JWSS - Journal of Water and Soil Science

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The general goal of this research was to study the effective factors on the success of the poultry-farm cooperatives in Isfahan province. Based on multi-stage cluster sampling and Chocran formulas, nine cooperatives and 173 members were selected from 15 cooperatives with 1768 members. After completion of questionnaires, the AHP method was employed for scaling. Statistical tests (factor analysis and alpha coefficient) indicated that this research has a high construction validity and reliability. The research results indicated that cooperative functions toward fulfillment of members' demands were weak. The results of the path model indicated that effective factors on the success of cooperatives (from highest to the lowest) are: knowledge of cooperative principles by the members, extra-organizational factors, education quality, managers' skills, participation in cooperative affairs, and members' education level. Also, the success of cooperatives much relies on inter-organizational factors. The amount of members' share from education, participation in cooperative's affairs, the managers' specialty and skills, and knowledge of cooperatives' principles are very weak. Research results indicated that there is a direct and statistically significant correlation between these independent variables and the success of cooperatives in Isfahan province.

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Conventional soil survey methods for soils within the watersheds in Iran require a significant budget with many soil surveyors and much time. Additionally, no accurate and reliable information exists on the spatial variability of superface soil parameters in order to predict the soil loss by different models (RUSLE, PISAC, EUPOSEM, MORGAN). Also information on planning and management activities is lacking. These limitations call for methods of estimating soil properties using minimum sampling derived from important terrain parameters. This study was performed to develop soil-landscape models in three geological units (E2Sc, Ku, Plc), in a part of Mehr- watershed, Sabzevar. Six soil variables selected for this study were topsoil clay, gravel, sand, organic matter content, field capacity and bulk density measured at 316 sites on a regular 100m grid. Topographic attributes were calculated by a digital elevation model with 100m spacing. Finally, multiple linear regression analyses relating soil to topographic attributes were performed and then models were validated by additional sample points (78 of 316). The developed regression models showed significant relationships between surface soil properties and topographic attributes such as elevation, slope, aspect, wetness index, stream power index and sediment transport index. The mean errors and root mean square errors in the validation of the models were low and acceptable. The regression equations could explain only 26 to 72 % of the variability measured in the soil attributes in the watershed scale with 100m spacing.

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Using a deterministic model for dairy herd according to milk pricing system in Iran, the economic weights of milk production, fat percentage, protein percentage and herd life with minimized cost were identified, while restricted total input and total costs were variable in animal unit. By data simulation and the data obtained from 3 different dairy herds in Iran, the sensitivity of economic values with the assumption of 20% change in forage and concentrate price, forage to concentrate ratio, feed-cost, non-feed cost, base price of milk, free-market price of milk, average milk production, fat percentage, protein percentage and herd life were estimated. In the base condition, the economic weights of milk production, fat and protein percentage and herd life in three herds were -0.55, -0.24, -0.54 -34, -20, -11 -34, -37, -33 -0.37, 0.67, -0.39, respectively. The effect of change in different factors of production system on economic weights of three farms was variable. The economic weights of milk production, fat percentage, protein percentage and herd life had the most sensitivity to change in the average milk productoin, base price of milk and herd life, respectively.

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Isotherm curves are useful for the designing of dryer as well as controling of the seed moisture content during storage and drying process. To study the curves, this research was performed on the basis of two factorial experiments including three factors: (1) hybrid at two levels (Three Way Cross 647 and Single Cross 704) (2) temperature at 6 levels (from 5 to 55°C) and (3) Relative Humidity (RH) at 5 levels (from 10 to 90 percent) for the analysis of the adsorption and desorption phenomena. For maintaining RH at the above mentioned ranges, glycerol solutions with different concentrations were used. The results showed that the relationship between solutions concentration and their RH was non-linear and somewhat related to temperature. Also, statistical analysis displayed that for 3 factors of tepmerature , RH and hybrid, the effects on Equilibrium Moisture Content (EMC) in both adsorption and desorption phenomena were significant at α=1%. Comparisons of means showed that hybrid 704 had higher EMC values than did hybrid 647 under the same conditions, in other words, hybrid 704 produced lower a_w than did hybrid 647 at the same moisture content. Fitting experimental values on non-linear models (Henderson, Chung-Pfost and Oswin) showed Oswin as the best model for adsorption and desorption curves for hybrid 704 and also for adsorption curve for hybrid 647 , but the best model for desorption curve for hybrid 647 was Chung-Pfost.

