Iranian Journal of Soil and Water Research
Year:2020 | Volume:51 | Issue:3|Papers Count:20

The agricultural sector is particularly important in the economic growth and development of different societies. The application of Nitrogen fertilizer is one of the most influential factors in agricultural productivity enhancement. Management and optimum fertilizer consumption based on field or greenhouse experiments are time and cost consuming. Therefore, the application of models that simulate the effects of different fertility stresses on crop production are useful tools in fertilizer planning and optimization. In the AquaCrop model, the crop biomass is simulated using a semi-quantitative method. The purpose of this study was to simulate basil response to different fertilizer treatments and evaluate the semi-quantitative method used in the AquaCrop model. For this purpose, a study was carried out in a research greenhouse of the College of Agriculture and Natural Resources, University of Tehran, during two growth periods. Five levels of nitrogen fertilizer application (Urea fertilizer) with three replications was investigated to find out the effect of fertility stress on basil yield. Initially, the semi-quantitative method was calibrated. The calibration results showed that the normalized water productivity coefficient decreased by 41%. Then, the AquaCrop model was validated using statistical measures to estimate biomass and canopy cover. The variation range for R 2, MBE and RRMSE indices for crop biomass were 0. 95-0. 98, 1. 72-21. 56 g m-2, 17/42-19. 07% and for canopy cover were 0. 66-0. 78, 6. 44-12. 86% and 19. 66-21. 83%, respectively. According to the results, the AquaCrop model and the semiquantitative method can be used as a suitable tool to simulate crop growth under soil fertility stress conditions.

Deficit irrigation is a method for water use management that water use efficiency increases by eliminating excess water. Application of crop growth regulators such as Salicylic Acid increase the resistance of crops under water stress. The purpose of the current study was to investigate the effect of Salicylic Acid foliar application under deficit irrigation conditions on yield of cucumber and water use efficiency. This study was contacted as factorial test based on randomized complete blocks in 3 treatments since June to November 2018 in The Research Filed of University of Zanjan on cucumber (cv. Kish F1). Experimental treatments were Salicylic Acid concentration in 3 levels (3. 0, 1. 5 and 0. 0 mM) and irrigation water amount in 3 levels (100, 80 and 60% of crop water requirement). The control treatment was 100% crop water requirement and 0. 0 mM Salicylic Acid. Based on the results, the foliar applicasion of 3. 0 mM Salicylic Acid increased chlorophyll index, 32% at 100% crop water requirement and leaf area and relative water contants, 21% and 9. 4% (respectivevly) at 80% crop water requirement as compared to the control treatment. Maximum means of fruits number per plant, total yield and water use efficiency were obtained at 3. 0 mM salicylic acid foliar application (respectivevly 9. 9, 34. 1 ton/ha and 15. 1 kg/m 3 ) that they were 38. 4%, 39. 0% and 40. 0% more than the one in treatment of 0. 0 mM Salicylic Acid. Considering the results of current research, applicasion of 20% deficit irrigation and 3. 0 mM Salicylic Acid as foliar application are suggested for cucumber in the region of Zanjan.

In this study, the fractional-order differential equations in range of (0, 1) were used to model the water surface profile under Darcy's law condition in porous medium for a fully developed turbulent flow. The developed equation is solved analytically. The laboratory model used in this study consists of a coarse-grained porous medium with 6. 4 m length, 0. 8 m width and 1 m height, including rounded corner materials, which are tested for different flow rates and three longitudinal slopes of 0, 4, 20. 3%. Then, parameters of model and porous media were calibrated based on laboratory data. In order to evaluate the proposed analytical solution, the obtained results from fractional-order differential model were compared with the laboratory data. The results showed a satisfactory agreement with experimental data of water surface profile (seepage line) in all three slopes. The maximum error of the proposed model is 3. 5% compared to the experimental data. It can be concluded that the proposed method can provide better description of water surface profile analysis under nonDarcy flow conditions as compared to Darcy model in porous media.

