This study was conducted to evaluate the effect of changes in irrigation water quality and quantity which applied for cotton in the Rudasht irrigation system in Esfahan. This was performed by using a physically based, well-tested SWAP SIMULATION MODEL for crop growth, water and salt transport at field scale. Results indicated that the current practice of 900 mm annual irrigation application rates for colton, with salinity level of 4 dS m-1. Different scenarios are studied based on changes in water quantity and quality and their effect on the water and salt balance and crop yields. The first scenario is the baseline scenario which describes the current situation and will function as a reference for the other scenarios. According to the results, an almost linear relationship exists between the amount of water applied by irrigation and the amount of percolation. Soil evaporation was also linearly related to the irrigation supply. Crop transpiration and relative yields reached their maximum level at an irrigation input of about 1000 mm. Increase in appled irrigation water to more than 1100 mm caused soil salinity levels decrease slightly, but deeper collation, water logging, and soil salinity increased.At the current practices, cotton yield in average was about 66% of the potential yield (5000 kg ha-1). An incease in irrigation water salinity to 6 dS m-1 caused cotton yield decreased to 51% of potential level.

There are two approaches for simulating memory as well as learning in artificial intelligence; the functionalistic approach and the cognitive approach. The necessary condition to put the second approach into account is to provide a MODEL of brain activity that contains a quite good congruence with observational facts such as mistakes and forgotten experiences. Given that human memory has a solid core that includes the components of our identity, our family and our hometown, the major and determinative events of our lives, and the countless repeated and accepted facts of our culture, the more we go to the peripheral spots the data becomes flimsier and more easily exposed to oblivion. It was essential to propose a MODEL in which the topographical differences are quite distinguishable. In our proposed MODEL, we have translated this topographical situation into quantities, which are attributed to the nodes. The result is an edge-weighted graph with mass-based values on the nodes which demonstrates the importance of each atomic proposition, as a truth, for an intelligent being. Furthermore, it dynamically develops and modifies, and in successive phases, it changes the mass of the nodes and weight of the edges depending on gathered inputs from the environment.

Many mathematical MODELs have been applied and developed for SIMULATION of water and solute transport in irrigated agriculture. Using a MODEL, it should be first calibrated and validated for different regions. SWAP is a field scale MODEL that simulates water, solute and heat movement in the soil profile. In this study, the SWAP MODEL was evaluated for two years (2001 and 2002) on wheat in a semi-arid area in North of Gorgan. Required data were collected by field experiments. The experiments were consisted of four water quantity levels (50, 75, 100 and 125 percent of crop water requirements) and four water quality levels including S1, S2, S3 and S4 having 1.6, 7.9, 10.8 and 13.6 dS/m in the first year and 1, 9.3, 12.2 and 14.7 dS/m in the second year, respectively. The experimental design was performed by randomized complete block design as a split plot layout with three replications. Based on statistical analysis, results from the SIMULATION of SWAP MODEL were in good agreement with the field measurements of water content (q), salinity (ECe) along the soil profile and wheat relative yield. In all cases, correlation coefficient (R), was higher than 80 percent and root mean square error (RMSE) was less than standard division (Sd). In the first year, bottom boundary condition was supposed to be free drainage, but due to fluctuations of water table in harvest time, MODEL under predicted soil water content in 80-100 cm depth. Since the high frequency of rainfall (especially in second year) and elimination of deep percolation, the discrepancy between the measured and predicted ET was not satisfied.