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Because of slight variation of the static head due to discharge fluctuations, the labyrinth weirs are considered to be economical structures for flood control and water level regulation in irrigation networks, as compared to other devices. Labyrinth weirs are composed of folded sections observed as trapezoidal and triangular in plan view. In this study, rectangular and U-shaped labyrinth weirs were investigated. Experiments were conducted on 15 labyrinth weir models. The models included eight rectangular labyrinth models and six U-shaped labyrinth models with different heights and lengths, and one linear model. All the experiments were performed in a horizontal rectangular flume, 7 m long, 0.32 m wide and 0.35 m high. The results indicated that for all the models, discharge coefficient increased sharply with an increase in Ht/P and attained a maximum value. This coefficient then decreased smoothly with a further increase in Ht/P. Increasing height of weirs increased the discharge coefficient for both rectangular and U-shaped weirs. The results also showed that increasing the length parallel to the flow direction decreased and increasing the length perpendicular to the flow direction increased the discharge coefficient. Generally, the discharge coefficient for rectangular weir was less than that of the U-shaped weir. The obtained results compared with those of Tullis et al. (1995) showed that discharge coefficient for U-shaped weir is more and for rectangular weir is less than that of the trapezoidal weir for angle of the side legs of 8 and 12 degrees.

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Agricultural investigations use computer models for simulation of crop growth and field water management. By using these models, the effects of plant growth parameters on crop yields are simulated, hence, the experimental costs are reduced. In this paper, the model of MSM (Maize Simulation Model) was calibrated and validated for the prediction of maize forage production at Agricultural College, Shiraz University in 1382 and 1383 by using maize forage yield under furrow irrigation with four irrigation and three nitrogen treatments. Irrigation treatments were I4, I3, I2, and I1, with the depth of water 20% greater than, equal to, 20% and 40% less than potential crop water requirements, respectively. Nitrogen treatments were N3, N2, and N1, with the application of N as urea equal to 300, 150, and 0 kg N ha^-1, respectively. After calibration and validation of MSM, it was used to estimate suitable planting dates, forage yield and net requirement of water discharge for planting at different dates. The results indicated that the net requirement of water discharge was reduced by gradual planting at different planting dates. By considering different planting dates for maize, from Ordibehest 20th to Tir 10th, the planting area might be increased 17.9%, compared with single planting date on Ordibehesht 30th under a given farm water discharge and full irrigation.

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In this paper, the effect of irrigation water salinity levels on seed germination, dry matter weight of seedlings at eight-leave stage, and the salt tolerance of 8 rapeseed cultivars was investigated. Relative yield reduction in saline and non saline conditions, salt sensitivity index and Van Genuchten-Hoffman methods were used to determine the salt tolerance of the cultivars. Results showed that the effect of different salt levels, cultivars and their interactions on germination and dry matter weight of seedlings was significant at 0.01(the higher the salt level, the lower the germination and dry matter). Also, using the Van Genuchten-Hoffman method, the irrigation water salinity corresponding to 10%, 25%, 50% and 90% reducts in germination and dry matter of seedlings were determined. Statistical analysis showed that a single cultivar gives different responses to salinity during growth stages and it may be tolerant in one stage, but sensitive to salinity in another growth stage. In this research, ACSN1, Falcon, and Shirali in germination stage and ACSN1, Falcon, and Cobra in seedling growth stage were salt tolerant. The three cultivars Oyerka, Global, and Ceres and the next three Shirali, Global, and Oyerka were sensitive to salinity in germination and seedling growth stages, respectively. Finally, the ACSN1 and Falcon cultivars were introduced as salt tolerant, and Oyerka and Global were considered as salt sensitive.

