نشریه آب و خاک
سال سی‌ام شماره 3 (پیاپی 47، امرداد و شهریور 1395)

One of the practical and classic problems in the water resource studies is estimation of the optimal reservoir capacity to satisfy demands. However, full supplying demands for total periods need a very high dam to supply demands during severe drought conditions. That means a major part of reservoir capacity and costs is only usable for a short period of the reservoir lifetime, which would be unjustified in economic analysis. Thus, in the proposed method and model, the full meeting demand is only possible for a percent time of the statistical period that is according to reliability constraint. In the general methods, although this concept apparently seems simple, there is a necessity to add binary variables for meeting or not meeting demands in the linear programming model structures. Thus, with many binary variables, solving the problem will be time consuming and difficult. Another way to solve the problem is the application of the yield model. This model includes some simpler assumptions and that is so difficult to consider details of the water resource system. The applicationof evolutionary algorithms, for the problems have many constraints, is also very complicated. Therefore, this study pursues another solution.
In this study, for development and improvement the usual methods, instead of mix integer linear programming (MILP) and the above methods, a simulation model including flow network linear programming is used coupled with an interface manual code in Matlab to account the reliability based on output file of the simulation model. The acre reservoir simulation program (ARSP) has been utilized as a simulation model. A major advantage of the ARSP is its inherent flexibility in defining the operating policies through a penalty structure specified by the user. The ARSP utilizes network flow optimization techniques to handle a subset of general linear programming (LP) problems for individual time intervals. The objective of the LP application is to minimize a cost function, which reflects relative benefits derived from a particular operating policy. In this model, the priority for supplying different demands is defined based on a penalty structure. In this approach, the original system elements are delineated by nodes and arcs. Accordingly, nodes are junction points and arcs are the basic elements used to represent channels, and reservoir storages for each time interval. There are arcs connecting reservoir and demand nodes to the source and sink node. The source node supplies water to nodes within the network to simulate local inflow and the sink node receives flow from nodes within the network to represent consumptive use. Application of the simulation model causes that the configuration of the water resource system with more details is investigated. In this research, tree alternative for reliability including 80, 85 and 90 percent were considered, which are usual reliability for satisfying demands in water resource management in Iran. Then, for the each reliability, optimal reservoir volume was calculated along with optimal flow in each arc. The inflow to the model is established based on a long-term period of historical data (48 years) with monthly time interval.
Results Evaluation of the alternative, defined for reliability, demonstrated if the reliability increases from 85 to 90 %, the incremental volume of the reservoir will be considerable. In fact, for a higher reliability the model must supply water for a more severe drought. However, for the reliability from 80 to 85% the required incremental volume is negligible. Thus, selecting the reliability of 85% is more justified, by which the optimal reservoir volume will be 4.6 million cubic meters. Additionally, increasing of the reliability resulted in decreasing in average deficit and modified shortage index (MSI). However, these two deficit indexes have no same descending trend. The MSI has a less variations versus the reliability that is due to use square deficit in its formulation.
The model used in this research, in comparison to the MILP that is a common method for solving the above problem, make a reform in the traditional mass balance and flow routing in the network. The results show the reservoir capacity sensitivity versus the reliability, in which the sensitivity amount is affected by the intensity and duration drought periods. In fact, with considering higher reliability for supplying demands, a variation of the required reservoir volume has an ascending trend. Thus, application of predefined reliability, that is a common method in designing reservoir volume in Iran, is not appropriate for all drought conditions. In this regard, a sensitivity analysis of reservoir volume versus the reliability accompanying an economical analysis is recommended.

Flood routing is a procedure to calculate flood stage and water depth along a river or to estimate flood hydrograph at river downstream or at reservoir outlets using the upstream hydrography . In river basins, excess rainfall is routed to the basin outlet using flow routing techniques to generate flow hydrograph.
A GIS-based distributed hydrological model, Wet Spa, has been under development suitable for flood prediction and watershed management on a catchment scale. The model predicts outflow hydrographs at the basin outlet or at any converging point in the watershed, and it does so in a user-specified time step. The model is physically based, spatially distributed and time-continuous, and simulates hydrological processes of precipitation, snowmelt, interception, depression, surface runoff, infiltration, evapotranspiration, percolation, interflow, groundwater flow, etc. continuously both in time and space, for which the water and energy balance are maintained on each raster cell. Surface runoff is produced using a modified coefficient method based on the cellular characteristics of slope, land use, and soil type, and allowed to vary with soil moisture, rainfall intensity and storm duration. Interflow is computed based on the Darcy’s law and the kinematic approximation as a function of the effective hydraulic conductivity and the hydraulic gradient, while groundwater flow is estimated with a linear reservoir method on a small subcatchment scale as a function of groundwater storage and a recession coefficient. Special emphasis is given to the overland flow and channel flow routing using the method of linear diffusive wave approximation, which is capable to predict flow discharge at any converging point downstream by a unit response function. The model accounts for spatially distributed hydrological and geophysical characteristics of the catchment.
Determination of the river flow hydrograph is a main target in hydrology. Hydrological modeling deals with calculation of watershed hydrograph using hydro-meteorological information and terrain data, and processes of transforming rainfall into a flood hydrograph and the translation of hydrographs throughout a watershed. Flow routing subjects hydrography transformation and translation throughout a river basin. The Wet Spa model used in this study is a simple grid-based distributed runoff and water balance simulation model that runs on an hourly time step. It predicts hourly overland flow occurring at any point in a watershed, hydrography at the outlet, and provides spatially distributed hydrologic characteristics in the basin, in which all hydrologic processes are simulated within a GIS framework (Bahremand, 2007). The Wet Spa model was originally developed by Wang et al. (1997) and adapted for flood prediction by De Smedt et al. (2000) and Liu et al. (2003).
The outlet is accomplished using the first passage time response function based on the mean and variance of the flow time distribution, which is derived from the advection–dispersion transport equation. The flow velocity is location dependent and calculated in each cell by the Manning equation based on the local slope, roughness coefficient and hydraulic radius. The hydraulic radius is determined according to the geophysical properties of the catchment and the flood frequency. The total direct runoff at the basin outlet is obtained by superimposing all contributions from every grid cell.
The routing of overland flow and channel flow is implemented by the method of the diffusive wave approximation. This method has been used in some recent GIS-based flood models (Fortin et al., 2001; Olivera and Maidment, 1999). Liu et al 2003 has presented the flow routing method of the WetSpa model in detail. A two-parameter response function, based on the average flow time and the standard deviation of the flow time, is proposed in this study. The flow time and its variance are determined by the local slope, surface roughness and the hydraulic radius for each grid cell. The flow path response function at the outlet of the catchment or any other downstream convergence point is calculated by convoluting the responses of all cells located within the drainage area in the form of the probability density function (PDF) of the first passage time distribution. This routing response serves as an instantaneous unit hydrograph and the total discharge is obtained by a convolution integral of the flow response from all generated spatially distributed runoff.
Starting from the continuity equation and the St.Venant momentum equation, assuming the one-dimensional unsteady flow, and neglecting the inertial terms and the lateral inflow to the flow element, the flow process can be modeled by the diffusive wave equation (Cunge et al., 1980)
In this study, flood routing is done as the main part of flow simulation of the distributed hydrological Wet Spa model in the Ziarat watershed. In order to execute the model, hourly hydrometeorological data for a period of four years (2007-2010) including rainfall, evapotranspiration, temperature, and discharge are used as inputs. Additionally, three main maps of the digital elevation model, soil map (texture), and land use are also applied and converted to digital formats. The result of the simulation shows a good agreement between the simulated hydrography and the observed one. The routing of overland flow and channel flow is implemented by the method of the diffusive wave approximation.
Results and Disscasion: The Wet Spa model has been applied in several studies, e.g. the Barebeek catchment in Belgium, the Alzette river basin in Luxembourg, the Hornad watershed in Slovakia, In this study, flood routing is done as the main part of flow simulation of the distributed hydrological WetSpa model in the Ziarat watershed. In order to execute the model, hourly hydrometeorological data for a period of four years (2007-2010) including rainfall, evapotranspiration, temperature, and discharge are used as inputs. Additionally, three main maps of the digital elevation model, soil map (texture), and landuse are also applied and converted to digital formats. The result of the simulation shows a good agreement between the simulated hydrography and the observed one. The routing of overland flow and channel flow is implemented by the method of the diffusive wave approximation. A sensitivity test shows that the parameter of flood frequency and the channel roughness coefficient have a large influence on the outflow hydrography and the calculated watershed unit hydrograph, while the threshold of minimum slope and the threshold of drainage area in delineating channel networks have a marginal effect.

