تیمور سهرابی

Surface irrigation systems have been widely used in different regions worldwide, particularly in arid and semi-arid areas. However, inadequate management has resulted in significant water losses in the agricultural sector. Utilizing plastic and organic mulches in furrow irrigation systems reduces water loss and increases irrigation efficiency. The main purpose of this study is to investigate the effect of the type of mulch and the location of the plastic mulch in furrow irrigation on the hydraulic parameters of the surface flow, such as advance time, recession, runoff, and infiltrated water volume. Field experiments were conducted in 2021 in Karaj, Iran. In general, five treatments were considered: three treatments with plastic mulch, including mulch on the ridge (R), mulch on the bottom of the furrow (F), and mulch on the ridge and bottom of the furrow (FR), and one treatment with organic mulch of wheat straw (OM) and a treatment without mulch or control (C). Considering the same irrigation management and inflow rate, it was observed that using mulch would increase water losses due to maintaining the soil moisture and reducing the wet perimeter. The highest amounts of runoff and the fastest advance time were produced for the FR, F, OM, R, and C treatments, respectively. Conversely, the order was reversed for the volume of infiltrated water. When mulch is used, it is essential to make fundamental changes in irrigation management. This may involve adjusting the inflow rate, cut-off time, field length, or a combination of these methods. It is also suggested that deficit irrigation could be utilized in future experiments.

In many fields of water sciences, the moisture movement in the soil profile is very important. Due to the non-linearity of the governing equation in moisture movement in the soil profile, the comprehensive analytical solution of this equation is impossible, and there is a need to solve it numerically. The abundance of data and simulation steps reduces the flexibility in using existing software to solve the Richards equation and using this data as initial conditions. Therefore, having a numerical solution plan for the Richards equation will be very useful. Among the existing methods, the fully implicit finite difference method can continue the simulation unceasingly due to its unconditional stability in providing a non-iteration solution. However, using the finite difference method to solve the Richards equation leads to significant mass balance error. Some usual methods to reduce the mass balance error could not be applied to the non-reverse solution. By creating the Richards equation numerical solution in MATLAB software, this research introduces a method to reduce mass balance error, which is a simple method to apply to all kinds of numerical solutions.

In this research, a Non-Iteration implicit solution for the Richards equation was developed. After creating the Richards equation numerical solution, the difference between the entering flux to the soil column and the added water to the same soil column, is added to each node to reduce the mass balance error. This amount is added to the nodes that their matrix pressure head difference (PD) compared to the initial state, is more than a threshold value. This amount applies as a coefficient proportional to the humidity of each node. To investigate the effect of various factors on the performance of the created numerical solution, a series of 11 experiments were designed with different characteristics in terms of infiltration rate, infiltration duration, duration of moisture redistribution in the soil profile, and initial volumetric water content. The optimal value for PD in each experiment was determined in such a way as to minimize the mass balance error. For the integrity of the results, the average PD values equal to 10 cm were used to simulate all cases. These series of experiments were simulated by two-dimensional HYDRUS software, and the results were used to verification of the created numerical solution.

The results showed that the most mass balance error is forced in the infiltration phase. Using the proposed method to preserve the mass balance caused a significant reduction in the mass balance error. The absolute value of the mass balance error varied in a narrow range and was always less than 3.5 percent. It is expected that time and space steps have a considerable effect on the mass balance error. The absolute mass balance error decreased linearly from 3.36 to 3.33, with the infiltration duration increasing from 10 to 30 minutes at a constant infiltration rate of 1 mm 〖min〗^(-1). The absolute mass balance error increased linearly from 3.36 to 3.37% by the initial volumetric water content increasing from 13 to 17% and decreased from 3.40 to 3.35 percent by the increase in the duration of the moisture redistribution in the soil profile from 300 to 900 minutes. Also, the Mean Absolute Relative error (MAE) increased from 1.17 to 9.53% by the infiltration time increasing from 10 to 30 minutes; the MAE increased from 1.17 to 8.89% by the infiltration rate increasing from 1 to 3 mm 〖min〗^(-1); and the MAE increased from 1.17 to 6.89% by the volumetric water content increasing from 13 to 17%.

The results showed that this method leads off the simulation to a significant reduction in the mass balance error; so that, in all experiment cases, the mass balance error ever fluctuated in a small range, less than 3.5%. The results comparison of the created simulation and the HYDRUS software showed that this method provided acceptable results, in cases such as summer rains where the infiltration duration is much less than the water redistribution time in the soil profile. Also, the highest value of the MAE in comparing the created simulations with the obtained results from the HYDRUS software is less than 10%. It proves a good agreement between the created simulation and the HYDRUS software.

