فهرست مطالب نسرین آزاد

One of the new ways to save water and reduce irrigation costs is the use of superabsorbents. Since the zeolite nanoparticle has a larger specific surface area, it can absorb water and nutrients and release them when the plant needs them. A two-year greenhouse experiment was conducted to investigate the effect of different levels of irrigation and nanozeolite on growth indicators, relative water content and ion leakage in basil plants. The experiment was done as chopped plots in the form of randomized complete blocks with three replications. The experimental treatments included irrigation levels at three levels (I1 = 0.75 FC or underwatering, FC = I2 or normal irrigation and I3 = 1.25 FC or overwatering) and nanozeolite superabsorbent levels in four levels (Z0 without superabsorbent, Z5 five grams of superabsorbent per kilogram of soil, Z10, 10 grams of superabsorbent per kilogram of soil and Z15 was 15 grams of superabsorbent per kilogram of soil). The results showed that with the increase in drought severity, diameter and height growth and other traits such as the number of leaves, leaf surface, weight of dry matter (biomass) of basil, the irrigation level decreased significantly by 75Percent, leading to a decrease in vegetative traits, a decrease in the relative water content of the leaves. and increased ionic leakage, also the results showed that the use of nanozeolite has a significant effect at the level of 1Percent on the investigated parameters, so that the use of this superabsorbent in the amount of 5 and 10 grams per kilogram of soil in all irrigation treatments (I1, I2, I3) ) by increasing the height of the plant stem by 22 and 30Percent in two consecutive years, as well as increasing the diameter of the basil stem by 33 and 29Percent respectively, increasing the number of lateral branches of basil in two years by 90 and 89Percent, respectively. The increase in the number of basil leaves was 49 and 76Percent, respectively, and the growth of the leaf surface was also increased by 25 and 19Percent, respectively. The dry weight of the plant increased by 40Percent and 30Percent, respectively, and the relative water content of the leaves increased by 14Percent and 7Percent in two consecutive years. In electrolyte leakage, contrary to the previous parameters, the application of superabsorbent reduced the ionic leakage of basil, but with the application of low irrigation, we saw an increase in this parameter. This study showed that there is a statistically significant difference (P>0.5) in the yield of the crop among treatments Z5, There is no Z10.

Water shortage is the most important factor in reducing the yield of agricultural products all over the world and this factor is more effective in arid and semi-arid regions. Iran is a country whose average rainfall is about one-third of the global average, and in terms of water resources, it is in dire straits. Therefore, it is necessary to help preserve limited water resources by optimal use, saving and increasing irrigation efficiency. This research was defined according to the consumption of the strategic product of corn and the importance of managing the country's limited renewable water resources, on top of that, the use of pressurized irrigation systems in the region and in the climatic conditions of Urmia.

In order to investigate different levels of irrigation on performance indicators and plant traits of sweet corn, under the subsurface drip irrigation system in the form of a complete randomized block design with four treatments of 20% over-irrigation, equal to the water requirement, 20 and 40% under-irrigation in four replicates in the research farm of the Engineering Department. water of Urmia University. The plant index values of stem diameter, leaf area, grain yield, number of leaves per stem, biological yield (wet), plant dry matter and cob yield during the growing season on specific dates and also on the day of harvest. was taken and evaluated.

The results showed that in general, the effects of under-irrigation and over-irrigation on biological yield, dry matter, uncoated cob yield, 300 seed weight, number of leaves and stem diameter were significant. Also, based on the results, it can be stated that with the reduction of water consumption, the cob yield decreases linearly. The highest and lowest cob yields were obtained in overwatering and 60% water requirement treatments with an average of 1.83 and 1.13 kg/m2, respectively.

In general, under-irrigation and over-irrigation have a significant effect on biological yield, dry matter, uncoated bale yield, three hundred weight, number of leaves and stem diameter. Also, based on the results, it can be stated that with the reduction of water consumption, the quantity of cobs decreases linearly. The highest and lowest cob yields were obtained in over-irrigation and 60% water requirement treatments with an average of 1.83 and 1.13 weight per square meter, respectively. According to the results of the research, with a 20% reduction in water consumption compared to full irrigation, only 5.02% of the biomass weight is reduced, apart from significance. Control (equal to water requirement) and 20% less irrigation in dry matter traits, uncoated cob yield, 300 seed weight, number of leaves and stem diameter, no significant difference was observed. The process of changes in the accumulation rate of biological yield of sweet corn initially started from 21 days after planting and after 6-9 days it entered the linear growth stage and then continued steadily. The highest weight of biological yield of sweet corn in different treatments was observed in 87 days after planting.