The maximum water efficiency and water productivity of the agricultural sector is one of the most important and effective ways to deal with the water crisis and mitigate the effects of drought. Therefore, scientific and practical agricultural water productivity in terms of planning and development must be followed. Local or drip irrigation systems supply some of the moist around the roots and the plant uses the moisture in the soil. Irrigation systems and irrigation scheduling affect water uptake by plants.
Matrials and In order to evaluate the effect of irrigation on the yield of 4-year-old pomegranate trees with local irrigation system (Bubbler) in sandy loam soil with bulk density 1.15 grams per cubic centimeter a research was performed in Agriculture and Natural Resources Research Center of Yazd province with an altitude of 1230 meters . The region has an arid climate with 51 mm average annual rainfall and average annual temperature of 20 ° C, which is located 10 kilometers from the center of the city of Yazd. This project was designed in a factorial experiment with a randomized complete block with three irrigation regimes I1, I2, I3, including irrigation (FC100%), 25% of deficit irrigation (FC75%) and 50 percent deficit irrigation (FC50%) on two commercial cultivars of pomegranates, which have been growing at 3 × 4 with three replications. To prevent penetration of water per tree, plots adjacent to each block strip (three meters between rows and between plants within one and a half meters without irrigation tape) were used as a guard. Trees around the pool shaped a rectangular building with a flow rate of 96 liters per hour for each tree using Bubbler system. The use of such a system with high flow rate, suitability and cost of such a system in orchards and vineyards, water supply reduces energy consumption in a tree in a short time. To prevent clogging of the filter, disc dropper was used at the beginning of the project. At the beginning of each block a flow meter was installed to measure the amount of water distribution. All the operations, including pruning and combat weeds, fertilizing, leaching requirement, according to the research center for all three irrigation regimes in the garden was the same as usual conditions. Due to the salinity of irrigation water and soil salinity testing during the growing season only once and 25 percent, respectively water and soil physical and chemical properties of the test was run.
Analysis of variance and comparison of performance for the three treatments was shown in table (number of the table). In calculating the yield, weight per hectare garden products were considered. Analysis of variance showed that the yield of the different treatments in the water by five percent (p

Evapotranspiration (ET) is one of the key parameters in water resource planning and design of irrigation systems. ET could have spatial variations in a plain due to the diversity of plant species and spatial variability of meteorological parameters. Common methods of ET measurement are mostly point based and generalization of their results to the regional level are costly, time consuming and difficult. During the last three decades, several algorithms have been developed to estimate regional ET based on remote sensing techniques. Verstraeten et al. (2008) classified remote sensing-based methods for ET estimation into four categories i) methods based on the surface energy balance, ii) Penman-Monteith equation, iii) water balance and iv) the relationship between surface temperature and vegetation indices. SEBS (Surface Energy Balance System), SEBAL, METRIC and SEBI are examples of the algorithms which is developed based on the surface energy balance approach. SEBS is developed by Su (2002) and has been evaluated by several researchers. However this algorithm has been examined in the several studies in the world,it has been used rarely in Iran. The aim of the current study was to assess the results of SEBS algorithm in Mahidasht, Kermanshah, Iran. The study area is located at the latitude of 34º 5' – 34º 32' N and longitude of 46º 31' - 47º 06' E.
A brief description of the SEBS algorithm (in Persian) as well as its procedure to calculate ET based on Landsat images were presented in this paper. All equations of the algorithm were coded in the ERDAS Imagine package software using model maker tools. Actual ET over the study area was estimated using SEBS algorithm during the growth period of grain maize in the year 2010. For this purpose, available LANDSAT TM satellite images during the growing season of maize in 2010 (25 June, 11 July, 27 July and 12 August) were downloaded free of charge from the http://glovis.usgs.gov website (last visited: 26 November 2015).
A Lysimetric study was carried out to obtain reliable amounts of ET to assess the accuracy of calculating actual ET by SEBS algorithm. Because of the absence of the weighing Lysimeters in the study area, Drainable Lysimeter was used. Since the maize was the major crop in the study area, 10 ha maize was planted on 15 May 2010 at the research farm of the Mahidasht agricultural research station. At the same time, maize was cultivated in the Drainable Lysimeter (1m*1.5m*1.5m) which was located almost in the middle of the research farm. Actual ET of maize was calculated with the Lysimeter for each irrigation interval (10 days) based on water balance equation.
The Results of the SEBS algorithm were evaluated on two levels (farm and regional). At the farm level, average of calculating ET at the pixels of research farm was compared with the average of measured ET at the Lysimeter. The absolute and relative differences between the calculated and measured values of ET was used to describe the accuracy of the algorithm. Due to the absence of regional ET measurement, maximum ET estimated by the SEBS algorithm in the plain was compared with the calculated potential crop reference evapotranspiration (ETO). ETO was calculated using the Penman - Monteith formula based on daily weather data obtained from Mahidasht weather station.
Results indicated that an average of ET in the study area increased from June to August which coincides with increasing air temperature and vegetation density in the irrigated fields of the study area. The highest and lowest values of actual ET over the study area were determined in the irrigated farms and mountainous area, respectively. The results of Lysimetric study indicated that daily actual ET of maize on 25 June, 11 July, 27 July and 12 August was 4.13, 7.74, 7.45 and 8.05 mm.day-1, respectively. The value of ET estimated by SEBS algorithm was less than actual measured ET by Lysimeter for the all mentioned dates. The maximum absolute difference between estimated ET by SEBS and measured ET with the Lysimeter was occurred on 27 July with the amount 0.34 mm.day-1. Considering the maximum relative difference of 4.56 % between calculated and measured ET, it could be concluded that estimated ET by SEBS algorithm can be acceptable.
Due to the absence of ground-based measurements of evapotranspiration at the regional level, the maximum amount of ET estimated by SEBS algorithm was compared with ETO. The highest and lowest ratio of maximum ET over ETO were calculated as 1.02 and 1.22 which are acceptable values for the crop coefficient (Kc) in the studied period. The maximum difference between estimated ET by SEBS algorithm with ETO was 1.53 mm.day-1 which is equal to 21.86% of ETO in the same date (12 August).
The results of the current study showed that the SEBS algorithm can estimate the actual ET of maize with the acceptable accuracy in the Mahidasht. In the absence of measured ET data at the regional level, it was difficult to have a reasonable judgment on the accuracy of the estimated values of ET by SEBS algorithm at this scale. It is recommended to do the same study on other remote sensing-based approaches of ET estimation.

