country having long-term data.
Irrigation
T. Khalili; M. Sarai Tabrizi; H. Babazadeh; H. Ramezani Etedali
Abstract
Introduction: Water resources management in arid and semi-arid regions is very important specially, in agricultural sector. The major share of water use is daily consumption by humans for drinking, washing and cooking. Furthermore, population growth increases agricultural production demand, and ...
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Introduction: Water resources management in arid and semi-arid regions is very important specially, in agricultural sector. The major share of water use is daily consumption by humans for drinking, washing and cooking. Furthermore, population growth increases agricultural production demand, and this highlights the role of water resources management in the agricultural sector. The 1950’s studies showed 12 countries with a population of 20 million experienced water shortage. Virtual water is the volume of water which is consumed for a production from the beginning stage to the end. Scientists have shown that 96% of water footprints are related to crops, livestock and horticultural productions and only 4% it consumed as domestic water. Water balance data in Qom province shows that 90% of water resources are using in the agricultural sector. Investigation of water footprints in the agricultural sector is highly beneficial to improve water resources management in arid and semi-arid regions such as Qom. Materials and Methods: The research was conducted to find out the production and cultivation water needs in the agricultural sector for 10 years, via calculating the gray, blue and green water footprints using Mekonnen and Hoekstra models. In the livestock sector, water footprint’s information such as the number of livestock and poultry, production of red meat, chicken meat, egg and milk were also determined using the Mekonnen and Hoekstra. The water footprint in fertilizer was calculated using a questionnaire survey. Excel and SAS apps were used to analyze the collected data for all three study sections. Results and Discussion: The results showed that the water footprint in wheat, barley, cotton, onion, tomato, melon, watermelon, alfalfa, and corn were 3018, 2882, 10960, 1463, 1525, 960, 2504, 1683 and 416 m3/ton, respectively. The low irrigation efficiency led to a very high amount of white water footprint in the productions. Green water footprint was very low due to the lack of rainfall. In the livestock sector, the water footprint in red meat and milk were 39 m3/kg and 2.42 m3/lit, respectively which were much more than the global average. In the poultry sector, the water footprint in chicken meat and egg were 7.4 and 4.34 m3/kg, respectively, that were very high compared to the global average. The water footprint in fertilizer for wheat, barley, cotton and alfalfa productions were 2.62, 1.19, 1.07 and 2.54 m3/kg and this amount was higher under nitrogen fertilizer. The average virtual water footprint for chicken meat production in Qom province was 7.4 m3/kg. This amount in the world, USA, India, Russia, Mexico and the Netherlands is equal to 3.92, 2.39, 7.74, 5.76, 5.01 and 2.22 m3/kg respectively. In Netherlands, less water is in use in the agricultural sector than the other countries. In this country, the virtual water footprint in chicken meat is in the best position. India has the highest water consumption in poultry breeding with a consumption of 7.74 m3/kg. The average virtual water footprint in Iran for egg production is 4.34 m3/kg , while the average virtual water footprint for egg production in the world, USA, India, Russia, Mexico and the Netherlands is 3.34, 1.51, 7.53, 4.92, 4.28, and 1.4 m3/kg, respectively. India consumes the most water in the production of eggs such as chicken with a quantity of 7.53 m3/kg and the Netherlands has the least consumption with a value of 1.4 m3/kg . Conclusion: The concept of virtual water footprint in each region reduces the pressure on water resources. For better management in agricultural regions, it is possible to prevent the cultivation of high water demand crops. The most common cause of high water footprint in livestock and poultry is nutrition, so, internationally food import can be a good solution. Industrialization of poultry can also reduce water footprint. The implementation of this research can be a useful clue to the sustainable control and management of water resources and achieving an optimal cultivation pattern in our country and all provinces facing limited water resources.
Irrigation
A,. Uossef gomrokchi; J. Baghani; F. Abbasi
Abstract
Introduction: One of the modeling methods researchers have considered in various sciences in recent years is artificial neural network modeling. In addition to the artificial neural network and regression models, today, the capabilities of data mining methods have been used to improve the output results ...