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Heavy metals including cadmium (Cd) and lead (Pb) are entering agricultural soils from different routes and mainly due to human activities. Accumulated Cd and Pb in the soil would eventually enter the human and animal food chains and pose threat to their health. Therefore, evaluating heavy metal accumulation is necessary to prevent soil and environmental pollutions and should be considered by researchers as well as policy makers. This study was conducted to model the accumulation rates of Cd and Pb in the agro-ecosystems of Isfahan, Mobarakeh, Lenjan, Borkhar, Najafabad, Khomeinishahr and Felavarjan. Cadmium and lead accumulation rates in the agro-ecosystems were computed using a stochastic mass balance model which uses Latin Hypercube sampling in combination with Monte-Carlo simulation procedure. Agricultural information including crop types, crop area and yield, the type and the number of livestock, application rate of mineral fertilizers, compost and sewage sludge and also metal concentration in plant and amendments were used to quantify Cd and Pb accumulation rates. Modeling Cd and Pb accumulation rates indicated that the metals are accumulating in the agricultural lands in the studied townships. The largest Cd (18 g ha^-1 yr^-1) and Pb (260 g ha^-1 yr^-1) accumulation rates were found in the township of Isfahan but the minimum accumulation rates were found in township of Lenjan for Cd (3 g ha^-1 yr^-1) and Mobarakeh for Pb (10 g ha^-1 yr^-1). The major input route to agricultural soils is phosphate fertilizers for Cd but for Pb is manure on the regional scale. High application rates of sewage sludge and compost in agricultural lands in the township of Isfahan could result in considerable amounts of Cd and Pb entering the soils of this region.

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Sedimentation and consolidation of cohesive sediments near the dam body can cause many problems such as clogging the bottom outlets and entering the sediments into the hydropower intakes. Flushing of these sediments through the bottom outlet will be successful only if the hydraulic conditions are designed according to the physical and mechanical properties of consolidated sediments. During the past decades many researches have been conducted on the distribution of non cohesive sediments in the reservoir, yet little information is available for cohesive sediments. Therefore the main purpose of this study is to conduct a physical model study to investigate the process of sedimentation and consolidation of cohesive sediments in the dam reservoir. The experimental tests were conducted in a settling column test with a height of 3.8 m and diameter of 0.3m. The sediment samples were collected from the Dez dam reservoir since it is predicted that in less than 5 years the sediment will reach to such an elevation that can enter into the hydropower intakes. The obtained results show that there is a an algorithmic relationship between the time and changing of the sediment concentration during the sedimentation and self-weight consolidation processes. This process can be divided into four separate phases. It is also of note that in this paper the effective stress-void ratio and coefficient of permeability – void ratio relationship were obtained as a power relationship, which are in agreement with the results obtained by other investigators. These relationships can be used as primary data in the mathematical model of sedimentation and consolidation.

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The potential of artificial neural network models for simulating the hydrologic behaviour of catchments is presented in this paper. The main purpose is the modeling of river flow in a multi-gauging station catchment and real time prediction of peak flow downstream. The study area covers the Upper Derwent River catchment located in River Trent basin. The river flow has been predicted (at Whatstandwell gauging station) using upstream measured data. Three types of ANN were used for this application: Multi-layer perceptron, Recurrent and Time lag recurrent neural networks. Data with different lengths (1 month, 6 months and 3 years) have been used, and flow with 3, 6, 9 and 12 hours lead-time has been predicted. In general, although ANN shows a good capability to model river flow and predict downstream discharge by using only upstream flow data, however, the type of ANN as well as the characteristics of the training data was found as very important factors affecting the efficiency of the results.