Potato is one of the main products of agriculture in feeding the world's population and agricultural economy. The production of potato in the world occupies the forth place after wheat, rice and corn. In Iran, annual production of more than 5.5 million tons potato, has made this crop the most important food after wheat. On the other hand, in arid and semi-arid regions, water is the most important limiting factor for production of agricultural crops such as potato. Considering the water use efficiency is one of the most effective ways to deal with the water crisis and increasing the quality and quantity of agricultural productions. Production increasing per unit of water consumed (increasing water productivity) by improving the selection of plant varieties, irrigation management and use of new irrigation methods may be feasible.
Material and The research was performed in the Chahartakhteh research station (32° 18' N. and 50° 55' E.) with 2090 m height above sea level and semi-humid climate with moderate summers and cold winters. Average annual rainfall is about 320 mm mostly during winter. The soil moisture and temperature regimes are Typic Xeric and Mesic, respectively. Soil texture is silty clay.
In order to determine the best method of deficit irrigation for optimizing water use efficiency and yield of two potato cultivars, an experiment was performed in Agricultural and Natural Resources Research Center of Chaharmahal va Bakhtiari farm in 2013. The experiment was based on randomized completely blocks with split - split plot design in three replications. The furrow and tape drip irrigation methods were as the main plots, two potato cultivars as sub plot units and four deficit irrigation managements as the secondary sub plot units including CI(100%), RDI80(80%), RDI65(65%) of available water depletion (AWD) and partial root-zone drying (PRD) during full growth period.
Almera and Burren cultivars are two new cultivars of high yield and quality of early growth period of approximately 90-80 days, high compatibility with Chaharmahal va Bakhtiari climate and more regions of Iran.
Analysis of variance (ANOVA) of studied factors showed that the deficit irrigation management on tuber yield (ton/ha), tuber yield per plant, the amount of starch, soluble sugar, proline, chlorophyll, water use efficiency, and water productivity were significant (P≤0.01). Effects of cultivar on tuber total yield, tuber yield per plant, soluble sugar, water use efficiency, and water productivity were significant (P≤0.01). The interaction between cultivar and deficit irrigation management was only significant (P≤0.05) on tuber yield (ton/ha), proline, water use efficiency and water productivity.
The results showed that Burren cultivar in comparison with Almera was better in tuber yield (19%), water productivity (20%), water use efficiency (19%), and resistance of draught in all deficit irrigation treatments. Maximum tuber yield (59.02 ton/ha) was obtained in Burren cultivar under complete irrigation. Minimum tuber yield (23.1 ton/ha) was obtained in Almera cultivar under deficit irrigation management RDI65 (65% of available water depletion). The maximum water use efficiency (16.79 Kg/m3) and water productivity (14.78 Kg/m3) were obtained under tape irrigation and partial root-zone drying (PRD) treatment. The minimum water use efficiency (7.46 Kg/m3) and water productivity (4.81 Kg/m3) were obtained under furrow irrigation and deficit irrigation management RDI65.
Effect of cultivar was not significant on amount of irrigation water during the growing season. The amount of irrigation water for two cultivars was the same and 4711 m3.ha-1. The amount of irrigation water in the different deficit irrigation managements showed that the highest water use was in CI (5615 m3 ha-1) and lowest water use was in deficit irrigation management RDI65 (4065 m3 ha-1) treatments.
Deficit irrigation management RDI80 ¡PRD and RDI65 in comparison with CI led to reduction of irrigation water amount 16, 21 and 28% of irrigation water amount.
Due to the results of this study, the high consumption of water in agriculture, for optimal use of available water resources, the methods with high water use efficiency and productivity, such as tape irrigation, the PRD irrigation management and the use of drought resistant cultivars is recommended. According to the limitation of water resources, for optimizing water use, the best suggestion for reducing water use on potato, is using Burren cultivar with suitable quality and high yield potential, and deficit irrigation management (PRD).