Determation of moisture distribution pattern is time-consuming and a costly field tests. SIMULATION MODELs are a suitable alternative in answer to issues of water movement and distribution. In this research, soil moisture under drip irrigation was simulated with SWAP MODEL and the MODEL efficiency was evaluated by comparing the simulated results with field results. SWAP MODEL was evaluated based on the information gathered from a research field of Water Sciences Faculty, Shahid Chamran University of Ahvaz under corn cultivation and equipped with drip irrigation system. The hydraulic parameters were obtained from RETC MODEL in the growing season of 2012-13. Required data were collected by field experiments. The experiments consisted of two treatments of salinity including treatments T1 (Karun River water with salinity of 3 dS/m) and treatments T2 with salinity of 3.5 dS/m. Planting was done by hand in plots including four rows of 3 m with row spacing of 75 cm and with a plant density of 80, 000 plants/ha. Irrigation system was drip tape with emitter holes spacing of 20 cm and discharge of 2.2 lit/h at a pressure 0.6 bar. Comparison of the measured soil moisture with simulated soil moisture to a depth of 90 cm depth was performed on the ridge and 10 and 20 cm from emitter by drawing graphs and calculation of Maximum Error (ME), Normalized Root Mean Square Error (NRMSE) and Coefficient of Residual Mass (CRM). Computed values of ME, NRMSE and CRM in different locations were as follows: 10 cm from emitter: 0.02, 14.41 and -0.0016 cm3 cm-3; 20 cm from emitter: 0.07, 15.49 and -0.036 cm3 cm-3, and on the ridge: 2.1, 12.52 and -0.036 cm3 cm-3. SWAP MODEL accuracy in estimating changes in moisture away from the emitter decreased with increasing distance from the emitter. This may be due to low precision of the MODEL under high salinities. Generally, the results obtained from stimulating by SWAP showed that this MODEL could stimulate moisture distribution in soil under drip irrigation with salty water. This MODEL can be used as a useful tool for evaluation of moisture distribution around the a dripper.

Precise knowledge of all components of water balance is essential to optimize water use in irrigated agriculture. However, water balance components are difficult to measure in required time intervals because their measuring is time consuming and costly. Unsaturated zone simulator MODELs are useful tools for predicting the effects of agricultural management on crop water use and can be used to optimize agricultural practices such as agricultural water use. This research has been done on Wheat irrigated farms in Neyshabur plain, that is one of important plains in Khorasan Razavi province. SWAP Agro-hydrological MODEL, was used for SIMULATION of water balance components and crop growth in three wheat fields: Farob Roman, Hajiabad and Soleimani. Input data for MODEL was a combination meteorological and field data. RETC software package was employed to evaluate and calibrate the soil hydraulic parameters, used. SIMULATION period was selected from October 2008 until early June 2009, in accordance with the wheat growing season. Sensitivity analysis to soil hydraulic parameters showed that the MODEL is more sensitive to a and n coefficients. Also, acoording to presented statistical parameters, the results showed that SWAP is able to simulate water flow in soil, truly. Mean R2 coefficient value was 0.62, Mean Error was between -0.1 to -2.28 and Relative Error was fluctuated between - 0.33 and -12.69. Therefore, calibrated SWAP MODEL can be used as an instrumental tool for calculating all components of water balance in field scale, with time and cost saving.

Despite the high capability of field-scale agro-hydrological MODELs to simulate plant growth interactions with water and solute transport in agricultural systems, their application to real conditions of large sugarcane fields in Khuzestan province faces many challenges, including spatial heterogeneity of irrigation scheduling across the field, the difficulty of determining initial and boundary conditions as well as several unknown MODEL parameters, and data–, intensiveness of calibration procedure. This work aimed to implement the agro-hydrological MODELing under real operational conditions of large fields with surface/subsurface drainage. In this work, a distributed agro-hydrological MODELing scheme was developed through the application of a modified version of the SWAP MODEL and an improved variant of the Unified Particle Swarm Optimization (UPSO) algorithm with capability of sub-daily calibration and SIMULATION of controlled drainage. The developed MODEL was applied to a sugarcane field with subsurface drainage with planted sugarcane (CP48-103 cultivar) in Imam Khomeini Sugarcane Agroindustrial company farms, during 2010-07-19 to 2011-12-11 (481 days). The results revealed the reasonable performance of the developed MODELing scheme in retrieving the measured soil moisture, groundwater level, subsurface drainage outflow (with an EF of 0. 901, 0. 827, and 0. 877 for calibration dataset,and 0. 514, 0. 798, and 0. 672 for validation dataset, respectively), soil water solute concentration, subsurface drainage outflow salinity (with a NRMSE of 0. 039 and 0. 096 for calibration dataset,and 0. 154 and 0. 046 for validation dataset, respectively), Leaf Area Index, cane yield, and sucrose yield (with an EF of 0. 995, 0. 999, and 0. 972, respectively).