In-Site water harvesting is just one of the rainwater harvesting techniques with a wide range of traditional and innovative methods. Its efficiency can be improved by applying proper management and mechanization. By following the traditional architecture of Iran and modifying the existing rainwater harvesting methods, designed an In-Site water harvesting system for planting or groundwater feeding, called the Kajaveh, as a matrix of inverted cones. In order to study the influential factors on the Kajaveh system, 13 different treatments were examined. The results indicate that there is a specific base diameter and cone height which were determined according to the climatic and geographical conditions of the region and lead to the optimal operation of the Kajaveh system in water harvesting. Considering the different initial conditions for these treatments, results indicated that the case with a wall slope of 0.3 m/m, cone base diameter of 50 cm, loam soil, rainfall intensity of 12 cm/h, and rainfall length of 10 min, to yield the best rainwater harvesting results and on the average provided 14.9% more water than the unstructured state in the target area.

The Hargreaves-Samani method of estimating reference evapotranspiration (ETo) has been recommended by irrigation and drainage paper No.56 of the Food and Agricultural Organization of the United Nations (FAO)  in the situations that weather data are missing. since the method requires just measured temperature, the it has been used in several studies over the past decades. FAO paper No. 56 and other investigations has mentioned that Hargreaves-Samani method is an overestimating method in humid cliamtes. Hence, the method has been calibrated for different site and situations. This issue made the purpose of the current study. In this study, the history of the development of Hargreaves-Samani method has been reviewed. Thus, an equation for adjusting humidity condition is discussed. To compare the goodness of models,  ETo was calculated based on 3 different methods 1) Hargreaves-Samani method 2) Allen modified method of Hargreaves-Samani, and 3) the modified method of Hargreaves-Samani based on relative humidity. Also ETo was calculated according to FAO Penman-Montith method as a control estimation. The values were calculated for monthly weather reports of 4,169 stations from CLIMWAT v2.0 all around the world. The results showed that the Hargreaves-Samani’s method has a weakness of estimation under extreme conditions. Interestingly, the corrected method improved precision of the estimations especially in arid and semi-arid locations.

Climate change is an undeniable phenomenon, which affects virtually every aspect of life on Earth. The agricultural sector is heavily connected to the environment and thus, gets affect by climate change the most. Climate change affects agriculture by affecting temperature and rainfall. The elevated air temperature increases the potential evapotranspiration. Variation in precipitation is generally unfavorable. Increase in precipitation causes waterlogging and subsequently erosion in soil, while decreased precipitation causes water stress in crops. It is necessary to assess the climate change impact on agriculture in order to change policies accordingly. This paper sought to assess the impact of climate change on sugar beet net irrigation water requirement and potential yield. In this research, the climatic information of the meteorological station located in Mohammadshahr, Karaj for the period 1970-2014 and the crop parameter of the sugar beet research farm located in Mehrshahr, Karaj were used. Future climatic data from six global climate models, namely ACCESS-ESM1-5, CanESM5, EC-EARTH3, IPSL-CM6A-LR, MRI-ESM2-0 and NorESM2-LM, under three optimistic, intermediate and pessimistic scenarios (SSP126, SSP245 and SSP585) for the period 2015-2100 were downscaled for Karaj using empirical quantile mapping method. Taylor diagram was used to evaluate the downscaling results. Temperature and precipitation data as well as reference evapotranspiration, which was calculated by Hargreaves-Samani method, were given to AquaCrop model. The effective rainfall calculation approach was set to USDA-SCS method in AquaCrop model. The trend and fluctuations of the climatic and crop variables were examined using the Mann-Kendall and Pettitt tests, respectively.The results indicate that the sugar beet sowing and harvest dates advance by 39 and 71 days, respectively, which means a decrease of 29 days in the growing season length (from 171 to 142 days). The reference evapotranspiration under SSP585 will increase by 14.8% (6.5% under SSP126) at the end of the 21st century in Karaj. The water requirement can increase up to 7.8% under SSP585 (3.7% under SSP126). The amount of irrigation water requirement in the future period will increase up to 10.5% under SSP585 (5.8% under SSP126). The biomass and yield variations at the 21st century ending period will be 11.8% and 19.2% increase under SSP585 (4.2% and 5.9% increase under SSP126), respectively. All the climatic and crop variables showed strongly significant trend in the study period (1995-2100) under the pessimistic scenario, while the fluctuations of the variables were not as significant as their corresponding trends under the same scenario.According to the results of this paper, the increasing temperature caused by the elevating atmospheric CO2 concentration, under the pessimistic scenario, increases the sugar beet net irrigation water requirement by increasing the crop evapotranspiration. The decreasing precipitation also contributes to the obtained result. The potential yield showed a contradicting result, i.e., the elevated CO2 under the pessimistic scenario favors the yield production due to the fact that more CO2 contributes to more efficient photosynthesis. The results can be used in climate change adaptation policies regarding water allocation and optimal planting date determination for sugar beet cultivation in Karaj.