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Introduction: One of the modeling methods researchers have considered in various sciences in recent years is artificial neural network modeling. In addition to the artificial neural network and regression models, today, the capabilities of data mining methods have been used to improve the output results of prediction models and field information analysis. Tree models (decision trees) along with decision rules are one of the data mining methods. Tree models are a way of representing a set of rules that lead to a category or value. These models are made by sequentially separating data into separate groups, and the goal in this process is to increase the distance between groups in each separation. Research shows that plant yield is a function of various plant, climatic, and water, and soil management conditions. Therefore, calculating the amount of plant yield and related indices follows complex nonlinear relationships that also have special difficulty in modeling. Considering that the response of irrigated wheat to different inputs in different climates by field method is time-consuming, costly, and in some cases impossible, so the introduction of an efficient model that can predict yield and analyze yield sensitivity to various parameters is a great help. It will be to solve this problem. This study aimed to develop and evaluate the capability of three models of the neural network, tree, and multivariate linear regression in predicting wheat yield based on parameters affecting its yield in major wheat production hubs in the country. Materials and Methods: The information used in this study includes the volume of water consumption and yield of irrigated wheat and the committees related to these two indicators in irrigated wheat fields under the management of farmers (241 farms) in the provinces of Khuzestan, Fars, Golestan, Hamadan, Kermanshah, Khorasan Razavi, Ardabil, East Azerbaijan, West Azerbaijan, Semnan, south of Kerman and Qazvin, which were harvested in a field study in the 2016-17 growing season. According to the Ministry of Jihad for Agriculture statistics, these provinces have the highest area under irrigated wheat cultivation in the country and cover about 70% of the area under cultivation and production of this crop in the country. One of the most widely used monitored neural networks is the Perceptron multilayer network with error replication algorithm, which is suitable for a wide range of applications such as pattern recognition, interpolation, prediction, and process modeling. In the present study, in order to develop the neural network, the capabilities of R software with Neuralnet package have been used. After the normalization step, the data were randomized. This step aims to have a set of inputs and outputs in which the input-output categories do not have a special system. After the randomization of the data, the amount of information that should be used in the network training process is determined. This part of the data was considered for training (70%) and another part for network test (30%). Perceptron neural network activator functions in the implementation of network training and testing. The hyperbolic tangent activity function has been used to limit the range of output data from each neuron and the pattern-to-pattern training process. In the present study and the neural network modeling capability, the tree model method has been used to predict wheat yield. Tree modeling is one of the most powerful and common tools for classification and forecasting. The tree model, unlike the neural network model, produces the law. One of the advantages of the decision tree over the neural network is that it is resistant to input data noise. The tree model divides the data into different sections based on binary divisions. Each data partition can be re-subdivided into another binary, and a model fitted to each subdivision. In this research, the capabilities of WEKA software have been used to run a tree model. It is worth noting that after grouping, the prediction model is applied to the grouped data. Results and Discussion: In this study, the efficiency of three models of the artificial neural network, multivariate linear regression, and tree model to predict the performance of irrigated wheat in major production areas in the country was evaluated based on field information recorded in 241 farms. The results showed that the coefficient of explanation of the model in predicting the yield of wheat production in the model of artificial neural network and a multivariate linear regression model was 0.672 and 0.577, respectively, which was applied by grouping the data by tree method. The coefficient of explanation has been increased to 0.762. The output results of the tree model showed that the major wheat production areas in Iran in terms of water consumption could be divided into four independent groups. Finally, it can be concluded that the tree model, considering the purposeful grouping in the input data, can be used as a powerful tool in estimating irrigated wheat yield in major wheat production areas in Iran. Conclusion: In this study, the need to use data mining methods in analyzing field information and organizing large databases and the usefulness of data mining methods, especially the decision tree in estimating wheat crop yield, were investigated and compared with other forecasting methods. The general results of the research show that purposeful separation of input data into forecasting models can increase the output accuracy of forecasting models. However, it is not possible to provide a general approach to selecting or not selecting a forecasting model in different regions. In some studies, neural networks have shown a high ability to predict the performance of different products, but it is important to note that if there is sufficient data and correct understanding of the factors affecting the dependent variable, the accuracy of the models can be applied by data mining methods. It also improved the neural network. In a general approach, considering the accuracy of estimating the predicted models under study, these techniques can be used to estimate other late-finding characteristics of plants and soil.