Biochar has attracted the attention of many researchers because of its ability to improve soil fertility, immobilization of pollutants, as well as a suitable method of carbon sequestration and as a carbon reservoir. In order to investigate the effect of pyrolysis temperature and type of organic residues on physicochemical properties of biochars, a completely randomized designe as a factorial experiment was designed with two factors of organic residues type (wheat straw and walnut and almond bark) and pyrolysis temperature (300 and 500° C) in three replicates. The results showed that EC, pH, ash, and CEC of biochar increased at pyrolysis temperature of 300° C. By increasing the pyrolysis temperature to 500° C, the amount of organic carbon (OC), CEC, and surface functional groups of biochar decreased compared to biochar produced at 300 ° C whereas pH, ash, and EC increased. The highest EC, pH, water soluble materials, ash, and the lowest bulk density were recorded in wheat straw biochar produced at 500° C. The highest value of equivalent calcium carbonate was obtained in almond peel biochar produced at 500° C. Biochar production yield decreased and the loss of volatile compound such as CO2 increased by increasing the pyrolysis temperature from 300° C to 500° C. In addition, the characteristics of biochar were dependent on type of feedstock and pyrolysis conditions (temperature and time residence).

Atmospheric emissions from cement industry are one of the major sources of environmental pollution. To evaluate the effect of cement dust on some soil properties around Yasouj cement factory, 61soil samples were collected from different land uses at a depth of 0-30 cm. Different properties such as acidity (pH), electrical conductivity (EC), organic matter, calcium carbonate equivalent, sand, clay and silt percentages, total concentration of nickel, manganese, lead and cadmium were measured. The Kolmogorov-Smirnov test was used to verify the normality of the data. The results showed that the studied soils were calcareous, non-saline and alkaline and they had 18. 44 to 54 percent calcium carbonate equivalent, 0. 82 to 2. 19 percent organic matter, 0. 07 to 0. 96 dS/m electrical conductivity and 6. 72 to 8. 02 pH. Nickel, Manganese, Lead and Cadmium concentrations ranged from 214. 98 to 268. 34, 45 to 708, 2. 25 to 168. 75 and 0. 37 to 11. 12 mg kg-1, respectively. In the proposed samples, the mean concentration of nickel, manganese, lead and cadmium were 243. 53, 436. 46, 18. 47 and 0. 96 mg kg-1, respectively. The order of the average frequency of the heavy metals concentration was Mn> Ni> Pb> Cd. The concentration of nickel and cadmium in all soil samples and the concentration of manganese and lead in some soil samples around Yasuj cement factory were much higher than the USEPA standard levels. The high concentrations of these metals in surrounded soils are the result of different activities applied in the process of cement production and the movement of vehicles around the cement factory, illustrating the effect of pollutants released from this factory in increasing metals concentrations.

Water supply from groundwater resources because of rapid population growth and coastal zones development, converts the intensity of seawater intrusion to a global concern in these areas. Analyzing the sensitivity of costal aquifers' behavior to different controlling factors, preventing the seawater intrusion to these resources and the related adverse consequences is an essential effort. This study aimed to analyze the global sensitivity of factors controlling the seawater intrusion and the interaction of Caspian Sea water and the considered coastal aquifer. To assess the seawater intrusion, SUTRA, a three-dimensional density-dependent calibrated and validated numerical model, was employed. For this purpose, five well-known global sensitivity analysis methods have been employed and the sensitivity indices of each methods have been calculated. The permeability of first layer was the most sensitive parameter based on FAST, VBSA, PAWN and RSA methods among five considered methods. The fifth layer’ s permeability was found to be the most sensitive parameter by applying EE. Overall, the higher the permeability of extended layers nearer to coastline, the larger the seawater intrusion. Therefore, the permeability of such layers effectively contributes to seawater intrusion. These findings can be used to support the management-related decisions and prioritize the measurements conducted on the aquifer in the study area. Such decisions are not based on the local findings and consider all possible changes of layers' permeability, therefore cause to more reliability.

The potential of biochar for pollutant removal from aqueous solution greatly depends on biochar characteristics and its production conditions. The objective of this research was to investigate the efficiency of phosphorous adsorption from aqueous solution by date wood and sugarcane bagasse biochars produced at different pyrolysis temperature. For this purpose, biochars were produced at different temperatures (250, 400, 550 ˚ C) and their physio-chemical characteristics were measured. Batch experiments performed to evaluate equilibrium and kinetics phosphate adsorption on biochars surface. Then, experimental data of phosphate adsorption were analyzed using the kinetic (Pseudo First-order, Pseudo second-order, and intra-particle diffusion) and the adsorption isotherm (Langmuir, Freundlich) models. In addition, the effect of various initial phosphate concentrations (25– 500 mg L-1 ) and solution pH was investigated. The results indicated that the removal efficiency of sugarcane bagasse biochars was more than the date wood and increased with increasing of pyrolysis temperature. The sugarcane bagasse biochar produced at 550 ˚ C, had maximum phosphorus adsorption from aqueous solution (46. 94 mg g-1 ). Freundlich model showed the best fit for experimental data of phosphate adsorption onto biochar with R 2 =0. 96 and RMSE=0. 004. The results also revealed that Pseudo second-order kinetic model (R 2 = 0. 99) had the best fit for phosphate adsorption data. According to the results of this study, it can be concluded that the sugarcane bagasse biochar produced at 550 ˚ C has high efficiency for removal phosphate from aqueous solution.