One of the important factors for agricultural irrigation management and planning is accurate estimation of reference evapotranspiration (ETo). The application of the standard model (FAO-Penman-Monteith) to estimate ETo is restricted due to the availability of climatic variables including temperature, humidity, radiation, wind speed as well as the availability of the mentioned hypotheses in FAO 56. Accessibility to all climatic parameters or satisfaction of the FAO-Penman-Monteith assumptions are often not possible in some areas or in controlled environments (greenhouses). Therefore, it is preferable to use methods that can provide an accurate estimate of ETo with fewer input parameters. The aim of the present study was to evaluate the performance of two methods of artificial neural networks (ANNs) and adaptive neuro-fuzzy inference system (ANFIS) for estimating ETo in the research greenhouse of the College of Agriculture and Natural Resources of the University of Tehran, located in Karaj, Iran. Based on the measured climatic parameters inside the greenhouse, different combinations were created and evaluation indicators were calculated for each method and scenario. The best neural network structure was obtained for Scenario 4 (radiation, temperature, humidity) with 7 neurons in the hidden layer and Bayesian Regularization training algorithm. ANFIS model was designed with different membership functions. The results showed that there was no significant difference between the performance of the ANFIS method under different scenarios. In other words, even with temperature and humidity data, ETo can be simulated with high accuracy by ANFIS method. Comparison of evaluation indicators between ANFIS and ANNs models showed that ANFIS performed better than ANNs method. The calculated relative root mean square error (RRMSE) for scenarios 1 to 4 in ANNs model was equal to 12.70, 2.23, 2.12 and 2.10% however it was equal to 1.41, 0.80, 1.06 and 1.01% in ANFIS model.

The purpose of soil management is maximizing the supply of water and nutrients to the plant and minimizes the soil erosion, improve soil fertility and soil physical conditions. Using in-site water harvesting methods reduces runoff from the area and increases the water stored in the soil profile. Rainwater harvesting is not a new concept, but it requires the combination of native methods with modern knowledge. Because the used technology was inappropriate for special conditions of the region, some water harvesting projects have been unsuccessful or even led to the loss of the whole crop. The suitability of an area for rain water harvesting depends on its ability to supply the technical and basic needs of the system. This study introduces a method for rain water harvesting in the area with little slope or no slope, which can be Mechanized Construction for large-scale. On the other hand, a computer simulation has been preparation and introduced for precise and scientific designing of a water harvesting system, which there has not been much effort in this case. The results of simulation indicated the reduction of concentration ability of water by Kajaweh system with decreasing the size of structure. In addition, in relatively smaller sized structures under high intensity rainfall, reduction of water concentration ability by Kajaweh system was predicted by simulation. Such trend is also expected for long time rainfall times (especially in low rainfall intensity).

The main objective of this study was to optimize the environmental conditions for maximum growth of Dunaliella salina algae. In this study, effective environmental parameters in algae growth, such as temperature in two levels of 18± °C and 28±2 °C, pH in three levels of 7.0, 7.5, and 8.0 and salinity seven levels of 0.5, 1.0, 1.5, 2.0, 2.5, 3, and 4 molar NaCl in a 30-day culture period were investigated. The dark: light cycle and the constant light intensity were considered 24:0 and 130 130 molPAR. m-2.s-1, respectively. Results depicted that an increase in temperature affecting specific growth rate and a decrease in cell’s population doubling time. The highest specific growth rate and the shortest cell’s doubling time were observed under the condition of pH = 7. Furthermore, the highest specific growth rate was obtained in the salinity of 1.5 molar (0.59 per day) while the lowest specific growth rate in the salinity of 4molar (0.04 per day). The shortest (approximately 1.5 day) and longest (from 10 to 19 days) cell’s doubling time were recorded in salinities of 1.5 and 4molar, respectively, such that by increasing salinity from 0.5 to 1.5 molar, doubling time decreased while by increasing salinity from 1.5 to 4 molar, the doubling time showed a decrease trend. The algae cell concentration increased by an increase in temperature. There were significant differences among cell concentrations in various pH levels. pHs higher and lower than 7.5 led to a decrease in cell concentration. Therefore, in most samples, the maximum cell concentration was observed at pH of 7.5. An increase in temperature when pH was 7.5 let cell concentration to reach its maximum amount faster. By increasing salinity from 0.5 to 1.5 molar, cell concentration increased. In comparison, an adverse effect was observed when salinity increased from 2 to 4 molar. Cell concentration in 1.5 molar salinity condition ranged from  to  and in 4 molar salinity, cell concentration varied from  to . Based on the results of this study, the optimum environmental condition for growth of Dunaliella salina recorded under the salinity = 1.5 molar, temperature = 28±2 °C, and pH = 7.5. Condition of 1and 2 molar salinities with the aforementioned temperature and pH, is suggested as the further option for production of this algae.