Planning for the best use of water resources in agriculture is inevitable. In this regard, the method of subsurface drip irrigation can, in addition to reducing the amount of irrigation water, increase crop yield. This study was conducted to investigate the different levels of under-irrigation and over-irrigation on yield indices and plant traits of sweet corn cultivar CHASE, under subsurface drip irrigation system in a randomized complete block design with four treatments of 20 Percent over-irrigation, equal to water requirement, 20 and 40 Percent under-irrigation in four Repeated. The results showed that in general, the effects of under-irrigation and over-irrigation on cob yield, 1000-seed weight, uncovered cob diameter, pod-free cob length, number of cob rows and number of seeds were significant. Also, based on the results, it can be stated that by reducing the amount of water consumption, the yield of the product decreases linearly. The highest and lowest cob yields were obtained in over-irrigation treatments and 60 Percent of water requirement with an average of 30.4 and 19.9 tons per hectare, respectively. Accordingly, with a 20 Percent reduction in water consumption compared to full irrigation, only 4.72 Percent of the crop is significantly reduced. This is while with a 20 Percent increase in irrigation water, the yield of cob increases by 10.54 Percent. 1000-seed weight in full irrigation and 20 Percent low irrigation treatments was 375.7 and 372.6 g, respectively. There was no significant difference between over-irrigation and 20 Percent under-irrigation treatment. There was a significant difference between the means of ear yield indices, length and number of seeds per ear row in all irrigation treatments.

Optimization of cropping pattern can be the best approach to reduce water consumption with maintaining maintain or increasing agricultural productions and consequently increase farmers' incomes. In this research, the cropping pattern of Mahabad irrigation and drainage network (with an approximation area of 12,000 ha) was determined using the PSO optimization algorithm with the objective of increasing the net benefit of the network based on the specified amount of delivered water and increasing water productivity. Optimization was done in 6 treatments of full and deficient irrigation and two strategies of deficient irrigation implementation (H1: in delivered water to the network and farm and H2: in delivered water to the network). Finally, the amount of water consumption, net benefit and economic productivity in the optimal cropping pattern were compared with the present condition. The results showed that in H1 strategy, with water consumption equal to the present condition, the amount of net benefit and economic productivity in the optimum cropping pattern increased about 16.7% compared to the current situation. In H2 strategy, productivity increased compared to the present situation in all treatments. Even by a reduction of about 40% of delivered water to the network, economic productivity increased about 37% compared to the present condition.

In the present research, the climate change effect on variation of surface runoff of Zarrinehrud located in the Miandoab plain was investigated. In this direction, the scenarios including A1B, A2 and B1 via LARS-WG downscaling model and with applying the HadCM3 general circulation model and artificial neural network model in two different periods (2046-2065, 2080 -2099) were studied. For this purpose, the best combination of input parameters of the MLP artificial neural network model was selected to estimate the runoff among various meteorological parameters with time delay of zero and one day and runoff parameter with one-day delay. Then, the meteorological data predicted by the LARS-WG in the future were used as inputs for the selected neural network model and consequently the runoff was predicted. The comparison of results between observed and simulated data by LARS-WG model using different statistical and error measurement indices indicates that there is no significant difference between simulated and observed values. Performance analysis of the artificial neural network model indicates that the mentioned model has good and suitable accuracy to simulate the runoff variations in the studied area. The results showed that the average annual runoff in the period of 2046-2065 will increase about 4.62 CMS than base period and it will decrease about 14.7 CMS during the period 2080-2099 compared to the base period.