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Optimal crop water requirement is needed for precise irrigation scheduling. Prediction of crop water requirements is a basic factor to achieve this goal. In this study, maize potential evapotranspiration (ET_p) was prediced by maize simulation model (MSM). Then, it was evaluated and validated using experimental field data obtained in Agricultural Research Station of Shiraz University (Bajghah, Fars province) during 2003 and 2004. Comparison of measured volumetric soil water content with predicted values by MSM model in 2003 and 2004 indicated that this subroutine (prediction of maize evapotranspiration) did not need modification. Also, daily potential evapotranspiration of maize was estimated by using Penman-Monteith equation considering single and dual crop coefficients. Comparison between the results of predicted ET_p by MSM model, calculated ET_p by Penman-Monteith, and measured irrigation water and soil water content indicated that the prediction of ET_p by MSM model was satisfactory. Model prediction of seasonal ET_p, potential transpiration (T_p) and soil evaporation (E) were 831, 536 and 329 mm, respectively, in 2003, and 832, 518 and 314 mm, respectively, in 2004. The values of ET_p, T_p and E calculated by Penman-Monteith method using dual crop coefficients were 693, 489 and 205 mm, respectively, in 2003, and 700, 487 and 213, respectively in 2004. Maximum rate of predicted potential ET_p, Tp and E were 11.1, 8.2 and 5.1 mm d^-1, respectively in 2003 and 13.0, 9.0 and 4.0 mm d^-1, respectively in 2004. The values of calculated seasonal ET_p by Penman-Monteith method using single crop coefficient were 615 and 632 mm in 2003, and 2004, respectively. Comparison between the results of predicted ET_p by MSM model, calculated ET_p by Penman-Monteith equation with single and dual crop coefficients (FAO-56) and measured values of irrigation water and soil water contents of root depth indicated that FAO-56 methods underestimated the ET_p.

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  Presence of genotype × environment interaction necessitates evaluation of genotypes in a wide range of environments to find desirable genotypes. This study was carried out to determine the stability and adaptability of grain yield of 17 chickpea genotypes, in RCBD with four replications at Kermanshah, Lorestan, Ilam, Gachsaran and Gorgan Research Stations during two seasons (2003-2004). The genotype × environment interaction effect analyzed using the additive main effects and multiplicative interaction (AMMI) statistical model was significant at 1% level of probability. The sum of squares of G × E interaction was partitioned by AMMI model into four significant interaction principal component axes (IPCA). The first four principal component axes (IPCA 1, 2, 3 and 4) cumulatively contributed to 94% of total genotype by environment interaction. A biplot generated using genotypic and environmental scores of the first two AMMI components also showed that genotypes FLIP 97- 79, X95TH1 and FLIP 97- 114 were selected as stable genotypes, among which the genotype FLIP 97- 114 was outstanding for high yield stability.

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  Continuous measurement of river discharge is a hard and expensive task in hydrology. To overcome this problem, the stage readings at hydrometric gauges are permanently taken and the discharge of any time at which the actual discharge is unavailable will be estimated through a relationship between discharge and stage. To study the stage-discharge relations and the capability of long-term data in establishing a permanent stage-discharge relationship, and also to determine the best time to measure the discharge of rivers, a study was conducted at the hydrometric station of the Zayandehrud regulatory dam using data from 1990 to 2003. The data were analyzed using simple regression analysis, the percentage of relative error and factor analysis. The results indicated that the best model to show the stage-discharge relation at the studied station is a power function model. Moreover, the model used for every year can only be used for that year. The results also showed that the most suitable times for the measurement of discharge are July, December and March.

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  In order to quantitatively evaluate the sediment yield in ungauged basins, it is necessary to use empirical models. The EPM model, as a model which is using in Iran, has sometimes been evaluated. Most evaluations have often been conducted by using river's sediment information and direct measurements of dam reservoir sedimentation have been less used, while the sediment measurement method on reservoir is more carefully. 9 small watersheds from Semnan province (Iran) were selected in this research. There is a small earth dam which have been built on the outlet of each watershed in the past years that them age is 10 years. These dams have not been weirs since they have been building to now. Therefore total of sediment yield volumes of each watershed are entrapped in the dam reservoirs. The volume of sediments deposited in reservoir were calculated by surveying. Sediment's apparent specific weights were measured in each reservoir and the volume of sediments transformed into sediments weight. By EPM model the volume and weight of sediment yield were estimated. Values of sediment yield measured in reservoirs were compared with estimated values by t-test. The results showed that at level 5%, there was not any significant difference between sediment yield values estimated in reservoirs by EPM model in comparison with values of volume and weight which were measured. But determination of performance and relative root mean square error showed that EPM model has low efficiency for estimation of sediment yield in the case study of watersheds.