One of the most important factors in calculation of greenhouse crop water requirement is the accurate estimation of reference crop evapotranspiration. Numerous parameters affect the evapotranspiration rate of the reference crop; with the knowledge of the most important factor the simulation error will be reduced. Because of the differences among mathematical structure and underlying assumption of indirect reference crop evapotranspiration estimation methods, behavior of the response variable to changes in climatic parameters may become inconsistent. Therefore, it is mandatory to analyze the sensitivity as well as determining the influence of meteorological factors on reference crop evapotranspiration. In this study, the sensitivity of Penman-Monteith, Irmak, Copais and Valiantzas methods to changes in meteorological factors including maximum and minimum daily temperature, maximum and minimum relative humidity and short-wave radiation was analyzed in the research greenhouse of the College of Agriculture and Natural Resources of the University of Tehran, located in Karaj, Iran. Sensitivity coefficients were calculated by changing meteorological factors in the range of [20, -20] percent with 5% intervals. Results showed that in all methods, the internal radiation was the most influential variable in determining the reference crop evapotranspiration under greenhouse conditions. The obtained sensitivity coefficient for this variable in Penman-Monteith, Irmak, Copais and Valiantzas methods was equal to 0.78, 0.71, 0.68 and 0.63, respectively. In contrast, the least important climatic variable was the minimum humidity in Penman-Monteith, Copais and Valiantzas methods and the minimum temperature in Irmak method. The results also showed that Penman-Monteith is the most sensitive method to changes in meteorological factors. As a result, in case of using of Penman-Monteith method for reference crop evapotranspiration estimation in greenhouse conditions, ensuring the correct operation of measuring instruments and their accuracy is essential.

The use of modern irrigation methods, deficit irrigation, the use of cultivars more resistant to drought stress, are ways to increase water use efficiency in agriculture. To study the effect irrigation level and type of maize cultivar on water use efficiency in forage and grain maize production, this research was conducted at the research farm of Agricultural and Natural Resources College of University of Tehran (Karaj) in 2017. The main treatments included two levels of irrigation (100 and 80% of maize water requirement) in subsurface drip irrigation system; sub-treatments included three maize cultivars KSC704, KSC600, KSC400. Experimental design was based on split plots based on randomized complete blocks. The studied traits were forage yield, biomass, grain, water use efficiency in forage, biomass and grain production, 1000-grain weight and harvest index. The results showed that the effect of irrigation level on the measured traits was insignificant and the effect of cultivar on them was significant at both irrigation levels. The highest amount of water use efficiency in biomass production was 4.37 kg / m3 in KSC600 cultivar and the highest water use efficiency in grain production was 2.43 kg / m3 in KSC704 cultivar (with KSC400 cultivar in a Statistical group) obtained at the irrigation level of 80%. Also, KSC400 cultivar, being in the common statistical group with KSC704 cultivar, had the highest 1000-grain weight of 537.3 grams. Deficit irrigation up to 80% of water requirement using subsurface irrigation system had not any significant effect on the yield of maize cultivars.