Manure application and irrigation practice with wastewaters in olericulture may introduce antibiotics and antibiotic resistant bacteria to soil which may contaminate edible vegatables. The aim of this study was to investigate the antibiotic resistant bacteria isolated from radish (Raphanus sativu) and parsley (Petroselinum crispum L. ) and their cultivated soils. Three vegetable farms were selected in Pirbazar, Chaboksar and Fouman areas in Guilan province. Samples were taken from vegetables and soils at three replications. After making serial dilution, their heterotrophic and coliform bacteria number were determined on NA and EMB agar media respectively, containing 100 µ g/mL antibiotic. Four antibiotics including cephalexin, ciprofloxacin, gentamicin and trimethoprim were tested. Antibiotic resistant index (ARI) was calculated by dividing bacteria colony numbers on each antibiotic contained medium to control (medium without antibiotic). Data were analyzed as split-split plot design with three locations as main plot sector, two olericulture fields as sub-plot and four antibiotics as sub-sub plot factor. The effect of antibiotic was significant on the vegetable and soil bacteria ARI (p<0. 05). But the effect of sampling area and farm (radish and parsley farms) were significant only on the heterotrophic and coliform bacteria ARI, respectively (p <0. 01). In Chaboksar area, 29% of vegetable's heterotrophic bacteria and 42% of soil coliforms were resistant to gentamicin. The highest coliform ARI (38%) was obtained in radish and was to gentamicin. Overall, culturable bacteria from vegetables of Chaboksar area had higher antibiotic resistance index and eating fresh vegetables cultivated in this area is not recommended.

Construction of proper foundation for water structures such as canals increases their long life. One of the effective factors in this issue is soil strength condition. Chemical compounds of the soil affect its strength and change its bearing capacity. Sodium and Calcium are the most important cations in the soil and water resources. In recent years, because of its environmental compatibility and economic advantages, fine sand has been used widely as an additive amendment for soil remediation. In this research, the effect of calcium chloride and sodium chloride as well as fine sand, as additive material, on the strength characteristics of clay soil have been investigated. In this regard, the additive materials (salt and sand) were added to the clay soil at four different levels (0, 5, 10, 20 and 0, 5, 10, 15 percent of the soil dry weight, respectively) and specimens were provided by static compaction method. The specimens were subjected to an unconfined compressive strength test after two curing times of 7 and 28 days. The results showed increasing sodium chloride decreases the strength characteristics of the soil and adding fine sand does not have any significant effect on this trend. Also, adding 5 percent sand and calcium chloride to the clay soil caused to obtain maximum unconfined compressive strength and elasticity module of it. On the base of the results, adding calcium chloride improve soil strength relatively but not as much as other common additives, such as lime. Moreover, for increasing the strength of soils with large amounts of sodium chloride, soil leaching is suggested as a proper solution before foundation construction of the structures.

The catchment is a temporal-spatial dynamic hydrologic system; therefore, the process of rainfall-runoff is complicated. The hydrological models with their potentials are efficient tools to estimate runoff, especially under the conditions of climate change. The purpose of this study is to estimate runoff of Gorganroud Basin, located in the Aq Qala region, using the IHACRES semi-distributive model. For this purpose, the data of Gorgan Synoptic and Aq Qala Hydrometry Stations, four models; CanESM2, GFDL-CM3, HadGEM2, and MRI-CGCM3 from the CMIP5 models were applied under the SDSM and MarkSimGCM Statistical Downscaling methods. High-resolution CHIRPS precipitation data (0. 05 × 0. 05 arc degree) were also used. The statistical indices of R 2, MBE, and RMSE were used for validation and non-parametric Mann-Kendall and Sen's Slope tests were used to evaluate the trend and slope trend of the data process. The results showed that the CanESM2 model downscaled with SDSM has a higher performance than the other models. CHIRPS data has also shown a good performance for rainfall studies. The long-term statistical behavior of discharge in Aq Qala showed that April and May have the maximum discharges among the other months. Although IHACRES model did not show an appropriate performance for prediction of maximum discharges, but in general, it's performance is acceptable. The rainfall-runoff trend during the proposed future period under the RCP2. 6 and RCP4. 5 scenarios will be reduced, whereas, it will be increased under the RCP8. 5 scenario. Expected flood events in the region are also expected to show an increment trend with respect to the rainfall increment.

