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.

Rice is most important agricultural crop of Guilan province sensibility to salinity and alkalinity of water and soil. In recent years, using of toxicants and fertilizers in farmlands, constructing several dams upstream, entering agricultural, homemade and industrial sewage in to a river, and drought have decreased gradually discharge of river and increased salinity of Sefidrud River as an irrigation source of Sefidrud irrigation network of Guilan province. This research tries to determine the optimal intermittent and depth of irrigating of rice in proportion to salinity of Sefidrud River using of optimization- simulation mechanisms as is the decrease in crop efficacy become minimum. To achieve this, an agro hydrological SWAP was used to simulate different stages of rice growing and an optimization Model was used in a reasonable range of the intermittent rice irrigation period and depth with regard to different growth stages. Because some types of rice are affected by salinity, field experiments of Hashemi variety in Rasht in 1386 were used to calibrate the Model. Optimal values of the intermittent irrigation regime in current salinity of the Sefidrud River (1.747 ds/m) included 8 days intermittent irrigation period and the depth of water for irrigating was 1, 3, 4 and 5 for vegetative, tiller, maturity and harvest stages respectively. The comparison of results of optimization- simulation Model with field data in 1389 showed good efficiency of this Model in irrigation optimization. In the field experiment 8 days intermittent period with irrigation 5 cm in depth was highest crop performance in 2 ds/m salinity.

This study was conducted to evaluate the response of hybrid varieties of maize (single cross 260) under drip irrigation treatments in the Fars province in 2012 and 2013 at the Experimental Field of Islamic Azad University of Shiraz. Irrigation levels were 20, 40, 60 and 80% deplection of moisture contents and experiment was conducted in a randomized complete block design. The triats measured were leaf area index, dry matter yield and total biomass in 2012 and the measurements were repeated in 2013 to validate the use of SWAP Model. The results showed that simulated yield changes by the use of Model, at different levels of irrigation levels in the farm, corresponded with the yield changes in the field. Statistical indices including correlation coefficient (greater than 0.9), t-test (greater than 0.05), the root mean square error and normalized root mean square error (RMSEn) equal to 1.9-6.9, indicate good performance for grain yield and total biomass by using the SWAP Model.

In this study, the effects of different quality and quantity levels of irrigation water on crop yield, soil water and solute transport were simulated using SWAP Model. Field experiments were conducted for the six main crops of the region such as wheat, barley, onion, sunflower and sugar beet at Rudasht drainage and soil reclamation research station. The effects of water salinity under different irrigation managements on crop yield, crop yield components and soil salinity were investigated. The SWAP Model was calibrated by inverse Modeling and was linked with the PEST Model. The Model calibration consisted of hydraulic parameters of soil layers as well as solute transport and crop parameters. In order to evaluate Modeling validity, statistical indices such as coefficient of determination, root mean square error, Modeling efficiency and coefficient of residual mass were calculated. Result of the Model analysis showed that with precise calibration, SWAP Model is able to predict soil water and solute transport and crop yield with high degree of accuracy. To determine crop-water-salinity production functions, SWAP Model was linked to the SENSAN Model, then by changing irrigation water depth and salinity values, the Model was executed. In order to determine optimal production function for each crop, six functions including linear, cobb douglas, transcendental, translog, quadratic and the Leontief were examined and the pertinent parameters were determined with ordinary least square method using SHAZAM Model. Based on statistical indices the optimal production function for wheat, barely, sugar beet, onion and cotton were adjusted Leontief and for sunflower was quadratic.