 In recent years, to increase the efficiency of surface irrigation methods, new techniques such as surge irrigation have been developed. Numerous studies have shown that the surge flow can reduce water consumption in the advance phase and subsequently improve irrigation efficiency and water distribution uniformity. One of the factors affecting the performance of surface irrigation systems is the accurate estimation of infiltration. Due to continuous changes in the infiltration process during on-off cycles in surge irrigation, determining the empirical equation of infiltration in surge irrigation method is complex and requires time-consuming and costly field data. As a result, proper selection and parameterization of empirical equations with a simplified procedure are needed. The goal of this research was the field evaluation of the point method (surge infiltrometer) to simulate the infiltration process in advance phase surges.      A field experiment was conducted at the experimental station of the College of Agriculture and Natural Resources, University of Tehran, Karaj, Iran. A ring infiltrometer was modified by connecting a pipe arm for inward and outward water flow to the ring and from the ring to the pipe to create on-off surge cycles, respectively. Water entered the ring through the inlet hole at the top of the pipe arm and water depth was recorded at different time intervals during the on-time of each cycle. Four treatments were performed for infiltration tests under surge flow, including different cycle time and ratio. Also, infiltration tests were performed under continuous flow conditions. To simulate the first (dry soil) and second irrigation conditions, infiltration experiments were conducted twice on an 8-day interval. The Kostiakov infiltration equation was corrected by applying surge factors to predict infiltration water depth for subsequent surges, using first surge data. The empirical coefficients of the Kostiakov equation were calculated by applying the two-point technique.   Results of the study revealed that the infiltration data simulated by the developed Kostiakov equation matched closely with those collected from the surge-ring infiltrometer. The coefficient of determination and the root mean square error were calculated to be 0.92 to 0.97 and 0.03 to 0.16 cm, respectively. In general, the amount of cumulative infiltration in the second and subsequent surges decreased. The ratio of the infiltration depth at the end of the second to the first surge was less than 0.5. In all experiments, the depth of water infiltrated in the third surge was significantly reduced and almost reached to the final infiltration rate. As the cycle ratio increased, the cumulative infiltration also increased. However, the effect of on-off time on the infiltrated water depth in the first experiment was greater than that in the second experiment. It was concluded that in the first experiments, the surging phenomena substantially reduced water movement and the reduction in cumulative infiltration ranged from 50 to 70% during the second surge and from 59 to 85% during the third surge. The above values were determined 52 to 76% and 61 to 88% for the second experiment, respectively. A significant difference was observed between surge and continuous flow tests. The surge flow led to a 46 to 76% reduction in the cumulative infiltration depth compared to the continuous flow. The effect of surge flow was greater in the first experiments.  One of the most important points in designing surface irrigation systems is to determine the infiltration equation parameters. In particular, the difficulty involved in the planning and design of surge irrigation systems is the prior knowledge and understanding of how infiltration changes occur during surging. The main objective of the present study was to evaluate the surge ring infiltrometer test to predict the infiltration in the second and third surges using the first surge data. The results obtained from the surge infiltrometer experiments showed that the use of surge irrigation has the potential to reduce infiltration. The observed and predicted cumulative infiltration for the second and third surges showed a good agreement. The surge-ring infiltrometer has the potential for creating an on-off mechanism and is best suited to determine the cumulative infiltration from surges for constant on-off time surge intervals.

In areas where annual rainfall is less than the crop water requirement, providing water for plant is necessary to grow properly without stress. One of the methods that have least damaging to the environment is rainwater harvesting techniques. The Kajaveh system is a local rainwater harvesting system that can be used in very low-slope areas and can be used in a mechanistic manner for annual crops. In order to investigate the operation of the rainwater harvesting system, computer simulations were performed. Estimating rain infiltration on sloping surfaces is the main part of this simulation. In this research, a semi conceptual- experimental method was used to estimate the infiltration of rainfall on sloping surfaces and find a structure with suitable geometric dimensions to rainwater harvesting. The results of the simulation that was prepared using this method were compared with the experimental data and after calibrating the simulation, it was used to study structures with different wall slopes. The results indicate that there is an optimal slope in which the maximum ability of the Kajaveh system to water concentrate occurs. For the soil whit Sand-Loam type, Aggregate structure, precipitation intensity of 11.49 cm per hour, rainfall duration of 10 minutes and in the conditions of structure formation in this research, a square base structure with 50 cm length and cavity depth of 10 cm (wall slope of about 22 degrees) showed the highest efficiency in water concentrating.

Nitrogen is one of the most widely used nutrients for crop development. Application of nitrogen fertilizers plays a crucial role in increasing agricultural yield and production. In order to achieve maximum crop yield and reduce the negative environmental effects, application of nitrogen fertilizers should be based on the dynamics between nitrogen supply and crop demand. In order to manage the consumption of nitrogen fertilizers, it is necessary to accurately predict the crop nitrogen requirements at different growth stages. In present study, the concept of critical nitrogen concentration (Nc) has been used as an effective approach to determine nitrogen status and estimate nitrogen requirement of basil. For this purpose, basil was cultivated in the research greenhouse of the College of Agriculture and Natural Resources, University of Tehran, Karaj, Iran. Different nitrogen fertilizer treatments were applied at seven levels with three replications. Crop dry matter and nitrogen concentrations were measured seven times during the growth period. Then nitrogen nutrition index (NNI) and basil nitrogen requirement (NR) were calculated for the first experiment. Results showed that, there was a significant regression relationship between basil NNI and NR (R2> 0.96). Accordingly, the NR prediction model was developed using NNI values and day after planting (DAP). Then, accuracy and performance of the NR-NNI relationship were verified by the second experiment data. The values ​​obtained for RMSE, NMB and NRMSE statistical indicators were less than 1 kg / ha, 0.10% and 3.10%, respectively, which indicates high accuracy of the model for prediction of crop nitrogen requirement. In general, results showed that estimation of crop NR based on the concept of Nc could be used as a scientific and suitable approach for managing nitrogen application in agricultural production.