In recent years by growing technology, new methods have been substantially developed to solve nonlinear problems such as river flow forecasting. Among the available various methods, Support Vector Machine (SVM) and Adaptive Neuro-Fuzzy Inference System (ANFIS) models have been recently used by many researchers. In this study, these methods were used to predict the monthly flow of NazluChai and Sezar Rivers during 19562016 period. Firstly, the data were prepared in two modes: (a) using flow data and considering the role of memory; (b) influencing the periodic term. Modeling was done by 80% of the data (576 months) for training and the remaining 20% (144 months) for testing. The root mean square error (RMSE), Nash-Sutcliffe (NS) and mean absolute relative error (MARE) metrics were used to evaluate the performance of the proposed models. The results showed that the SVM method with the RBF kernel function had the best performance in predicting monthly flow of the studied rivers. In addition, the periodic term significantly increased the prediction accuracy of the SVM-RBF model. Also, the performance of the ANFIS method was improved by using the periodic term and this model had the least error in estimating the monthly flow of the Saesar and Nazlu chi Rivers in M6 and M7 patterns, respectively. In general, the results of this study showed that the SVM method performs better than the ANFIS model in monthly flow prediction and the selection of appropriate kernel function has a direct effect on its efficiency.

The complexity of the concept of soil water availability has led to the emergence of a variety of methods to estimate it, which have always been changing, refining, and replacing. Among those, the conventional method of plant available water (CPAW=FC-PWP) due to convenient measurement has received more attention. In theory, however, the methods of Integral Energy (EI) and Kirchhoff Potential (Mh0) have been considered due to the interference of soil properties and plant ability for water uptake. In this study, the available water was calculated with CPAW, EI and Mh0 concepts in a wide range of soils (72 samples) with various physical properties and results were compared. Also, different upper limits were tested to determine the water availability and the new field capacity moisture coefficient was used as the upper limit of the concept of water availability. Despite the weak correlation between EI and Mh0, the trend of their variations in different soils is somewhat similar, indicating their similarity in the estimation of available water for plants. In contrast, the lack of a clear relationship between EI and Mh0 with CPAW confirmed their lack of correlation in explaining water availability of the plant. The convenience of using CPAW makes it even more preferable to study the variability of soils in terms of hydraulic properties. On the other hand, the use of EI and Mh0 results will be useful for explaining the available water content but still needs to be modified in terms of determining threshold limits.

In this research, the spatial distribution of evapotranspiration and its relationship with remote sensing in contrast with lysimetric data as control was investigated in Arak, Markazi province in Iran. For estimation of actual evapotranspiration amount in the region based on SEBAL, SSEB and TSEB algorithms, 28 imageries of MODIS and Landsat7 (ETM+) were used for the years of 2000-2004. The multiplicity of MODIS images and its high temporal resolution is the reason of least error for ET estimation. According to the statistical results, the SEBAL model with the lowest RMSE in both TERRA and ETM + sensors (0. 97 and 1. 38 mm/day) was presented as the superior model in the region. Also, TSEB model showed the weakest results among the proposed models, in both MODIS and ETM + sensors (3. 57 And 2. 53 mm per day). Comparing the performance of two sensors, the ETM+ satellite images are recommended for ET estimation due to increased spatial resolution and improved resolution of images in the Landsat satellite. In addition, the NDVI vegetation index was at its lowest level at the beginning of the growing period due to germination and vegetation thinness, and it is increased by increasing air temperature and vegetation cover. L factor has a significant effect on SAVI and ET estimation and it is depended on the region vegetation. In this study, the L factor for the studied area was estimated to be 0. 6 during the maximum growth period, which had the least amount of error in comparison with other values.