Saturated hydraulic conductivity and the other hydraulic properties of soils are essential vital soil attributes that play role in the modeling of hydrological phenomena, designing irrigation-drainage systems, transportation of salts and chemical and biological pollutants within the soil. Measurement of these hydraulic properties needs some special instruments, expert technician, and are time consuming and expensive and due to their high temporal and spatial variability, a large number of measurements are needed. Nowadays, prediction of these attributes using the readily available soil data using pedotransfer functions or using the limited measurement with applying the geostatistical approaches has been receiving high attention. The study aimed to determine the spatial variability and prediction of saturated (Ks) and near saturated (Kfs) hydraulic conductivity, the power of Gardner equation (α), sorptivity (S), hydraulic diffusivity (D) and matric flux potential (Фm) of a calcareous soil.
Material and The study was carried out on the soil series of Daneshkadeh located in the Bajgah Agricultural Experimental Station of Agricultural College, Shiraz University, Shiraz, Iran (1852 m above the mean sea level). This soil series with about 745 ha is a deep yellowish brow calcareous soil with textural classes of loam to clay. In the studied soil series 50 sampling locations with the sampling distances of 16, 8 , and 4 m were selected on the relatively regular sampling design. The saturated hydraulic conductivity (Ks), near saturated hydraulic conductivity (Kfs), the power of Gardner equation (α), sorptivity (S), hydraulic diffusivity (D) and matric flux potential (Фm) of the aforementioned sampling locations was determined using the Single Ring and Droplet methods. After, initial statistical processing, including a normality test of data, trend and stationary analysis of data, the semivariograms of each studied hydraulic attributes were calculated in various directions and their surface semivariograms were also prepared to determine the isotropic or anisotropic behavior of each studied soil attributes. Since all of studied soil hydraulic attributes were isotropic variables, therefore, the omnidirectional semivariograms were calculated and different theoretical models were fitted to them. The best fitted semivariogram models were determined using the determination coefficient, R2, and the residual sum of the square, RSS. The parameters of the best fitted models to the experimental semivariograms were also determined. The prediction of study hydraulic attributes was carried out using the parameters of semivariogram models by applying the ordinary Kriging approach. Predictions were also carried out using the Inverse Distance Weighing approach. The results of predictions were compared to each other using the Jackknifing evaluation approach and the suitable prediction method was determined and zoning was performed using the results of introducing prediction method. All of the semivariogram calculations and modeling, prediction of zoning of study hydraulic attributes were performed using the GS 5.1 software packages.
Results indicated that all of the studied soil hydraulic attributes belonged to the weak to moderated spatial correlation classes and the spherical model was the best fitted model for their semivariograms (except for Kfs and D that their best semivariogram models were exponential). The sill of all semivariograms ranged between 0.0003 to 0.419 for the S and Kfs, respectively. The nugget effects and the Range parameter of all semivariograms were located between 0.00015 to 0.108 for the S and Фm, and 211 to 6.4 m for Ks and D, respectively. Results also indicated that 3.5 and 50% of total variation of D and Ks was spatially structured and the other was random, respectively. The spatial correlation classes of near saturated soil hydraulic conductivity and soil hydraulic diffusivity were week, whereas, the spatial correlation classes of the other studied soil hydraulic attributes were moderate. Results revealed that the Inverse Distance Weighting method was the most suitable approach for the prediction of all studied soil hydraulic attributes in the present study. Comparison of the calculated statistical evaluation measures (i.e. Determination coefficient, R2, Mean residual error, MRE, mean square error, MSE, Normalized mean square error, NRMSE and geometric mean error ratio, GMER) and the final determined order of precision showed that the most and the least accurate predictions were obtained for Ks and Фm, respectively.
It is suggested in the cases that we need to map the hydraulic attributes or need their quantities in a large number; geostatistical prediction be performed using the limited measurements to reduce the needed time and costs.

Surface water bodies are the most easily available water resources. Increase use and waste water withdrawal of surface water causes drastic changes in surface water quality. Water quality, importance as the most vulnerable and important water supply resources is absolutely clear. Unfortunately, in the recent years because of city population increase, economical improvement, and industrial product increase, entry of pollutants to water bodies has been increased. According to that water quality parameters express physical, chemical, and biological water features. So the importance of water quality monitoring is necessary more than before. Each of various uses of water, such as agriculture, drinking, industry, and aquaculture needs the water with a special quality. In the other hand, the exact estimation of concentration of water quality parameter is significant.
Material and In this research, first two input variable models as selection methods (namely, correlation coefficient and principal component analysis) were applied to select the model inputs. Data processing is consisting of three steps, (1) data considering, (2) identification of input data which have efficient on output data, and (3) selecting the training and testing data. Genetic Algorithm-Least Square Support Vector Regression (GA-LSSVR) algorithm were developed to model the water quality parameters. In the LSSVR method is assumed that the relationship between input and output variables is nonlinear, but by using a nonlinear mapping relation can create a space which is named feature space in which relationship between input and output variables is defined linear. The developed algorithm is able to gain maximize the accuracy of the LSSVR method with auto LSSVR parameters. Genetic algorithm (GA) is one of evolutionary algorithm which automatically can find the optimum coefficient of Least Square Support Vector Regression (LSSVR). The GA-LSSVR algorithm was employed to model water quality parameters such as Na, K, Mg2, So42-, Cl-, pH, Electric conductivity (EC) and total dissolved solids (TDS) in the Sefidrood River. For comparison the selected input variable methods coefficient of determination (R2), root mean square error (RMSE), and Nash-Sutcliff (NS) are applied.
According to Table 5, the results of the GA-LSSVR algorithm by using correlation coefficient and PCA methods approximately show similar results. About pH, EC, and TDS quality parameters, the results of PCA method have, the more accuracy, but the difference of RMSE between the PCA method and correlation coefficient method is not significant. The PCA method cause improvement in NS values to 22 and 0.1 percentages in pH and TDS water quality parameters to the correlation coefficient method, respectively,and NS criteria value for EC water quality parameter did not change in both methods. As a result, according to positive values of NS criteria in both PCA and correlation methods, it is clear that GA-LSSVR has a high ability for modeling of water quality parameters. Because of summation of NS criteria for PCA method is 5.53 and for correlation coefficient is 5.62, we can say that the correlation coefficient method has more applicable as a data processing method, but both methods have a high ability. Orouji et all. (18) used assumed models to model Na, K, Mg2, So42- , Cl- , pH, EC, and TDS by Genetic programming (GP) method. The RMSE criteria of the better models for testing data are 2.1, 0.02, 0.85, 0.93, 2.18, 0.33, 404.15, and 246.15, respectively. For comparison the orouji et al. (18) and table (5), the Results show using the correlation coefficient method as a data processing method can improve the results to 5.5 times. The results indicate the superiority of developingalgorithm increases the modeling accuracy. It is worth mentioning that according to NS criteria both selected inputs variable methods (correlation coefficient and PCA) are capable to model the water quality parameters. Also the result shows that using correlation coefficient method lead to more accurate results than PCA.
In this study, GA algorithm as one of the most applicable optimization algorithms in the different sciences was used to optimize the LSSVR coefficients and Then GA-LSSVR was developed to model the water quality parameters. To comparison data processing methods (correlation coefficient and PCA methods), the input variables of both methods were determined and GA-LSSVR was performed for each of the input variables. To compare the results of the PCA and correlation coefficient methods, some statistics were used. It is worth mentioning that according to NS criteria both input selection methods are capable to model water quality parameters. Also the results show that using correlation coefficient method lead to more accurate results than PCA.