Modern irrigation systems are one of the most important factors affecting crop production, water consumption and productivity, but the performance of these systems requires careful consideration. For this purpose, a study on the effect of surface and subsurface drip irrigation systems with different levels of deficit irrigation on yield, yield components, and water productivity in SC 704 maize, a factorial split design based on randomized complete block design was conducted in the field of Deputy of Soil and Water, Ministry of Agriculture (Karaj) in summer of 2018. The treatments were included %100, %75 and %50 of water requirement in each type of surface and subsurface drip irrigation. A total of 54 irrigation drips were tested. Based on the results, the interaction of stress and irrigation method for plant length was non-significant, and dry plant weight and harvest index were significant at 1% probability level and other traits at 5% probability level. The results also showed that the highest grain yield 22.33 ton/ha and 22.31 ton/ha, were obtained from DI=%100 IR and SDI=%100 IR treatments, respectively, which were not significantly different between these treatments. The lowest grain yield was obtained from DI=%50 IR treatment which had a 33% decrease in yield compared to non-stress treatment in surface drip irrigation. The SDI=%50 IR treatment had the highest irrigation water productivity (2.75 kg/m3) among the other treatments. The water productivity of this treatment increased by %53.6 compared to the non-stress treatment in subsurface irrigation.

Crop model parameters are influenced by different management and environmental conditions. Sensitivity analysis is recognized as an effective approach for identifying the most influential parameters in the modelling process and output uncertainty assessment. In present study, the sensitivity of AquaCrop model parameters for basil was evaluated under different nitrogen fertilizer stresses. For this purpose, an experiment was conducted in the research greenhouse of the College of Agriculture and Natural Resources, University of Tehran, Karaj, Iran. Crop growth parameters used for sensitivity analysis include normalized water productivity (Wp < sup>*), initial canopy cover (CC0), maximum transpiration coefficient (), canopy growth coefficient (CGC) and canopy decline coefficient (CDC) which analyzed by Beven (1979) approach. The results showed that the highest sensitivity of the AquaCrop model was due to the change in the Wp < sup>* parameter. Therefore, it is necessary to calibrate this parameter under different environmental conditions and for diverse crop species to increase the accuracy and performance of the model. Also, comparison of the sensitivity coefficients obtained for each of the growth parameters showed that by increasing nitrogen fertilizer stress, the model sensitivity also increased. But the growth rate was not the same among the selected parameters. In other words, the impressibility of parameters was different from nitrogen deficiency.

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 R2, 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 semi-quantitative method can be used as a suitable tool to simulate crop growth under soil fertility stress conditions.

The development of agricultural crop cultivation in greenhouse is one of the main strategies for managing water scarcity. Awareness of the crop water requirement and accurate estimation of crop coefficient is one of the most important component in irrigation scheduling and improving water use efficiency. The objective of this research was to determine water requirement and crop coefficient of basil in controlled greenhouse condition. For this purpose, a study was carried out in a research greenhouse of the College of Agriculture and Natural Resources, University of Tehran during a growth period using micro-lysimeter. Micro-lysimeters are useful tools for accurate determination of the crop evapotranspiration under standard conditions (ETc), or the actual crop evapotranspiration (ETa). In this study, the evapotranspiration of the reference crop and the Basil water requirement were estimated using the soil water balance equation. According to the results, average reference and basil crop evapotranspiration during the growth stage were equal to 8.23 and 5.13 mm per day, respectively. Then the crop coefficient was calculated based on the ratio of basil crop and reference evapotranspiration. The average basil crop coefficients for the initial, mid and end growth stages were obtained to be 0.30, 0.86 and 0.76, respectively.