Shallow water table is an important problem in arid and semi-arid regions. Since it causes reduction of agricultural yield; therefore, water table fluctuation is necessary to be monitored in irrigation and drainage fields. These conditions are intensified for arid and semi-arid countries, such as Iran, where saline groundwater is the main water resource. These problems were increased in sugarcane industrial farm that covered large area in Khuzistan province, Iran. Therefore, it is necessary to determine water table in sugarcane field during growing season. Regarding the purpose, it is important to evaluate water table fluctuations in each farm continuously. There are some problems to achieve this purpose like spending time and financial supports. So, computer Models are developed to solve the problems. In the other hand, water table can be simulated under different farm conditions, even before designing an agricultural unit, using the Models. In order to achieve the mentioned goal, this research was conducted to evaluate three Models: DRAINMOD, SWAP and Endrain, to simulate water table levels in Amirkabir Agro-industry farms. The studied area is located at latitude between 31˚ 15’ and 31˚ 40’ and longitude between 48˚ 12’ and 48˚ 30’ , southwest of Iran. Regarding this aim, water table data were collected from a 25 ha farm. Each Model use different equations to simulate water table. Nevertheless, Richards’ s equation is the main formula to determine water movement in saturated and unsaturated soils. SWAP uses this formula as following: Where: θ is volume of water content (cm3. cm-3); t, time (hr); z, increasing in depth to soil surface (cm); K(θ ), hydraulic conductivity (cm. h-1) and h is hydraulic pressure (cm). In order to estimate all of those parameters, sample data were collected from the farm. In addition, RETC Model was used to determine some of mentioned data. Upper boundary conditions like irrigation and rainfall were measured from local sensors. For simulating evapotranspiration, meteorological data were collected from the nearest metrological station. SWAP uses FAO Penman Monteith equation and Drainmod applies Thornthwaite formula. Lower boundary conditions were also determined based on soil and drains conditions. Before simulation, all data were randomly sorted out. Then, 70% of them were used to calibrate those Models and the 30% of remained data were used for validation. Four statistics criteria root mean square error (RMSE), Modeling efficiency (EF), coefficient of residual mass (CRM) and coefficient of determination (R2) were used for evaluating the results. The calibration results of soil physics parameters for SWAP and DRAINMOD revealed that in both Models, the parameters n and Alpha had the most variations compared with the other parameters. Similar results were cited by other researchers. In calibration stage, the amount of R2 for DRAINMOD Model was 87. This result showed that there was a good correlation between field and simulated data. The result of R2 for SWAP and ENDRAIN Models were 83 and 93, respectively. RMSE values for DRAINMOD, SWAP and ENDRAIN were 12. 42, 10. 46 and 11. 63 cm, respectively. So, in the calibration stage, SWAP had more accuracy, compared with the other Models, to determine water table. The CRM values were obtained as-0. 028,-0. 022 and-0. 061 cm for DRAIMOD, SWAP and ENDRAIN, respectively. Then, all three Models lead to overestimate of water table. The results of EF were 0. 83, 0. 85 and 0. 88 for mentioned Models, respectively. Validation results of DRAINMOD Model revealed that RMSE, CRM and R2 were 13. 19 (cm),-0. 008 and 0. 85, respectively. These statistical criteria were found to be 17. 00 (cm), 0. 020 and 0. 82 for SWAP. These parameters were obtained as 28. 10 (cm), 0. 603 and 0. 82 for ENDRAIN Model. Therefore, all the Models had acceptable error to estimate water table depth. The results of EF were 0. 84, 0. 75 and-2. 80 for DRAINMOD, SWAP and ENDRAIN Models, respectively. These results showed that ENDRAIN was inefficient to determine water table. It is due to lack of using parameters to simulate all boundary conditions in soil. However, since DRAINMOD simulates evapotranspiration and downside boundary conditions well, the mentioned results were better rather than two other Models. Although DRAINMOD had a better accuracy compared with SWAP, both of those Models had good efficiency to simulate water table. Thus, DRAINMOD had overestimate error and SWAP and ENDRAIN had underestimate error. DRAINMOD is recommended as a better Model according to the higher coefficient of determination and lower error value.

Using mathematical Models for irrigation management have great impacts to increase irrigation efficiency and product amount, in fields. In this study, simulation results by SWAP Model for moisture, compared with soil profiles moisture values, measured in the field. Moisture data, measured at three wheat farms in the Neyshabur plain, were used to predict moisture. Results show good agreement between simulated and measured moisture values. R2 coefficient values were 0.611 for Farob Roman farm, 0.648 for Haji Abad farm and 0.679 for Soleimani farm, respectively. Model absolute value was between 1.5 to 2.9 percent and root mean square error (RMSE) value was between 1.9 to 4 percent. According to these statistical indices, SWAP Model has been able to simulate moisture, in soil profile in different depths and times, accurately. Therefore, SWAP can be used for irrigation management in Neyshabur plain, with relatively sufficient accuracy.