Pollutants are usually drained off imperceptibly and suddenly in the rivers, which can be of human or natural origin, thus finding information from contaminant source as quickly as possible is important to reduce damage. The pollutant is released by the Advection-Dispersion processes in the river. Therefore, information on contaminant release site and release time can be obtained using inverse solution of the Advection-Dispersion equation. The purpose of this study is to solve Advection-Dispersion Equation (ADE) reversely and to obtain information on the release time and time series data of pollutant concentration discharged into the studied rivers. In this research, the quasi-reversibility method is used to reverse the ADE. In this method, by adding the stability term (fourth derivative term) to ADE, the mentioned relationship can be solved reversely without the instability of the answers. A hypothetical example and a case study of Karun River have been used for model validation. The aforementioned method determines the concentration experienced at different points and intervals of the river by reversing the ADE. The highest contaminant intake in each interval, maximum and average intake time are the obtained results by this method. The results show that the quasi-reversibility method has been performed with high accuracy and the proposed method has been satisfied in stability of solving ADE.

The objective of this research is to compare the performance of linear time series models of Box-Jenkins and IHACRES, multilayer perceptron ANN and hybrid ARMA-ANN in order to simulate and predict the daily discharge of Maroun River. For this purpose, daily discharge data of (1991-2006) were used for calibration and data of (2007-2017) were used for verification of the models. Schwartz (SBC) and Akaike information criterion (AIC) were used to select the best model. Different scenarios, learning algorithms and transfer functions with various neuron structures were used to develop the ANN model. The first scenario with less parameters and delay time was selected as the best ANN model in prediction of daily flow rate. Evaluation indices showed that the conceptual model performance in verification stage was better than that in calibration stage. Also, the 4 th order moving average model with R 2 =0. 61 had the weakest performance as compared to the other Box-Jenkins models. Evaluation indices indicating a relative promotion for ARMA-ANN hybrid model as compared to the other proposed models. As, ARMA-ANN hybrid model obtained the highest R 2 =0. 86 and Nash-Satcliffe coefficient equal to 0. 81. The results prove the ability of ARMA-ANN hybrid model for simulation and prediction of daily discharge, as compared with other models.

The main challenge in determining drainage depth in arid and semi-arid regions is the inefficiency of shallow drainage in salinity control and producing more drainage water by deep drains which is also more saline and more polluted. In the irrigation season, the focus of drainage is mainly on soil aeration, and the depth of the drainage design should keep the groundwater level in a position that avoids damages caused by waterlogging. During the non-irrigation period, the minimum depth required for drainage should be such as to prevent salinity increase through the capillary flow. Controlled drainage is the best way to overcome the conflict of salinity control and less damage to the environment. However, necessary equipment and structures for these systems are costly, as well as operational and maintenance problems, have led to a lack of expansion of such systems in developing countries. The simplest and cheapest solution to the problem is to plow the soil or any other tillage operation that will cut off the capillaries. But post-harvest plowing exposes soil organic matter to sunlight that is rapidly oxidized, which will have a negative impact on soil fertility. Another suggested solution is a bilevel drainage system. In such a system, the task of controlling the water level in the irrigation season is mostly the responsibility of shallow drains. In the non-irrigation season, the water level drops to deeper drain levels and the potential for re-salinization by capillary up-flow will be reduced.

In the modern world, it is necessary to have a sustainable agricultural system in which natural resources are utilized and at the same time does make any harmful to the environment. Nitrogen leaching is one of the most important problems in intensive farming for high crop production. Application of organic matter lead to reduce chemical inputs and achieve sustainable agricultural goals. Application of modified materials such as biochar and hydrochar can play an important role in creating optimal conditions for growth, increasing plant yield and reducing water consumption, as well as reducing nitrate leaching. In the present study, the effect of biochar and hydrochar, derived from sugar cane bagasse, on crop yield, water productivity and nitrogen leaching in maize cultivation under two irrigation levels of full and dificit (up to 30%) and two fertilization levels of 200 and 160 kg/ha of nitrogen for each sources of urea, biochar and hydrochar were investigated. Adding biochar and hydrochar to the soil increased the yield and water productivity and reduced drainage outflow and nitrogen leaching. In contrast to hydrochar, biochar has a more effective role for the above mentioned parameters due to its high porosity and specific surface area. In comparison with urea application, using biochar and hydrochar at the optimum moisture conditions reduced drainage outflow 9. 2 and 3. 1% and nitrogen leaching 2. 6 and 3. 4%, respectively. Therefore, the use of biochar and hydrochar could be considered as an effective solution to reduce the negative effects of agriculture.