In most countries, agricultural sector is the main user of water resources (surface and ground water). The process of exploitation of water resources to explain the sustainability and continuity of exploitation in each region, especially in arid and semi-arid areas, which is faced with the shortage and severe competition of water resources use in different sectors is necessary. The purpose of this study was to investigate the status of water resources in the Marvdasht-Kharameh range (covered by two modern irrigation networks in Dorodzan and traditional Korbal) in Fars province during the statistical period of 2006-2016, based on the stability analysis indexes proportional to the volume of water allocated in comparison with excessive withdrawal of groundwater resources, as well as the relationship between rainfall and the amount of variations in the level of stagnation. For this purpose, by using Dorodzan weather data and Persepolis stations, as well as Kheirabad, Pulkhan and Zarghamabad hydrometric stations and the irrigation networks data, the available water resources in terms of surface and groundwater were estimated. According to the average level of stagnation and changes in aquifer volume, excess water harvesting were calculated in two areas covered by Dorodzan and Korbal irrigation networks. The amount of runoff coefficient in plain, altitudes and total range was calculated to be 6.9, 14.1 and 9.9 percent, respectively. The average amount of excess withdraw in the area covered by two modern Dorodzan and Korbal networks is 96.33 and 16.2 MCM /year, which according to available water resources is 8.2% and 5.2%, respectively. The Average standardized precipitation-evaporation-transpiration12-month SPEI index for Droodzan and Persepolis stations was calculated to be -0.33 and -0.43, indicating the mild drought in the area and during the proposed time period, and this is in good agreement with the Water table drawdown. The result of linear regression between the independent variable of rainfall and the dependent variable of the average water table changes showed a significant increasing linear relationship (p < 0.001) with R2 = 0.95 and RMSE = 0.99. This result for the independent variable of rainfall with the dependent variable of water allocation volume, indicated an incremental linear relationship (P = 0.110), with R2 equal to 0.29 and RMSE equal to 245.6. Indicators of water resource sustainability analysis, such as Falcon Mark (FI), United Nation (UN) and Water Tension Index (WSI), were calculated for the region. The values of the Indicators of water resource sustainability analysis including Falcon Mark (FI), United Nation (UN) and Water Tension Index (WSI) were 1983 cubic meters per person, 210 percent and 2.93, respectively. By comparing the values of these indexes, it was found that based on the FI index, the area is close to tension. The UN and WSI indicators are indicative of the fact that the study area is under severe crisis and excessive use of water resources and the pattern of exploitation of water resources should be managed in order to eliminate surplus withdrawals and sustainability of water resources.

Irregular exploitation of water resources of the country, especially in the agricultural sector, has threatened Iran with serious threats. The main objective of this study is to provide of possible management strategies at farm level, without changing irrigation systems and additional costs in order to reduce agricultural water consumption such as improving irrigation water efficiency, changing the planting date and studying different levels of deficit irrigation with regarding the type of cultivation, the actual conditions of irrigation management (amount, number of irrigation, etc.) in different areas of the study area have been checked. The basics of the study are based on actual information and in the form of a case study. . The results showed that improvement of irrigation efficiency for dominant crops in two regions of Dorodzan and Korbal, leading to savings in water allocation of 131.5 (11.2%) and 33.8 (10.83%) million cubic meters, respectively. The results of the scenario of change in planting date using AquaCrop model simulation showed that with this management pattern could be saved, 31.6 (2.7%) and 9.17 (2.94%) million cubic meters in the two regions of Dorodzan and Korbal in water consumption respectively . At the same time, different levels of deficit irrigation can save 85.5(7.3%) and 26.2 (8.4%) million cubic meters in water consumption respectively.

Lack of oxygen and high salinity are factors that limit the biodegradation of the hydrocarbon. The electron accepters such as nitrate and salt tolerant bacteria can be used to increase the biodegradation rate in saline environment with low level of oxygen. In this paper, BTEX biodegradation by Bacillus thuringiensis andBacillus sp. is investigated in microaerophilic and saline environment under nitrate reducing condition. Firstly, the ability of the above- mentioned bacteria in BTEX biodegradation was confirmed. Then, the effect of Nitrate, BTEX concentration, salinity and cell mass on BTEX degradation was studied using Taguchi method and design expert software. The results of this study showed the ability of the Bacillus thuringiensis andBacillus sp. on BTEX degradation. For 200 mg/L BTEX concentration, the high efficiency of degradation by Bacillus thuringiensis andBacillus sp. could be achieved in optimum conditions; Nitrate Concentration (200 mg/L), salinity (1 and 5 %) and cell mass (1and 5×107 cell/ml) respectively.

Despite of numerous studies on BTEX biodegradation, a few researches has been conducted to optimize the environmental conditions for biodegradation of this pollutant considering the effective factors. The objective of this study was to investigate the effect of environmental factors such as nitrate, salinity and cell mass (the isolated bacterium from the soil) on BTEX degradation and to optimize the environmental conditions for biodegradation. In order to identify the appropriate microorganism for BTEX degradation, isolation of the bacterium from the oil contaminated soil was performed firstly. Then the nitrate, salinity, cell mass and BTEX concentrations were considered as independent variables to optimize BTEX degradation conditions by the isolated bacterium. Finally, a quadratic polynomial mathematical model was suggested by the Design Expert software (R2=0.85). This research showed that the isolated bacterium is able to degrade BTEX and the proper condition for degradation can be achieved by applying the above-mentioned model. Results showed that the effect of BTEX and Nitrate concentration on BTEX degradation is significant. So that increasing BTEX concentration to the extent of 200 ppm and decreasing nitrate concentration to the extent of 400 ppm reduced BTEX degradation to 4.2% and 9%, respectively.