The increasing Greenhouse Gases in atmosphere is the main cause of climate and ecosystems changes. The most important greenhouse gas is CO2 that causes global warming or the greenhouse effect. One of the known solutions that reduces atmospheric carbon and helps to improve the situation, is carbon sequestration in vegetation cover and soil. Carbon sequestration refers to the change in atmospheric CO2 into organic carbon compounds by plants and capture it for a certain time . However, the ecosystems with different vegetation have Impressive Influence on soil carbon sequestration (SCS). Soil as the main component of these ecosystems is a world-wide indicator which has been known to play an important role in global balance of carbon sequestration. Furthermore, carbon sequestration can be a standard world trade and becomes guaranteed. Costs of transfer of CO2 (carbon transfer From the atmosphere into the soil) based on the negative effects of increased CO2 on Weather is always increasing, This issue can be faced by developing countries to create a new industry, especially when conservation and restoration of rangeland to follow. This research was regarded due to estimation of SCS in three land use types (orchard, paddy rice and forest) in a Part of Ramsar Lands, Northern Iran.
Ramsar city with an area of about 729/7 km2 is located in the western part of Mazandaran province. Its height above sea level is 20 meters. Ramsar city is situated in a temperate and humid climate. Land area covered by forest, orchard and paddy rice. After field inspection of the area, detailed topographic maps of the specified zone on the study were also tested. In each of the three land types, 500 hectares in the every growing and totally 1,500 hectares as study area were selected .For evaluation the sequestration of carbon in different vegetation systems,15 soil profile selected and sampling from depth of 0 to 100 centimetres of each profile was done by collecting 15 samples with the total number of 45 samples. Soil sampling (at the 0-100 cm depth) was carried out following determination of points on map. Some of soil features (i.e., Soil structure, Bulk density ,Texture, Acidity, CEC, total Nitrogen and Organic Carbon) were measured in the laboratory. Then, the ANOVA and Duncan tests were employed due to statistical analysis using of SPSS software package. Also The map of carbon sequestration was prepared using of GIS approach.
According to obtained results, the amounts of SCS were imposed by different land uses as non-significant. The amounts of SCS were found in forest (4532.35 ton/ha), orchard (2997.66 ton/ha) and paddy rice (2682.55 ton/ha) land use, respectively. The differences may be resulted from the variation among the ecosystem types and plant species. Forests are located in wetlands in the high forest and agricultural land more organic carbon levels (0 to 20 cm), but non-significant difference was observed in the soil depth in these areas. The Increased amount of carbon sequestration in the Orchard of the Paddy Rice can be interpreted due to long-term use of fertilizer in the orchards. In Paddy Rice of study due to deep plowing, results showed more decline of organic matter and the loss of carbon from soils.In addition, the maximumtotal nitrogen, organic and sequestrated carbon in top soil (0-10cm depth) were detected in forest (866.968 ton/ha),whereas the least amount dedicated in paddy rice (393.4 ton/ha) land uses. Four classes of detected soil in the study area were included AlfiSols, Inceptisols, Entisols and Mollisols
We found no significant differences in terms of carbon sequestration in land use due to the impact of climate, annually high rainfall and washing clay seems logical. The plant communities in forest ecosystems can become more capable to absorb and retain carbon than other vegetation cover. Agriculture and farming operations are due to dispersion aggregates, reduce of organic matter and carbon sequestration compared to forest intact soils. Considering the vital role of soil carbon sequestration as one of the known values in terms of natural ecosystems and the importance of soil conservation programs, further research works are recommended on the effects of biotic factors such as grazing and land-use changes.

Although the fuzzy logic science has been used successfully in various sudies of hydrology and soil erosion, but in literature review no article was found about its performance for estimating of interrill erodibility. On the other hand, studies indicate that genetic algorithm techniques can be used in fuzzy models and finding the appropriate membership functions for linguistic variables and fuzzy rules. So this study was conducted to develop the fuzzy and fuzzy–genetics models and investigation of their performance in the estimation of soil interrill erodibility factor (Ki).
For this reason 36 soil samples with different physical and chemical properties were collected from west of Azerbaijan province . soilsamples were also taken from the Ap or A horizon of each soil profile. The samples were air-dried , sieved and Some soil characteristics such as soil texture, organic matter (OM), cation exchange capacity (CEC), sodium adsorption ratio (SAR), EC and pH were determined by the standard laboratory methods. Aggregates size distributions (ASD) were determined by the wet-sieving method and fractal dimension of soil aggregates (Dn) was also calculated. In order to determination of soil interrill erodibility, the flume experiment performed by packing soil a depth of 0.09-m in 0.5 × 1.0 m. soil was saturated from the base and adjusted to 9% slope and was subjected to at least 90 min rainfall . Rainfall intensity treatments were 20, 37 and 47 mm h-1. During each rainfall event, runoff was collected manually in different time intervals, being less than 60 s at the beginning, up to 15 min near the end of the test. At the end of the experiment, the volumes of runoff samples and the mass of sediment load at each time interval were measured. Finally interrill erodibility values were calculated using Kinnell (11) Equation. Then by statistical analyses Dn and sand percent of the soils were selected as input variables and Ki as independent variables for development fuzzy and fuzzy- genetic models. For this reason their linguistic variables were defined and fuzzy models rules were written by Mamdani's fuzzy inference method. Then, the outputs of model defuzzified by centroid method. Once again, generation of membership functions and fuzzy rules base as well as optimization of fuzzy rule bases was performed by genetic algorithm, and the fuzzy functions were determined by optimized weight of membership functions and fuzzy rules.
Results Interrill erodibility parameters (Ki) of the examined soils calculated at 3 rainfall rates using are listed in Table 2. The values ranged from 1.03 to 71.79 × 105 kg s m-4, depending on the soil and rainfall intensity. Results showed that the effect of rainfall intensity on Ki turned to be insignificant. This implies that Ki was independent of rainfall intensities. Results showed that the Triangular and Trapezoidal membership functions are better than the other membership functions for linguistic variables which used in this study. The values of R2, RMSE (Root mean square error) and GMER (Geometric mean error ratio) and GSDER (Geometric standard deviation of error ratio) were 0.63, 592755, 1.31 and 1.38 for the fuzzy model, and, 0.70, 441942, 1.10 and 1.044 for the fuzzy- genetic model, respectively. Higher R2 and lower RMSE of the fuzzy – genetic model shows higher accuracy and efficiency of the fuzzy-genetic model. The GSDER criteria shows better matching of the fuzzy- genetic model estimated values with measured values. The GMER criteria shows lower over-estimation of the fuzzy- genetic model than fuzzy model.
Fuzzy and fuzzy-genetic models which were designed with two input variables namely aggregates fractal dimensions and soil sand content, capable to predict of interrill erodibility coefficient of soils with reasonable accuracy. So using of these models for predicting of interrill erodibility is recommended.Optimization of fuzzy rule bases and membership functions weight increased model accuracy. Therefore, using genetic algorithm in developing fuzzy models for prediction of soil erosion rate is recommended.

