JWSS - Journal of Water and Soil Science

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The vast pastures and agricultural development plans for dry farming and irrigated farming in Khuzestan Province depend on rain. This requires availability of annual precipitation prediction models to be used in the management decision-making process. In this research, the long-term daily precipitation data from 15 rain gauge stations in the study area were collected for study and a relationship between the early fall season precipitations of 42.5 mm (t_42.5) and the annual precipitation was obtained. The results showed that the relationship was an inverse one such that the later the fall precipitation occurred, the greater the annual precipitation would be. To increase the coefficient of determination in the models, climatic variables such as Persian Gulf sea surface temperature and geographical characteristics (longitude, latitude, altitude, and long term mean annual precipitation) were used. Except for the long term mean annual precipitation and altitude, other variables did not increase the coefficient of determination. The final simple model found is as follows: P_a=184.787-1.891t_42.5+0.855P_m , R²=0.704 where, P_a is the annual precipitation, t_42.5 is the time from beginning of fall season for 42.5 mm of precipitation, and P_m is the long term mean annual precipitation.

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In this study, 14322 growth trait records of 2387 sheep bred and reared in the Rearing and Breeding Station of Bakhtiari Sheep during 1989-1997 were used to estimate the phenotypic, genetic, and environmental trends for some of the growth traits using Animal Model for lambs, rams, and ewes. The genetic trend of birth weight, weaning weight, six month's weight, daily gain from birth to weaning, daily gain from weaning to six month and daily gain from birth to six month were 12.2 (+2.9), 19.6 (+5.5), 28.7 (+8.7), .15(+0.04), 0.06 (+0.05) and 0.014 (+0.04) gr. for ewes as an indicator of genetic level of the herd respectively. Also, average of the genetic change rate per year for rams and lambs were calculated. Overall, the maximum progress rate was for six-month body weight (28.7 gr. per year) and the next was weaning weight (19.6 gr. per year). The results for lambs and rams also showed that these traits had the same rank for the genetic progress. The progress could be due to direct selection for these traits in the selection index criterion although there were negative phenotypic and environmental trends during the study years. Negative phenotypic and environmental trends could be due to bad environmental conditions, especially to nutrition of the sheep in an unsuitable (drought) climate during the study years. .

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In this study, the simulation of the BORKHAR plain aquifer located in north-east of Isfahan was done for the estimation of the hydrodynamic coefficients and for the preparation of the prediction and management model with the purpose of the study of the water table surface situation in the next years. The study of the geological situation of the plain and the report of the drilling of its exiting wells indicated that the BORKHAR plain has two kinds of aquifer: confined and unconfined. According to the field data related to the unconfined aquifer, a part of this aquifer was selected for the mathematical simulation. The calibration model for the estimation of the K and Sy. coefficients was done by dividing the plain into four geohydrologic units and by using the PEST, a module of the MODFLOW model. The situation of the water table level during 1380-1390 was studied according to the different management options by the calibration model. If the trend of the exploitation doesn’t change during the next ten years, we will confront with a maximum drop of 48 meters. As a practical way for preventing from this drop, it was suggested that the exploitation management reduce the 30 percent of the demand. One of the most important result of this will be the 26 percent reduction of the drop. By developing an optimization model and by imposing the necessary constraints on the critical regions, and transferring water from other parts, it seems that the trend of the drop will be controllable at a admissible level (less than 10 meters until 1390). Using the optimization model will make a change in the increasing trend of the drop and an improvement in the situation of the aquifer.

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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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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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  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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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.

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Variable rate technology-spraying technologies are new aspect of sustainable agriculture. In these technologies, the chemical is applied in the needed level of farm where there is a high intensity of pests and weeds. The purpose of this paper was to study the agricultural specialists' attitude toward and intention to use variable rate technology-spraying technologies in Jihad-e-Keshavarzi organization of Fars and Khuzestan provinces. A survey was conducted using a stratified random sampling to collect data from 249 agricultural specialists. The results showed that the specialists of Fars and Khuzestan provinces have intentions to use the variable rate technology-spraying technologies. The variables including attitude toward application, trialing, perceived usefulness, compatibility, and attitude of confidence all influence the intentions to use the variable rate technology-spraying technologies. Based on high positive intention of agricultural specialists, we recommend the use of these technologies in agricultural practices of the two provinces.

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Physicochemical characteristics of soil, land cover/use and human activities have effects on heavy metals distribution. In this study, we applied Classification and Regression Tree model (CART) to predict the spatial distribution of zinc in surface soil of Hamadan province under Geographic Information System environment. Two approaches were used to build the model. In the first approach, 10% of total data were randomly selected as test data and residual data were used for building model. In the second approach, all data were used to build and evaluate the CART model. Determination coefficient (R2) and Mean Square Error (MSE) were applied to estimate the accuracy of model. Final model included 51 nodes and 26 terminal nodes (leaf). Calcium carbonate, slope, sand, silt and land use/cover were determined by the CART model to predict spatial distribution of Zn as the most important independent variables. The regions of western Hamadan province had the highest concentration of Zn whereas the lowest concentration of Zn occurred in the regions of northern Hamadan province. The results indicate good accuracy of CART model using R2 and MSE indices.