Nitrogen is one the most important nutrients in achieving optimal yield of crops. The objective of this study was to investigate the effect of clinoptilolite zeolite on nitrate ion adsorbstion and growth indices and cucumber parameters including, number, weight, length and diameter of the cucumber. This research was conducted at greenhouse of the Faculty of Agriculture of Urmia University and in completely randomized design experiment with four levels including 0, 5, 10 and 15 gr zeolite per kg of sandy loam soil in three replications with drip irrigation system.The results show that zeolite has positive effect of on reducing nitrate leaching at p < 0.01 level.Comparing the averages, it showed that there was a statistically significant difference between the control treatment and 15 g zeolite per kg of soil. Also, results showed that the application of zeolite on crop yield (Multiplied by fruit number in fruit weight), number of fruits, leaf area and plant diameter was significant at p < 0.01 level and also on fruit weight, fruit diameter, fruit length and plant height at p < 0.05 probability but had significant effect on leaf number. Increasing amount of zeolite cause to increase yield by 2.6 time greater than control treatment.

Estimating the parameters of infiltration equation and Manning’s roughness coefficient are essential for the optimal design and evaluation of surface irrigation systems. The present study was carried out to calibrate these coefficients for a closed-end border irrigation system with four series of field information. In this regard, the hydraulic surface water flow is simulated using zero-inertia model by WinSRFR simulation model that linked to the particle swarm optimization algorithm for repetitive calculations. The objective function of the optimization problem was the minimization of the difference between the calculated and measured times of advance and recession phases, and four coefficients of the modified Kostiakov equation and Manning’s roughness coefficient were considered as decision variables. The sensitivity analysis of the developed model showed that the coefficient b of infiltration equation in the recession phase and the Manning’s roughness coefficient in the advance phase have the most errors in the predicted results. The results showed that based on the optimized parameters in the model, the values of root mean square error, RMSE, were obtained between 3.77 to 12.86 minutes and the coefficients of residual mass were varied between -0.099 and 0.003 to predict the advance and recession times in the four experimental irrigations. Based on results, with optimization of WinSRFR model, there is accessibility to achieve in application efficiency and distribution uniformity about 86 and 84 percent, respectively (with adequacy about 100 percent) by flow variable (inflow rate and cutoff time).

In the present research, the climate change effect on groundwater resources of Miandoab plain in West Azerbaijan province was investigated. In this direction, the scenarios including A1B, A2 and B1 via LARS-WG downscaling model and with applying the HadCM3 general circulation model and artificial neural network model in two different periods (2046-2065, 2080 -2099) were studied. For this purpose, monthly groundwater depths data of 25 piezometric wells in the Miandoab plain with a 10-year statistical period (2005-2014) and daily and monthly data of rainfall, minimum and maximum temperatures and sunshine hours of the Miandoab synoptic station in a 20-year statistical period (1995-2014) were used. The evaluation results of the observed and simulated data by the LARS-WG model, using different statistical indices indicates that there is no significant differences between simulated and observed values. The performance analysis of the artificial neural network model shows that the mentioned model has good and suitable accuracy in simulating the changes in groundwater depth in the studied plain. The results showed that the average depth of groundwater level in the first period (2046-2065) and the second period (2080-2099) increases 2.87% and 9.3%, respectively. In fact, considerable augmentation of temperature and consequently increasing the groundwater consumption cause to deeper depth of the groundwater.

The main problem in surface irrigation systems is the low irrigation efficiency due to poor management, inaccurate estimation of design parameters and inadequate design. Losses in surface irrigation include deep infiltration and runoff, which is one of the ways to increase the efficiency of border irrigation, using closed-end mode in irrigation systems. This research was conducted to evaluate the effects of geometrical variables (slope and length of border) and flow control (inlet flow rate and cut-off time) on application efficiency and uniformity of water distribution in closed-end border irrigation system. The length, slope, inflow rate, and cut-off time are considered as the decision-making variables for developing the multi-objective genetic algorithm based on the non-dominated sorting. For this purpose, three irrigation borders with closed-end system were considered in the Ramshir network. The optimization algorithm for calculating the objective functions involves maximizing the minimum water depth and minimizing the infiltration depth in a modeling loop. The optimization algorithm was linked to WinSRFR 4.1.3 software to calculate the objective functions. The results showed that the best combination of inflow rate and the cut-off time for 75 mm of required water depth was 1.9 lit/s/m and 150 min, respectively, which increased application efficiency and distribution uniformity to 79 and 78 percent. Furthermore, the application efficiency in the closed-end border irrigation system is higher (30% to 50%) than the open end method in different scenarios.