Adsorption plays a determinant role in the mobility and bioavailability of potassium in soils. Adsorption decreases the solution phase concentration, resulting in very low diffusive fluxes and small transfer by mass flow of soil solution. The K fixation in soils which occurs bytransformation of available forms into unavailable ones, influences the effectiveness of fertilization in soil-plant system. Thus, understanding the mechanism that involves adsorption of K in soil is important because soils may contain widely variable pools of K which are potentially mobilized by chemical weathering of soil minerals. The clay minerals types, pH, soil organic matter (SOM), hydroxide aluminum, soil moisture status, cation exchange capacity (CEC), fertilization and tillage system are the major factors affecting the equilibrium. Adsorption sites for K by organic matter are similar to planar surfaces like kaolinite clays. Soil pH has also significant effect on K adsorption as CEC increases with increase in pH. Knowledge about the variation in behavior of K adsorption among different soils is necessary to predict the fate of applied K fertilizers in soils and to make precise K fertilizer recommendations. The objective of this study was to evaluate the effect of soil organic matter and pH on the adsorption of K by three calcareous soils of Khuzestan Province, at southwest of Iran, having different mineralogical properties.
Three soil samples (Izeh, Shavour, Ahvaz) were collected from different areas of Khuzestan Province and their physicochemical and mineralogical properties were determined. Potassium adsorption experiments were performed by pouring 2g of each air-dried and Casaturated soils, with (control) and without (H2O2) organic matter into polyethylene tubes and adding 20 ml of the stock solution of KCl with initial concentrations of 10, 20, 50, 100 and 200 mg l-1 at pH=6 and pH=7.5. The tubes were shaken at 150 rpm for 24h, as the equilibrium time, at 25 ˚C. The pH of the soils was adjusted by application of 0.1 N HCl and NaOH solutions every 4 hours during the shaking period. The soil samples dissolved in potassium solutions (1:10w/v) were centrifuged at 3000 rpm for 15min. Then, the supernatant was filtered through filter paper (Wathman filters No.42) and the potassium concentrations in the supernatants were determined by flame photometer method. The amount of sorbed potassium in soils was calculated with the equation: (1) where q (mg kg−1) is the amount of adsorbed K onto soil particles, Co and Ce (mg l−1) are the initial and equilibrium concentration of the potassium in solution, respectively; V is the solution volume (ml), and M is the weight of air-dried soil (kg). The data were then fitted by linear Freundlich and Langmuir models.
Among the important geochemical properties of soils for the adsorption of cations are the contents of organic matter, pH, clay contents, and cation exchange capacity (CEC). Accordingly, organic matter, pH, clay and cation exchange capacity contents were 3.09%, 7.62, 20.5% and 16.7 cmol () /kg for Izeh, 0.79%, 7.52, 50.5% and 11.31cmol () / kg for Shavoor soil and 0.95%, 7.15, 20% and 7.39 cmol () / kg for Ahvaz soils. The mineralogical experiments showed that the order of dominant clay minerals in the soils are Vermiculite > Illite > Chlorite > in Izeh, Illite >Vermiculite > Chlorite in Shavoor and Vermiculite > Chlorite >Illite in Ahvaz soils. The results indicated that potassium sorption isotherms in the soils are L-type and both Freundlich and Langmuir equations are able (r2>0.9) to explain the results of the potassium adsorption in the soils studied. Potassium sorption capacity of Freundlich equation (kf) and maximum sorption capacity of potassium (a) in Langmuir equation were obtained between 12.47 to 32.59 (l g-1) and 7.50 to 22.13 mg kg-1, respectively at control and 22.34 to 41.16 (l g-1) and 17.81 to 28.59 mg kg-1, respectively at H2O2 treatments. The distribution coefficient is used to characterize the mobility of cations in soil; low Kd values imply that most of the cation remains in solution, and high Kd values indicate that the cation has great affinity for the surface of adsorbents. Mean content of potassium distribution coefficient at Shavoor soil was significantly higher than other soils which can be attributed to the high content of clay minerals such as illite. Moreover, the results indicated that by increasing the pH values of the soils from 6 to 7.5 the adsorption efficiency of potassium in Izeh, Shavoor and Ahvaz soils increased to 38.3, 8.3, and 26.1%, respectively.
Potassium adsorption in soil is affected by content and type of clay minerals. so that the soils with high illite content have more capacity for sorption and fixation of potassium in soil. On the other hand, organic matter removal from soils increased the potassium sorption by mineral components (especially clay minerals) of the soil studied. Moreover, with an increase in soil pH the potassium sorption increased significantly.