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Water Uptake by the root under salinity and water Stress in unsaturated soils was investigated through mathematical equations in three Groups of additive, multiplicative and non-consumptive. This study was an effort to assess six water uptake functions of van Genuchten (additive and multiplicative), Dirksen et al., Van Dam et al, Skaggs et al, and Homaee, for Rasht Hashemi rice under salinity and water stress conditions. Based on field observations of Hashemi Rasht rice in 1386 and 1389, crop growth simulation model of SWAP was calibrated and validated with a correlation coefficient of 0.97 and 0.95, respectively. Water Uptake Reduction Models' parameters were determined by the simulated data using SAS statistical software. Results showed that for the anticipated reduction of Water Uptake in rice water and salinity stress conditions for Rasht Hashemi rice, Homaee model is best.

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The SIMDualKc model is an irrigation scheduling simulation model that uses dual crop coefficient method for estimating ETc by computing two separate soil water balances in daily time-step, one for the soil evaporation layer from which Ke is computed, and the other one for the entire root zone to compute the actual Kcb adjusted to the soil moisture conditions. In this study, lysimetric measurements of evapotranspiration rates relative to (Coriandrum sativum L.) during 2 years were used for model calibration and validation. Kcb values for coriandrum were found as 0.21 for the initial, 1.12 for the mid-season and 0.79 at harvesting period. Model results have shown a good agreement between the actual daily evapotranspiration predicted by the model and the ones resulting in water balance calculation on drainable lysimeters, and root mean square errors of estimates (RMSE) of about 1.64 mm and 1.53 mm for the calibration and validation, respectively.The modeling efficiency EF and the index of agreement dIA were equal to 0.8 and 0.93, respectively, thus indicating good performance of modeling with SIMDualKc. Model estimates of evaporation (E) for validation and calibration years displayed an average of 181 mm, representing 25% of ETc. In conclusion, results show that the model is appropriate to simulate the daily evapotranspiration adopting the dual Kc approach for coriandrum in west regions of Iran.

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The Palmer Drought Severity Index (PDSI), which uses hydrometeorological variables to solve a simple water balance equation in the soil and considers the drought or wet conditions as dynamic phenomena, is used for the assessment of drought conditions in many parts of the world. The main goal of this study was to assess the PDSI based on its original assumptions, its regionalized status, using the outputs of already calibrated and validated SWAT model in central regions of Iran. The PDSI was assessed through five methods: 1) original Palmer Index without calibration in which the climate coefficients and the severity equation were derived for Kansas and central Iowa 2) original Palmer Index in which the coefficients of severity equations were adjusted 3) the Palmer Index with the calibration of equations in central areas of Iran 4) the Palmer Index using the soil moisture and potential evapotranspiration from SWAT model and 5) the Palmer Index using the soil moisture, potential evapotranspiration and runoff from SWAT model. The evaluation was conducted for 17 major basins covering the entire country with a monthly time step for the period 1990-2002. Then, using all five methods, the severity of the drought for 160 sub basins located in central Iran was calculated and evaluated. The results of this study indicated that method 4 provides more acceptable results. Also, the results of this research showed these methods clearly demonstrated (1992) as the wettest year and (2001) as the driest year. The approach used in this study is applicable to regional calibration of Palmer Index and the outputs of other hydrological models.

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Typical routine surveys of soils are relatively expensive in terms of time and cost and due to the fact that maps have been traditionally developed and considering their dependence on experts' opinions, updating maps is time consuming and sometimes not economical as well. While soil digital mapping, using soil various models - the Landscape, leads to simplification of the complexity found in natural soil systems and provides users with quick and inexpensive updates. In fact, the model represents a simplified form of the complex relationships between the soil and the land. This study aims to consider inferential model Soil-Land (SOLIM) in mapping and estimating soil classes in Aran area, Isfahan province. For this purpose, the SOLIM model inputs are digital geological and environmental layers of digital elevation model (DEM) including elevation, slope in percent, slop direction, curvature of the earth's surface, wetness indicator, flow direction, flow accumulation, and satellite images of Landsat 8. The seven subcategory of soil in the study area are input data of SOLIM model. Then fuzzy maps were prepared for seven types of soil and final maps of soil prediction were created by non-fuzzy action. Results showed that the SOLIM using environment variables has very high ability to separate soil types in greater detail and soils with different parent materials, geology, climate and vegetation can be separated from each other by this model with a high degree of accuracy. Comparing error matrix shows that the overall accuracy of the map derived from the model SOLIM is 92.36%.
 

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