Irrigation
M.H. Naderi; N. Arab; O. Jahandideh; Meysam Salarijazi; A. Aarb
Abstract
Introduction: Hydrological variability is of great importance for water resources management. Analyzing the instream environmental flow demand by coupling the hydrological cycle and the hydrodynamic process with aquatic ecological processes at a watershed scale remains one of the most important yet most ...
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Introduction: Hydrological variability is of great importance for water resources management. Analyzing the instream environmental flow demand by coupling the hydrological cycle and the hydrodynamic process with aquatic ecological processes at a watershed scale remains one of the most important yet most difficult issues. Ecological water demand (environmental flow) refers to the typical—intra-annual and inter-annual natural flow regime variability—which describes the quality, quantity, and timing of flow discharge required to preserve the ecosystem and sustain essential services upon which human livelihoods and well-being depend. Therefore, ecological water demand (EWD) should be considered as a constraint in water resource planning and management.
Materials and Methods: Numerous methods and frameworks have been developed for establishing ecological water demand at regulated rivers. Hydrologically-based ecological water demand methods, because of their simplicity, data availability, and other economic and social aspects, remain the most applied ones. A suitable range of discharges environmental flow Dinavar River was estimated using advocate statistical analysis of hydrological methods Tennant, Annual Distribution Method, and Texas, coupled with habitat suitability model using the program River2D to natural flow variability need. River2D is a two-dimensional, depth-averaged hydrodynamic and fish habitat model widely used in environmental flow assessment studies. A detailed digital model of the river channel and its surrounding area was developed, including all the morphological characteristics of the river channel and its various sandy islets. Data collection was performed through GIS/GPS mapping surveys, hydro-morphological measurements (water depth, flow, substratum type, etc.), and electrofishing samplings at a microhabitat scale under different discharge conditions. Several different steady-state hydraulic simulations were conducted under typical low flow conditions, producing water depth and water velocity (direction and magnitude) maps for each discharge scenario, while results were verified with the use of field measurements. In the next step, River2D was used for the fish habitat modeling of the study area, with the application of fish preference curves developed specifically for the study area. Finally, the fish habitat modeling was conducted for the Capoeta trutta (Heckel, 1843) species, divided into two life groups, forced under the flow conditions. Also, the suitable level of ecological water demand and crucial values with different flow frequencies were analyzed, including water level, water surface width, and Weighted Usable Area.
Results and Discussion: Results show that high environmental flow releases did not necessarily provide the highest habitat availability and suitability at all seasons and fish life-stages. The adult life stage resulted in being more vulnerable to water diversion, particularly during the spring season. Shallow-water hydromorphological units suffered the highest habitat loss. Some of the environmental flow methods demonstrated inconsistent results over seasons and fish life-stages by either allowing for higher environmental flow releases. Also, the Weighted Usable Area -Discharge curve was calculated with the suitability index in medium flow conditions. From the result, the Weighted Usable Area is changed according to flowrate. In the flowrate- Weighted Usable Area/A graph, ecological flow can be determined at 1.38 m3/s for Capoeta trutta (Heckel, 1843) species. Ecological flows were calculated in the range 0.17–3.71 m3/s as the required discharge, which assures the welfare and sustainability of protected fish species populations. It was also noticed that low flow months (June to November) required more proportions of mean monthly flow than high flow months (December to May). When compared with flow-duration analysis, it is demonstrative that simulation results fitted EWD considering the quantity of available habitat for fish species. Also, the results of the study indicated that monthly EWD had an increasing trend during the flood season and a decreasing trend during the non-flood season in three sections at different suitable levels. With the increase of suitable levels, the range of EWD in the three sections also increased. The EWD and crucial values were the lowest in April with the smallest range and were the highest from June to October.
Conclusion: The major finding of this research is that the estimated Suitable Range of Discharges could better address environmental water requirements, rather than simply allocating single value minimum ecological flows. Results reveal that the ecohydraulic modeling of river basins should be considered as an indispensable component in sustainable water resources.
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.
Irrigation
A. Aliverdi; S. Karami; H. Hamami
Abstract
Introduction: Since rainfall occurs often in the fall and winter, water is an important limiting factor to subsequent growing crops especially those in hot seasons like soybean. Therefore, there is a growing focus on increasing water use efficiency in crops in recent years. Recently, an irrigation technique ...