Soil salinity is one of the major limitations of agriculture in the warm and dry regions. Soil sodification also damages soil structure and reduce soil permeability. Therefore, control of soil salinity and sodium is very important. Vetiver grass has unique characteristics that can be useful in phytoremediation.
This research was conducted to investigate the effects of irrigation with different salinities on vetiver grass and the effects of this plant on the control of soil salinity and soil reclamation.The experimental design was randomized complete block design. Irrigation water salinities were 0.68(blank), 2, 4, 6, 8 and 10 dS/m, respectively, which artificially were constructed using sodium chloride and calcium chloride. At first, vetiver was transplanted and then moved to the farm. The amount of soil moisture was measured by the neutron probe. Irrigation depth was applied to refill soil water deficit up to field capacity. To evaluate the soil salinity in above salinity treatments, soil was sampled in each plot from 0-30, 30-60 and 60-90 cm depths and for each layer, electrical conductivity of saturated extract (ECe), sodium, potassium and chloride concentrations was measured .To measure the sodium, potassium and chloride concentrations in the leaves and roots of vetiver plant, samples were dried in oven. The dried samples were powdered and passed through the sieve (No. 200) and they were reduced to ash in 250 ◦C. 5 ml HCl was added to one gram of the ash, and after passing through filter paper, the volume of sample was brought to 50 ml by boiled distilled water. After preparing plant samples, the sodium, potassium and chloride concentrations were measured by Flame Photometer.
Reults and The results showed that the vetiver grass was able to decrease soil salinity at different salinity levels except highest water salinity (10 dS/m) and prevented salt accumulation in the soil. However, in the salinity 10 dS/m, soil salinity was not well controlled, but soil salinity was lower than the irrigation salinity. In these water salinities, the mean ECes in 0-90 cm soil depth were increased 25.0, 60.4, 79.2, 87.5 and 215.5 percent, respectively, relative to a control treatment, which was much less than the increasing of irrigation water salinities. These increases in ECe were significant at 5% level of probability. The accumulated values of sodium in vetiver leaves showed significant difference between S0 treatment and the other treatments (S3, S4 and S5) at the 5% level of probability. The sodium contents in vetiver leaves were 22.2, 33.3, 70.4, 103.7 and 122.2% and in vetiver roots were 32.7, 66.5, 129.3, 218.2 and 281.8% higher than the control treatments (S0), respectively. Sodium contents in vetiver roots were 103.7, 121.2, 154.4, 174.1, 218.2 and 250% more than sodium contents in vetiver leaves in S0, S1, S2, S3, S4 and S5 treatments, respectively. Sodium contents were increased 14.3, 28.6, 64.3, 100.0 and 114.3 percent in vetiver leavesand 28.6, 64.3, 125.0, 214.3 and 275.0 percent in the vetiver roots , relative to the control treatment, respectively, at above salinity levels, which indicated an improvement of sodium accumulation in leaves and roots with increasing salinity levels. Chloride concentrations at irrigation water salinities S1, S2, S3, S4 and S5 treatments (2-10 dS/m) were 22.9, 35.6, 74.5, 107.2 and 121.9% in vetiver leaves and 27.02, 59.7, 118.9, 195.06 and 255.7% in vetiver roots more than control treatment, respectively. The mean values of sodium and chloride in all salinity levels in the roots were 170.3 and 164.1 percent more than the leaves, respectively.There were no significant differences in accumulated potassium in vetiver leaves and roots between different treatments, but vetiver leaves and roots absorbed and accumulated high value of potassium. The potassium contents were 4.38, 4.64, 4.18, 3.89, 3.82 and 3.68 mg/g in vetiver leaves and 3.12, 3, 3.62, 3.69, 3.84 and 3.68 mg/g in vetiver roots, in S0, S1, S2, S3, S4 and S5 treatments, respectively.
In general, the results showed that up to irrigation water salinity 8 dS/m, Vetiver grass had very good ability to control soil salinity and prevented the accumulation of salt in the soil, but at the salinity of 10 dS /m, soil salinity was not well controlled. However, in 10 dS /m, soil salinity was much less than water irrigation salinity.
The mean values of soil salinity in layer 3 (60-90 cm) were 0.48, 0.6, 0.77, 0.86, 0.9 and 1.5 dS/m in S0, S1, S2, S3, S4 and S5 treatments, respectively. ECes were 29.4, 70.0, 80.8, 85.7, 88.8 and 85.0 percent lower than irrigation water salinities 0.68, 2, 4, 6, 8 and 10 dS/m, , respectively. Sodium and chloride accumulated in the leaves and roots of vetiver that showed that Vetiver it is well able to absorb these elements. The accumulations of sodium and chloride in roots were170.3 and 164.1 percent more than leaves, respectively.

Phosphorus (P) and zinc (Zn) fixation by soil minerals and their precipitation is one of the major constraints for crop production in calcareous soils. Recent Studies show that root exudates are effective for the extraction of the large amounts of nutrients in calcareous soils. A part of the root exudations are Low Molecular Weight Organic Acids (LMWOAs). LMWOAs are involved in the nutrients availability and uptake by plants, nutrients detoxification, minerals weathering and microbial proliferation in the soil. At nutrients deficiency conditions citric and oxalic acids are released by plants root in large quantities and increase nutrient solubility like P, Zn, Fe, Mn and Cu in the rhizosphere. These components are the large portion of the carbon source in the soil after exudations are mineralized by microorganisms, quickly. In addition, soil surface sorption can affect their half-life and other behaviors in the soil. In order to study the effect of oxalic and citric organic acids on the extraction of phosphorus and zinc from a calcareous soil, an experiment was conducted.
Studied soil was calcareous and had P and Zn deficiency. Soil sample was collected from A horizon (0-30 cm) of Damavand region. 3 g of dried soil sample was extracted with 30 ml of oxalic and citric acids extraction solutions at different concentrations (0.1, 1 and 10 mM) and different time periods (10, 60, 180 and 360 minutes) on an orbital shaker at 200 rev min-1.The soil extracts then centrifuged for 10 minutes (16000g). After filtering, the pH of the extractions was recorded and then phosphorus, calcium and zinc amounts were determined. Soil extraction with distilled water was used as control. Each treatment was performed in 3 replications. Statistical analysis was performed with ANOVA test followed by the Bonferroni method significant level adjustments due to multiple comparisons.
The results of variance analysis showed that the effect of different concentrations of organic acids at various times on the pH of extractions was significant at 1% level. Low concentrations of organic acids at various times had no effect on the pH of soil extractions compared to control, but organic acids at 10 mM concentration increased the pH of extractions. This high pH amount was related to the organic acid mineralization and consumption of H by microorganisms in the soil. The results of variance analysis also showed that the effect of different concentrations of organic acids at various times in the extraction of Ca from the soil was significant at 1% level .Citric acid extracted higher Ca from the soil compared to oxalic acid. The maximum extracted Ca was observed at 10 mM concentration of citric acid at 10 minutes of shaking time. Extracted Ca at 0.1 and 1 mM concentrations of both organic acids was almost the same at all the times. The higher extraction of Ca with citric acid was due to the Ca precipitation as oxalate. The analysis of variance for P showed that the effect of different concentrations of organic acids at various times was significant at the 1% level. Extracted P by oxalic acid was more than citric acid .The highest amount of P was obtained by 10 mM concentration of oxalic acid at 360 minutes. The amounts of extracted P by both organic acids at 0.1 and 1 mM concentrations were similar to control. Citric acid at 10 mM concentration also released lower P compared to other concentrations and control. More P extraction of oxalate than citrate was due to the Ca-oxalate formation and P release from calcium phosphate in calcareous soil. Different concentrations of organic acids at different time periods had no effect on Zn extraction from the soil and the amount of extracted Zn by organic acids was lower than control.
Organic acids at 10 mM concentration were effective in Ca and P extraction from the soil but had no significant effect on the Zn extraction. It seems that organic acid more than 10 mM concentrations is required for Zn extractionfrom from the calcareous soils. The type and concentration of Organic acids, soil type, shaking time and experimental conditions are important factors that affect the obtained results.