In recent decades, several MODELs have been developed to simulate farm water management. The main focus of most researchers is obtaining more products per unit of water consumed. Water productivity defined as crop yield per unit of water consumption. Due to limitation of water resources and its optimal consumption in order to save water and increase its productivity, this study was conducted to simulate water productivity indices of rice (Hashemi caltiver) using SWAP MODEL in paddy soils at field scale. For this purpose, two closed-ended lysimeters were used to measure the actual evapotranspiration. The quantity of evapotranspiration was measured daily and water productivity based on irrigation water (WPir) and evapotranspiration (WPET) was calculated and compared with the simulated values afterward. The obtained results indicated that the SWAP MODEL had a high accuracy for estimating amount of yield (R2=0.90 and RMSE=648.73) and the amount of water consumed in the evapotranspiration process (R2=0.89 and RMSE=164.07). Using the calibrated SWAP MODEL, the water productivity indices from division of yield on evapotranspiration (WPET) and yield on irrigation water (WPir) in the studied farm was estimated amount of 0.553 and 0.876 kg/m3, respectively. Also, results showed that with increasing irrigation efficiency, elimination of deep percolation and reduction of evaporation, water use efficiency increases by 30%. In general, for optimal management of paddy soils in field scale and considering the optimal yield at harvest time, serious attention must be paid to water efficiency to come up with most effective ways to deal with water crisis and to increase the quantity and quality of rice production.

In recent years, in order to solve problems were presented the way tasks in the agricultural sector. Among these, growth SIMULATION MODELs have been provided for water management, which it possible to reduce the difficulties in agricultural water. The main advantage of these MODELs is that, they can optimize irrigation schedule economically. SWAP MODEL is of the most widely used MODELs in the world which has shown good results for variety of crops. So that, in this practice the performance of this MODEL for simulating the growth of Canola was evaluated according to the data relating to two cultivation periods in Badjgah. The studied parameters con-sist of soil water content, evapotranspiration, dry matter, and seed yield. The results indicated that, in the calibration and evaluation phases for seed yield respectively, mean normalized error was 8.0 and 14.2. What is more, mean normalized error for SIMULATION of dry matter was 3.9 and 10.8 in calibration and evaluation periods, respectively.

Due to the dry climate and limitation of fresh water resources, using fresh and salt water is a solution for crop production under salinity conditions. This study was conducted at Isfahan University of Technology as a randomized complete block design with three replications and five irrigation management treatments in 2014. The treatments included irrigation with saline water (with the salinity of 5 dS/m, based on the relative yield of 75%), irrigation with fresh water (municipal water), alternate irrigation (irrigation with saline water and the next irrigation with fresh water), conjunctive irrigation (half of irrigation with saline water and the other one with fresh water) and irrigation with fresh water to reach the raceme stage, and irrigation with saline water. The maximum wet yield, dry yield and grain yield were related to the fresh water treatment with 4. 14, 2. 45 and 0. 588 kg/m2 and the minimum values were obtained for water their water treated with 1. 34, 0. 765 and 0. 0957 kg/m2 respectively. The conjunctive treatment had the highest yield after fresh water treatment. The various statistical indices showed that this MODEL could be used for sorghum in Isfahan. The determination coefficient for yield was 0. 65. The priority of MODEL for yield SIMULATION was salt water at the last stage, alternate irrigation, saline water, conjunctive irrigation and fresh water treatments, respectively.

Introduction Reduction of water resources in arid and semi-arid areas requires the application of management methods to achieve optimal performance. With the logical application of saline water as a source of irrigation water, we can supply a part of the crop water requirement (Hamdy, A., Abdel-Dayem, S. and Abu-Zeid, M., 1993), using various applicable management techniques. The optimal management is, in turn, considered as the use of conjunctive irrigation. Two commonly used solutions include mixing salty and fresh water to obtain water with the optimal salinity; and also the periodic application of fresh and salty water (Amer, 2010; Aslam, & Prathapar, 2006). In effect, salt mainly enters the surface layers of the soil through irrigation and the solute moves vertically from the unsaturated to the saturated zone and towards the groundwater. In turn, the SWAP MODEL is often used to simulate the solute transfer in soil. However, field measurement of the solute concentration changes is very difficult in soil profiles. A SIMULATION MODEL can, thus, be used to estimate the accumulation of solutes in the soil profiles. (Van Dam, Huygen, & Wesseling, 1997)...