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  Soil erosion is one of the most threatening issues for crop production and environmental qualities, especially for soil and water resources. Appropriate knowledge about total soil loss and runoff is valuable in order to perform soil and water conservation practices in watersheds. EUROSEM, "a single event, dynamic and distributed model," was developed to simulate soil loss, sediment transportation and deposition by rill and interrill processes. This study was conducted to evaluate EUROSEM model in order to simulate soil loss and runoff in Sulijan sub-basin, which covered 20 ha, from Charmah-Bakhtari province. The sub-basin was divided in to 19 homogeneous elements using topographic, land use, plant cover, slope and channel properties throughout it. Soil, plant cover, land surface and climate characteristics were measured and evaluated by field observations and laboratory measurements. Actual soil loss and runoff for studied events were determined by direct measurement in the field. After sensitivity analysis, calibration and validation steps were carried out to simulate runoff and soil loss. The results of sensitivity analysis showed that the EUROSEM model for predicting runoff was more sensitive to hydraulic conductivity, capillary drive and initial soil moisture. On the other hand the model for predicting soil loss was more sensitive to Manning's coefficient and soil cohesion. The results showed that the EUROSEM model was able to simulate well the total runoff, peak of runoff discharge, total soil loss and time for the peak of soil loss discharge. But that could not simulate well the peak of soil loss discharge and time for the peak of runoff. Although it seems that EUROSEM is able to predict soil loss and runoff partially well in individual events, it is necessary to evaluate the efficiency of the models for different basins with varieties of soil, plant cover and climatic properties.

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  Understanding nitrogen mineralization from different organic sources should be a key factor in developing efficient prediction of the need for nitrogen fertilization with minimal negative environmental impact. In order to investigate nitrogen mineralization rate in soils amended with compost, vermicompost and cattle manure, an experiment was done as factorial in a randomized complete block design in three replications. Four treatments (compost, vermicompost, cattle manure and soil alone), two temperature levels (8 and 25 ⁰C) and two moisture levels (50% and 85% FC) were used for the 90 - day incubation study. Ammonium and nitrate were measured by spectrophotometer method. Results indicated that the mixed first-and zero-order kinetics model is the best model for our data. Cattle manure treatment had the highest N_min at 25 ⁰C (87.78 mgN/kg equal to 14.54% N_total) and the least value (23.62 mgN/kg equal to 4.62% N_total) was obtained for the compost treatment at 8 ⁰C. N₀k (nitrogen availability index) for treatments was in the following order: Cattle manure>Vermicompost >Compost. With increasing the temperature and moisture, N mineralization increased. Also N_min positively correlated with N₀ (r =0.583*), and N₀k (r =0.834**).

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  Phytoremediation is a new technology that employs plants to remediate contaminated soils. This method compared to those that involve the use of large scale energy consuming equipments is an inexpensive method. Phytoremediation models are useful tools to further understanding the governing processes and also to manage the contaminated soils. A thorough literature review indicates that very few models have been developed for phytoremediation due to the complexity of the phenomena. The objective of this study was to develop a simple model for phytoremediation of lead and cadmium. A new formulation of phytoremediation was established based on soil and plant responses to heavy metal pollution. A large quantity of a sandy loam soil was thoroughly mixed to ensure homogeneous different concentration levels by lead and cadmium. These contaminated soils were transferred to some plastic pots. Land Cress (Barbarea verna) and Spinach (Spinacia oleracea L.) seeds were germinated in pots containing 8 kg of contaminated soil. Plants were harvested at five time intervals. The concentrations of Pb and Cd in the plant and soil samples were digested by wet oxidation and 4 M Nitric acid digestion methods, respectively, and were determined by flame and graphite furnace atomic absorption spectrometry methods. Proposed models then were calibrated using the collected data and validated quantitatively. The results indicated that the soil adsorption isotherms followed a linear form for both Pb and Cd concentrations. The results also indicated that the phytoremediation rate of Pb by Land Cress and Spinach are first-order function of Pb concentration in soil. In contrast, a zero-order function of soil Cd contaminations was obtained. Combining these two results of soil and plant responses to Pb and Cd pollution, a simple model with reasonable performance was derived to predict the time needed for remediation of soil Pb (R² > 0.98). However, in the case of Cd, the derived models appeared to be useful to make only some overall estimations of the remediation (R²≈^�0.70).