Use of subsurface drip irrigation (SDI) in row plants is increasing due to higher water and fertilizer efficiency. In order to investigate the effect of SDI levels and nitrogen fertilizer splitting on yield, yield components and water productivity of corn, a field study was conducted in 2018 as split plot experiment based on a completely randomized block design with three replications at the research farm of Urmia University. The main plots of this experiment including three irrigation levels: 100%, 75% and 50% of net irrigation requirement and subplots included three nitrogen fertilizer split applications as: weekly, every other week and three times during growing season as urea fertilizer. Based on the results, the effect of irrigation levels treatment and number of fertilizer splitting on yield, yield components and water productivity were significant at 1% level. However, the effect of fertilizer splitting on water productivity was not significant. Interaction effects of the two variable treatments on plant height and leaf area index were significant at 1% level but did not significantly affect grain yield, biomass and water productivity. The highest grain yield and corn biomass were obtained with 22.39 and 39.85 ton/ha for complete irrigation, respectively. Also, the grain yield and biomass in the three- split treatments were highest with 18.47 and 32.56 ton/ha, respectively. The highest water productivity was obtained by irrigation application of 75% of net water requirement. It seems that in regions with water scarcity, applying deficit irrigation equal to 75% of the corn irrigation requirement, can be a good solution for saving water and achieving high water productivity. Also, fertilizer injection with higher amounts and less frequency especially at the sensitive growth stages, can be a more effective solution than using lower amounts with more frequent fertilizer application.

The accurate prediction of soil hydraulic parameters is essential to simulate the transport of water, solutes and contaminants in soil, management of the agricultural water, management of production and in soil and water conservation. The least squares regression is the most common method applied for fitting the soil-water retention curve (SWRC) function to the observed data-points to optimize its parameters. However, the variance of SWRC data varies in different moisture content and therefore, unlike the wet-end of SWRC, the conventional unweighted regression method may not be sufficiently effective in estimating its dry-end (higher suctions). While, selected soil processes, such as soil moisture redistribution or transport of contaminants in soil occur in low soil moisture contents which correspond to the dry-end of the curve. Consequently, in fitting different hydraulic functions to SWRC, the accuracy of SWRC parameters would be improved in the low-moisture range content by determining the appropriate weights for data points. Accordingly, the objective of this study was to investigate the effect of properly weighting the SWRC data points on increasing the accuracy of the estimated soil hydraulic parameters. In this study, undistributed soil samples were collected from 20 cm soil depth with six replications. The SWRC of the samples were measured at suctions of 0 to 15000 cm. In order to fit the van Genuchten equation of SWRC on measured values of h(θ) and to estimate its hydraulic parameters through RETC code, the weighted least squares regression method was also used along with the conventional standard least squares regression method. For this purpose, some weights were assigned to the data points as the inverse of the variance of the measured volumetric soil water content in six replications, so that, the effect of the curve estimation error in low moisture contents were considered by assigning larger weights in the regression fitting. Finally, the accuracy of unweighted and weighted regression in the fitting of the SWRC model on the measured data was compared using statistical criteria and a suitable method for the averaging of hydraulic parameters was introduced. Comparison of the fitted hydraulic parameters by unweighted and weighted regression showed that the mean values of the residual water content (Ɵr), saturated water content (Ɵs) and α parameter (reciprocal of air-entry suction) in the weighted method were lower than the unweighted method, however the n parameter values obtained by the weighted method were higher than unweighted method. Reproduction of SWRC using the values hydraulic parameters estimated by either unweighted or weighted methods showed that the weighted method increases the accuracy of the estimation and reduces the percentage of point error in lower moisture contents (higher suctions) compared to the unweighted method. Although, the weighting method generally increased the error of SWRC estimation and decreased the correlation between estimated and observed moisture content. We found that, in both unweighted and weighted regression, the method II (averaging of volumetric water contents at different suctions and estimating hydraulic parameters) had a lower error in compression to method I (averaging of hydraulic parameters). However, in estimation of SWRC in lower moisture contents, the method I had lower point error than that of method II. The method I reduced the error percentage in the weighting method. Assigning proper weight to SWRC data points improves curve fitting in lower moisture range, which is very important in simulating redistribution of moisture or transfer of contaminants transport in the soil processes, particularly in arid and semi-arid conditions.