In recent years, increasing economic losses as a result of natural disasters are one of the main challenges fronting the insurance industry and researchers to discover original financial instruments so as to transmit disaster risks and minimize economic losses. In the present article, a Model is suggested for catastrophe SWAP pricing with deterministic loss fluctuations in order to decrease the risk of insurance and reinsurance companies in Iran. The research is retrospective and applied; the data collection method is the library, and for the data collection use the documents. For the full data extraction, the correlation method is applied, For the purpose of extracting the complete data, the correlation method is used, all damages of earthquakes that have been fatal, destructive and affecting in the period 1927 to 2018 in Iran, have been investigated. The probability of the deterministic loss occurrence and severity are regarded to be Brownian motion of jump-diffusion. The extracted integral-differential Model is converted into the standard differential one, and the answers are estimated via finite difference method and Matlab software. The changes to the suggested Model are explored through the Lambda sensitivity analysis. As a final point, the Model is implemented with real data of earthquake losses in Iran, which is extracted from the EM-DAT database and the regression results. Based on the results of the study, the price of catastrophe SWAP securities for less loss than the threshold has regular upward trend; however, once loss reached and passed the threshold, prices will drop dramatically.

In this research, SWAP Model was evaluated to estimate soybean grain yield, biological yield, leaf area index, water productivity, and available soil water content in soil profile. The sensitivity of SWAP Model was analyzed based on the field results obtained from soybean planting with four furrow irrigation treatments including full irrigation, conventional deficit irrigation at 75% and 50% soil moisture deficit compensation, and partial root zone drying at 50% soil moisture deficit compensation in 2008 agronomical year. Then it was calibrated, validated and evaluated based on the field results of the agronomical year 2009. The results of this study indicated that this Model simulated grain yield better than biological yield. The best and the worst simulations of soybean water productivity were obtained at partial root zone drying and conventional deficit irrigation treatments at 50% soil moisture deficit compensation, respectively. Based on calculated statistical indices in this research, the best simulations of the Model that had the best fitting with the measured data, were at grain yield, water productivity, leaf area index, biological yield, and volumetric soil water content (the least RMSE and ME and the highest R2), respectively. Also the results of the Model sensitivity analysis showed that SWAP Model was sensitive to soil input data, i.e. residual moisture and saturated hydraulic conductivity, and with any little change in these input data, output results (the amounts of simulated parameters) varied greatly.

In this study, seven main field crops of the Rudasht and Abshar Irrigation Networks of Esfahan (with 54,000 ha designed command area) such as Wheat, Barley, Onion, Sunflower, Fodder Mays and Sugar beet were selected and SWAP Model was calibrated by inverse Modeling base on field experiments results in order to determine crop water salinity production functions. Field experiments were conducted with effect of saline water with different irrigation managements on crop yield at Research Station of Drainage and Soil Reclamation of Rudasht during 1996 to 1998 and 2005 to 2007. In terms of insufficient field treatments and in order to fit proper crop yield production function, SWAP calibrated Model was run for different quantity and quality levels of irrigation water. Quadratic form of crop yield production function was calculated for 6 salinity levels of irrigation water include 1, 2, 4, 6, 8 and 10 dS/m and each crop. Optimal irrigation depth in different condition include scarcity of water quantity, land quantity and water quantity and quality was calculated base on crop yield production function, cost production function and marketable price of each crop based on 2008 with respect to maximize net benefit. Results of analysis showed that in scarcity of water quantity for 10000 m3 available water, maximum net benefit gain onion cultivation with 52.6×106 Rials beside with 1.16 ha of area cultivation. In land scarcity condition for specified available water, maximum net benefit gain onion cultivation, too. In scarcity of water quantity and quality condition, with increasing salinity of irrigation water, for 10000 m3 available water salinity level of irrigation water equal 2 dS/m, maximum net benefit gain onion cultivation with 35.11×106 Rials beside with 1.44 ha of area cultivation, too. In salinity level equal 6 dS/m, maximum net benefit gain wheat cultivation with 18.37×106 Rials and next maximum net benefit barely cultivation with 13.9×106 Rials. Yield of Onion and Fodder Maize decreased severely so that for higher than salinity level of irrigation water equal 6 dS/m, net benefit was negative. In salinity level equal 10 dS/m, maximum net benefit gain barely and next sugar beet cultivation.

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.