Feasibility of pressurized irrigation systems, based on the chemical properties of the water, at sub-regional and regional scale, It is especially important for its implementation. In this study, GIS has used for zoning of Marvdasht-Kharameh land suitability for executing pressurized irrigation systems based on indices irrigation water quality. In this study, the data of 50 wells water measured in 2014-2015 has used. The zoning map based on the HCO3 index showed that most of the region has a low to moderate limitation for performing sprinkler irrigation system. In addition, the zoning maps Cl and Na parameters in the Marvdasht-Kharameh study area showed that 84.6% and 78.2% Of land area respectively, are faced limitation for performing sprinkler irrigation systems. The results showed that in 60.2% and 27.3% of the area, there is a serious limitation and a low to moderate limitation for performing drip irrigation based on TDS and EC parameters, respectively. Throughout the study area, there was a limit to the pH index for implementing the drip irrigation method; which there have 90.4% and 9.6% of the land subject has a low to moderate limitation and serious limitation on pH index for performing drip irrigation system, respectively. The results showed that for the majority of the area, there is no limitation on LSI index for performing drip irrigation system because of Acidity of groundwater in the area.

The main objective of this study was to evaluate the surface and deep distribution of Pb, Ni and Cu in the wastewater-irrigated area of south of Tehran using GIS and Hydrus. It was expected to find a comprehensive information of heavy metals distribution and their accumulation in the soil. This study was carried out in wastewater-irrigated area of south of Tehran. Soil sampling from the top surface layer (0-15 cm) and wastewater channels was done. After sample analysis, ordinary Kriging method using different variogram in GIS was applied to explore the surface distribution of Ni, Pb and Cu heavy metals. Moreover, the deep percolation of heavy metals in the soil profile was simulated by Hydrus-1D in a duration of 210 days and the heavy metals concentrations in the soil were estimated. Exploration of the distribution of Pb using spherical model showed that the variation of this element was in the range of 20-70 mg/kg. This amount varied to 50-60 mg/kg for Cu and about 30 mg/kg for Ni. Moreover, the simulation of heavy metals deep percolation using Hydrus revealed that the most accumulation of heavy metals happened in the 0-15 cm soil surface layer and for deeper layer, this trend was descending. Comparing the concentration of Pb, Cu and Ni with the maximum allowable amounts of WHO standards demonstrated that Pb concentration was more than the threshold limit. Finally, the applied models could simulate soil’s heavy metals content for both surface and deep distribution in the studied area.

One of the most important components of the hydrological cycle is evapotranspiration which plays an important role in water resource management. In the present study the accuracy of evapotranspiration estimation by Hargreaves method and correction factor K was improved using the neural network and decision tree model M5. This coefficient is the ratio of Penman-Monteith evapotranspiration model is the method of Hargreaves. The data used in this study are the maximum and minimum temperatures and relative humidity in the period 2004-2013 Farokhshahr stations and airports in the region ShahrKord is cold and arid. Network Levenberg-Marquardt training algorithm is designed with a feedforward network and sigmoid tangent function is hidden in layers. Decision tree model was designed to help software WEKA. The results show that the neural network and decision tree model to model good performance, but the performance of the neural network model is more accurate correction factor. The results showed that the correction factor carefully before using the Hargreaves RMSE = 0.90 (Root Mean Square Error) Penman-Monteith than that this value after the correction factor to help RMSE = 0.69 and with the use of neural networks the correction factor to help decision tree to reach RMSE = 0.72. The results showed that after using a correction factor to the improved performance of Hargreaves.

Heavy metals pollution is one of the main drawbacks of using wastewater for irrigation. Exploring the pollution of heavy metals in a big area needs frequent experimental measurements, which is mostly time and money consuming. In such a condition, using satellite images and making a relationship between images and heavy metal’s concentration can be a solution for estimating the polluted area. In this study, the image of Sentinell2 satellite was used to evaluate the heavy metals pollution of wastewater irrigated area in south of Tehran. For this aim, 30 soil-surface samples were collected in the area that is irrigated by raw wastewater. After preparing the samples, the concentration of Pb, Cu and Ni was determined using atomic absorption spectroscopy. Then the relation between the heavy metals concentration and reflectance in the bands or the ration of the bands at the corresponded sampling points was determined by applying the stepwise regression method. The developed models were applied on the satellite image for zoning the heavy metals concentrations in the study area. Finally, the accuracy of the developed models was examined by Root-Mean-Square Error (RMSE) and Pearson correlation coefficients. The results showed that the amounts of RMSE for the equations of Pb, Cu and Ni were 1.90, 2.54 and 1.59 respectively while the amounts of R were 0.81, 0.75 and 0.73 for these metals that showed a promising match between predicted and measured results of the models.