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Introduction: Since rainfall occurs often in the fall and winter, water is an important limiting factor to subsequent growing crops especially those in hot seasons like soybean. Therefore, there is a growing focus on increasing water use efficiency in crops in recent years. Recently, an irrigation technique so-called magnetized water has been introduced to increase water use efficiency. The researchers have reported that the physical and chemical properties of water including electrical conductivity, volatility, pH, solubility, surface tension, and viscosity can be affected by its passage through the magnetic field. Subsequently, these changes lead to alterations in soil electrical conductivity, soil nutrient mobility, soil water holding capacity, water passage through the soil profile and soil pH. Increased water use efficiency in soybean (11%) and many leguminous crops have been demonstrated through their irrigation with magnetized water. However, those studies have provided no information about the status of bacterial nodulation on legume root in such an irrigation method. Therefore, the main purpose of this study was to investigate the effect of irrigation with magnetized water on five soybean varieties on their symbiosis with specific bacteria (Bradyrhizobium japonicum). Materials and Methods: The experiment was conducted in the open air at the Bu Ali Sina University of Hamedan in 2018. A completely randomized design with two factors (soybean cultivar and irrigation water type) and eight replications was applied. The soybean cultivar had five levels (Amir, Zan, Saba, Kosar, and Hobbit) and irrigation water type had two levels (untreated and magnetically treated water). An equal volume of water (1 liter) was added to each pot every two days. Before adding water to pots for the irrigation with magnetized water, we passed it through a magnetic tube with a 35 cm long, 1-inch radius and a 0.68 T magnetic field intensity. On August 26, the plants of the half of replications were harvested to measure shoot dry weight, root dry weight, number of nodules, nodule dry weight, shoot nitrogen content and root nitrogen content. On September 10, the plants of the other half of replications were harvested to measure individual seed yield and its components (number of pods per plant, number of seeds per pod and 100-seed weight). By dividing the seed yield obtained from each pot to the total volume of water added to each pot during the growing season, water use efficiency can be calculated. Results and Discussion: The soybean seedlings irrigated with magnetized water were green 1 to 2 days earlier than those irrigated with untreated water. The number of seeds per pod was not affected by soybean cultivar, irrigation water type, and their interaction. In other traits, the simple effects of soybean cultivar and irrigation water type and their interaction were significant at the 5% level of probability. The cultivars of Amir and Saba irrigated with magnetized water led to a higher shoot dry weight to root ratio, indicating the allocation of more resources to the shoot than to the root. The number of nodules formed on the root of all soybean cultivars (Amir (33.7%), Zan (55.3%), Saba (40.1%), Kosar (62.7%) and Hobbit (51.6%)) increased when they were irrigated with magnetized water. However, only in Zan (0.70%) and Kosar (45.1%), irrigation with magnetized water significantly increased the dry weight of nodules. The individual seed yield in all soybean cultivars (Amir (34.8%), Zan (35.1%), Saba (43.4%), Kosar (26.8%) and Hobbit (21.3%)) was significantly increased by irrigation with magnetized water, indicating an improved water use efficiency in soybean irrigated with magnetized water. Based on previous research, the most suitable soil pH range for bacterial growth and activity was found to be between 6.5 and 7.0. On the other hand, other researchers have shown that irrigation with magnetized water reduces the soil pH by approximately 0.5 units. Hence, in our experiment, irrigation with magnetized water probably caused the initial soil pH which was 7.6 to be closer to the optimal range for bacterial activity. Also, according to previous study, bacterial activity is also dependent on soil dry conditions. On the other hand, other researchers have shown that irrigation with magnetized water increases soil water storage capacity due to reduced water vaporization. Therefore, in our experiment, irrigation with magnetized water probably provided good moisture conditions for bacterial activity. Conclusion: The results showed that the irrigation of soybean with magnetized water improved its symbiosis with its specific rhizobium. Improved symbiosis increased plant seed yield and water use efficiency. Therefore, improved symbiosis by irrigating soybean with magnetized water can reduce the reliance on nitrogen fertilizer application in this plant. It can also improve the status of soil fertility for other crops in crop rotation.