Managing and monitoring of salinity is one of the most important affair in agriculture, especially in arid and semi-arid area. For this purpose we have to use new technology like remote sensing and GIS. The relationship between soil parameters with satellite data is an effective step for predicting soil salinity. In this study we use multivariable regression based on relationship between topographical properties and extracted indices from Landsat 8 satellite for predicting soil salinity in Urmia. For predicting soil salinity, samples of 40 points from 0-30 cm soil depth were taken. Electrical conductivity from soil saturation extract (ECe) was measured. After performing the necessary processing on satellite images, pixel values in the different bands were extracted. The data was divided into two series: Training data (80%), validation data (20%). The relationship between satellite data and results of multivariable linear regression methods predicted, accuracy of the model by using factors such as R- squared, standard error of the mean, adjusted R-squared and Durbin Watson statistic evaluated. Results showed that model predicted with correlation coefficient, standard error of the mean, adjusted R-squared and Durbin Watson statistic were 70.3, 10.03, 61.8 and 1.709 respectively. Finally, the model evaluated by statistical indices. The indices values of Geometric Mean Error Ratio (GMER), R- squared (R2) and Root Mean Square Error (RMSE) measured 0.867, 0.638 and 0.354 respectively. The results showed that the model has a better estimation of soil salinity.

Managing nitrogen fertilizers application in the field is an effective tool to mitigate groundwater pollution. The objective of this research was to investigate the effect of various fertigation scenarios on the nitrate leaching and nitrogen absorption by corn in surface tape micro-irrigation system and sandy clay loam soil. For this purpose, HYDRUS-2D model was used to simulate water and nitrogen movement in soil and the requirement data for the model calibration and validation were collected by the field experiments. Then, the nitrogen uptake and nitrate leaching in the different fertigation frequencies were simulated in the calibrated model. The mentioned scenarios in a sandy loam soil were also exerted to compare with the results of the previous stage. The results showed that the nitrate uptake by the plant, leaching and its accumulation at the end of the growth season in the root zone were similar in weekly and biweekly frequencies in the studied soils. Reducing the number of fertigation frequencies to three splits, nitrate uptake by the plant in sandy clay loam soil increased to 73 percent and total losses of leaching and accumulation in the root zone, decreased to 27 percent. However, in three-stage splits in sandy loam soil, the nitrate uptake by the plant decreased to 48 percent and total nitrate losses increased to 52 percent.

The purpose of this research was to analyze surge irrigation system performance and optimize the design and management parameters. In this order, by creating furrows with a length of 80 m and 1.1% slope and implementing four treatments of surge irrigation in two inflow rates of 0.6 and 0.8 lit/s and two cycle times of 40 and 50 minutes, different water and soil parameters were collected and SIRMOD (surface irrigation model) was calibrated and evaluated. Then, the iso-performance contour plots of irrigation system were obtained to optimize cutoff time and inflow rate under maximizing of application efficiency, distribution uniformity and requirement efficiency. The results indicated that in the experimented furrows with the texture of sandy loam, by providing requirement efficiency of 100%, in inflow rate of 1.2 lit/s and cutoff time of 170 min, distribution uniformity and application efficiency will be 84% and 60% respectively. According to the results, by providing requirement efficiency of 100% and considering the best length of the furrow in different inflow rates, application efficiency increases up to maximum 65%. But if the requirement efficiency of 90% to be considered, at different inflow rates in certain length of furrow, there is possibility of achieving to application efficiency up to 90%

In this research, NTC thermistors with composition of NiMn2-xCoxO4 (x = 0.4, 0.8, 1.2,1.6) prepared by two

solid state reaction and sol-gel (gel-combustion). The average particle size was monitored and structure of the calcinated powders have been investigated using x-ray diffraction (XRD) and tunneling electron microscopy (TEM) techniques. The averag particle size was estimated to be about 65nm with the cubic and cubic + tetragona phases for low and high cobalt concentrations, respectively. The grain size of samples verifies with scanning electron microscopy (SEM) images. Upon increasing the cobalt fraction, the grain size of samples increases from about 2μm to a few μm in size. The electrical properties of these thermistors depend on the grain size. The grain size of samples made from sol-gel is smaller than from solid state reaction under the same condition. For longer sintering time of the samples prepared by gel-combustion method, the grain size was increased then the electrical parameters of nanopowder improved and we obtain better results than the samples prepared from solid state reaction.