Achieving satellite images with high simultaneously spatial-temporal resolution has been one of the serious challenges faced by researchers in the field of remote sensing and its applications. In recent years, researchers have made serious efforts to solve the problem. In this study, producing Landsat like land surface temperature images with less than 16 day temporal resolution and over different land covers, using spatio-temporal image fusion algorithm (STI-FM) and MODIS Land surface temperature images, was investigated. The STI-FM technique consist of two main steps. First establishing a linear relationship between two consecutive MODIS LST images acquired at time 1 and time 2; then utilizing the above mentioned relationship as a function of a Landsat-8 LST image acquired at time 1 in order to predict a synthetic Landsat-8 LST image at time 2. The results showed strong linear relationship between the two consecutive MODIS images at times 1 and 2 (R2 in the range 0. 85-0. 95). The synthetic LST images were evaluated qualitatively and quantitatively and it was found that there is a high visual and strong agreements with the actual Landsat-8 LST images over different land covers. For example R2 and RMSE values were ranged 0. 74-0. 94 and 1. 44-2. 52, respectively.

Soil moisture is a determining parameter in many complex environmental processes and plays a decisive role in the occurrence of agricultural drought. For this purpose, in this study, using soil moisture data estimated by DSSAT model and Fifth Climate Change Report data, agricultural drought was determined by soil moisture deficiency index for future periods of (2015-2045) and (2045-2075) and they were compared with baseline period (1975-2005). The climatic data were estimated using GCM models and two emission scenarios RCP4. 5 and RCP8. 5 and they were scaled using LARS-WG model and entered into DSSAT model. Finally, using soil moisture data of 30 and 60 cm depths, agricultural drought was evaluated using SMDI index. Climate change results showed that the minimum and maximum temperature and precipitation will increase in the next period compared to the baseline period, and the RCP8. 5 scenario estimated a higher temperature and lower precipitation than the RCP4. 5 scenario. Weekly soil moisture decreased for future periods compared to the baseline and soil moisture values in RCP4. 5 scenario were higher than the ones in RCP8. 5 scenario. Also, weekly soil moisture changes at different irrigation levels in the base period are less than those in the future. Estimated values of SMDI drought index by RCP4. 5 scenario at 0-30 depth in period of 2015-2045 are more negative and drought than the ones in future period 2045-2075; while the future period of 2045-2015 in RCP8. 5 scenario has a better situation. The SMDI drought indices of 30-60 cm depth in both scenarios for the upcoming 2015-2045 period show lower values than the ones in 2045-2075 future period. The RCP4. 5 scenario estimates a higher SMDI drought index than the RCP8. 5 scenario.

Drought, salinity and essential plant nutrient stresses especially phosphorus (P) are the most important challenges for wheat production in dryland farming of Iran. The objective of this study was to investigate the effect of three plant growth promoting bacteria strains on soil available-P, as well as some of the physiological and growth traits of wheat under water-deficit stress. For this purpose, a pot experiment was carried out as factorial arrangement with three factors including: water deficit stress at two levels, application of P-fertilizer at six levels and strains of plant growth promoting bacteria at four levels, based on completely randomized design (CRD) with three replications within 125 days. The results show at the water deficit stress of 55% field capacity (FC) and without P-fertilizer application, bacterial treatment of Staphylococcus succinus compared to control increased available-P, P-uptake of root and grain by 2. 4, 4. 9 and 2. 7 times respectively. At moisture treatment of 80% FC and without P-fertilizer application, treatments of Bacillus pumilus, B. safensis and S. succinus compared to control, increased available-P by 1. 6, 1. 6 and 1. 6 times; P-uptake of root by 3. 1, 3. 1 and 2. 9 times; P-uptake of grain by 2. 2, 2. 4 and 2. 2 times, respectively. Maximum dry weight of root, shoot and grain (5. 3, 18. 2 and 4. 6 g pot-1, respectively) were obtained at the maximum level of P-fertilizer treatment (F4). At the water deficit stress of 55% FC, bacterial treatment of S. succinus compared to control increased prolin, root dry weight, grain dry weight and P-uptake of shoot up to 8, 31. 9, 20. 4 and 25. 5 percent, respectively. Generally, the use of Staphylococcus succinus strain R12N2 seems to be appropriate for increasing wheat production in dryland farming.