 

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Drought is an unavoidable natural disaster in dry and arid regions of the world. Studies indicate that Iran with its geographical and climatic characteristics is poor in water resources. Moreover, it is estimated that in 2025, Iran should increase the water resources by 112% in order to maintain status quo. Therefore, the occurrence of drought is more prevalent in the future. This implies a real challenge for researchers to study how to manage farms during the onset of drought. Inappropriate management strategies result in loss of resources, which in turn leads to more destructive impacts of drought, consequently leading to more droughts in future. The purpose of this survey study was to identify factors influencing drought management among farmers in Fars province, Iran. A multistage stratified random sampling technique was used to select a representative sample of farmers who has experienced drought in recent years. A total of 258 farmers were interviewed using a questionnaire. A panel of experts verified face validity. A pilot study was used to assess the reliability of the measuring instrument. Cluster analysis and Structural Equation Modeling were used for data analysis. Results indicated that farmers with different social, economical, and technical characteristics chose different management strategies when coping with drought conditions. Despite farmers' efforts to manage drought, they face harsh consequences. These consequences include economic losses and degradation of farming environment. It is therefore recommended that policy makers who are involved in drought management programs learn more about farmers' drought mitigation techniques and make further attempts to increase the efficiency and effectiveness of techniques used by farmers.

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Root depth is one of the main parameters affecting soil moisture availability held within the plant root zone. This study was conducted to evaluate the trend of corn root development during the growing season in different irrigation methods with two water qualities, and distribution of roots in soil profile. The experiment was a split plot design with three main treatments (subsurface drip(SSD), surface drip(SD) and furrow irrigation(FI)) and two sub main treatments (municipal effluent and fresh water) in two consecutive years conducted in Korbal plain, Fars province. Root monitoring was carried out with the observation of soil profile root depth measurement. Samples were taken during the growing season 16 times, each with a 7 day interval. Measurement of root weight in different soil layers was carried out using monoliths of soil washed with water pressure using 50 mesh sieves. Although the longest roots were observed in plots irrigated with SSD and the shortest in FI, the final root length was not significantly affected by irrigation methods and water qualities. In this research, a model showing the trend of root length average growth was developed and tested in the experiment conditions. The average final main root depth for all treatments was 77 cm. Irrigation volume using root depth monitoring could be reduced compared to linear model, Borg & Grimes and CROPWAT model for root depth estimation. Irrigation water on the base of soil moisture deficit within the root zone in each irrigation event could be reduced when the real root depth is considered compared with the conventional general models giving a final root depth. Results showed the total dry root weight in SSD was more than that in SD and FI methods. However, water quality did not show a significant effect on dry root weight. The most root concentration in SSD was measured in depth of 20-40 cm, while in SD and FI the most concentration was in surface layer (0-20 cm). In the SSD, the roots were distributed more evenly compared with SD and FI methods. The concentration of roots in all treatments below 65 cm was not significant.

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Canola (Brassica napus L.) in response to salinity represents various resistances with respect to its phonologic stages. Most plants such as Canola are resistant at germination stage. However, at seedling or earlier growth stages, plants become more sensitive to salinity but their tolerance increases with age. Salt tolerance of various plants has been extensively studied however, the results have either been qualitative or expressed as average values over root zone salinity for the whole growth season. Thus, developing appropriate models for quantitative characterization of plant response to salinity at different growth stages is essential. Canola which is considered as high economic value plant was selected for this study. Two productive stages for canola are recognized as flowering and ripening. To determine the effect of salinity on canola at vegetative growth stages, a greenhouse experiment was conducted on a natural saline loamy sand soil, using salinity treatment including one non-saline water (tap water) and 8 saline waters of 3 to 17 dS.m^-1. The canola plants were irrigated with tap water before the desired stage and then salinity treatments were imposed. The Maas and Hoffman (1977), van Genuchten and Hoffman (1984), Dirksen et al., (1993), and Homaee et al., (2002b) models were used to predict relative transpiration (T_a/T_p ) and relative yield ( Y/Y_m) as a function of soil salinity. The maximum error (ME), root mean square error (RMSE), coefficient of determination (CD), modeling efficiency (EF) and coefficient of residual mass (CRM) statistics were calculated to compare the models and their efficiencies. The results indicated that the van Genuchten and Hoffman (1984) model provides best prediction at flowering stage. However the Homaee et al. (2002b) model offers better prediction at ripening growth stage.