The most important problems of farmers in arid and semi-arid regions are adequate nutrition, optimum rooting, emergence, establishment and optimal density, and ultimately plant yield. Using grain priming and mycorrhizal inoculation is effective strategies in these conditions. Priming can cause earlier growth of seedling, to increase emergence rate, emergence percentage, plant tolerance to drought and salinity stress, early flowering as well as to increase the quality and quantity of yield and nutrient absorption. Plant hormones such as salicylic acid and gibberellic acid can be used for priming. Regarding plant response to environmental stresses, salicylic acid, which is an important signal molecule, plays a key role in the regulation of several physiological processes such as growth and plant development, absorption of ions, emergence and photosynthesis. Gibberellic acid (GA3) has been shown to be involved in many physiological processes such as cell division activity of meristem regions, increase the cell length, emergence speed, and emergence percentage, seedling growth in field condition, early flowering and yield. Mycorrhizal inoculation increases the availability of nutrients especially plant phosphorus, concentrations of plant hormones (auxins, cytokinins and gibberellins), chlorophyll content, the efficiency of biological nitrogen fixation, assimilates allocation to host plant organs, the changes of root structure, and improve soil structure.
In order to evaluate the response of lentil to grain priming (without grain priming, hydro-priming, 100 ppm gibberellic acid, 100 ppm salicylic acid, 100 ppm gibberellic acid 100 ppm salicylic acid) and soil mycorrhizal inoculation (non-inoculated control, inoculated with Glomus moseae and Glomus intraradices), a factorial experiment based on a completely randomized block design with four replications carried out in a greenhouse and research farm of the Gonbad Kavous University during 2013 and 2014. Various priming treatments - applied in the laboratory. Then, during planting, mycorrhizal inoculation treatment was kept in the closet place to the grains about 5 g per gram of grain (40 spores per gram). To determine the activity of roots (root length and number of nitrogen fixation nodes) 10 seedlings per pot were kept. Measured traits in the field condition were included the concentration and uptake of total phosphorus in aerial parts, concentration and total phosphorus uptake of grain, grain yield, and biological yield.
Variance analysis showed that different treatments of mycorrhizal inoculation, priming, and their interactions had significant effects on the studied traits such as the root length, number of nitrogen fixation nodules, phosphorus concentration of aerial parts, grain phosphorus concentration, grain phosphorus uptake, biological yield, and grain yield. In this study the highest root length (39.5 cm), nitrogen fixation nodules (114), aerial parts phosphorus uptake (12.1 kg/h) were obtained under combined treatment of G. intraradices inoculation 100 ppm gibberellic acid. While the aerial parts phosphorus concentration (0.24%) and grain phosphorus uptake (22.8 kg/ha) were higher due to using combined treatment of mycorrhizal G. Moseae hydro-priming. Hormonal priming with salicylic acid increased grain yield and biological yield significantly over the other hormonal priming and control. Hydro-priming had a significant and positive effect on grain yield in three levels of bio-fertilizer. Results of salicylic acid treatment were similar to the results of hydropriming. Influence of hormones, especially gibberellic acid in grain causes more activities in some emergence catalytic enzymes, the emergence speed, emergence percentage and root elongation. These effects may be inconspicuous in irrigated cultivation, but it can lead to the survival of plants in the dry farming situation. In this study, gibberellins increased the radicle length and the number of nitrogen fixation nodules. It may be an important factor in increasing the quality and quantity of grain yield of lentil. Various treatments of salicylic acid had a moderate effect. More positive effects were obtained when these treatments applied to the form of combination. The most applied treatments in this experiment such as mycorrhizal and priming treatments and their interaction had a positive effect on quality and quantity of grain properties of lentil aerial parts. This positive effect may be due to availability of some nutrients which is supplied using priming treatments, microorganisms, secretion of growth promotion and the change of root structure.
In the present study inoculation of both fungi and various treatments of priming had a positive effect on the studied traits individually, but the higher effects of them were found in the combined treatments. The effect of G. intraradices hydro-priming was more outstanding. Overall, the present study indicated that the various treatments of bio-fertilizer and priming increased the root length and nitrogen fixation. Therefore, the absorption of nutrients was increased. It could be concluded that synthesis fertilizer is unnecessary.

Nitrogen is an essential element for plant nutrition. Urea is a common fertilizer that used by farmers due to high nitrogen content in its structure. This fertilizer transforms into nitrate in soil. Nitrate is leached below the rooting zoon of agricultural soil. Nitrate leaching is not only a waste of a great cost, but also causes the pollution of water resources. Methemoglobinemia and cancer are well known issues that caused by nitrate leaching. For this purpose, many methods have been proposed to prevent nitrate leaching but due to high cost and low efficiency are not accepted. Using of zeolites is one of the ways that is considered due to its low cost and ability. Zeolite is a mineral material that found in many regions in Iran. Although effect of zeolite on nitrate leaching reduction was studied by many researchers, but there was no study on common three types of Iranian zeolite.
For this purpose, a study was conducted as factorial layout based on a CRD with 21 treatments and 3 replications (total of 63 pots) at the Agricultural Research Station (with longitude and latitude 59o 21’ E and 32o 78’ N, respectively, and elevation 1941m), University of Birjand during 2013. Treatments consisted of calcic zeolite (Zca), potasic (Zk) and z-mix (Zs) in three levels: 0 (M0), 2 (M2) and 6 (M6) as wt% and three nitrogen levels: zero (F0), 200 (F2) and 400 (F4) (as mg.kg-1 soil). Natural clinoptilolite zeolite (Zca, Zk and Zs) were collected from Semnan province (53o 15’ E, 35o 25’ N) and analyzed for its chemical composition by X-ray diffraction.
Pots after saffron harvesting irrigated (in October) and urea treatment added to irrigation water (Iranian farmers called as Zaeech Ab). For prepared sufficient drain from all pots, due to different effect of type and amount of zeolite on soil water content, based on former experiments, leaching fraction was considered as 20%. Sample drain from each pot were transferred toa lab, immediately, and were measured by spectrophotometer. Data related to nitrate leaching were analyzed by ANOVA and Tukey’s test. In this study, SAS 9.1.3 software and Microsoft Excel 2013 were used.
Results showed that type of zeolite, amount of zeolite, amount of nitrogen fertilizer, type of zeolite with amount of zeolite (interaction effect) had significant effect (P

Nanoparticles due to their large specific area and reactivity recently have been used in several environmental remediation applications such as degradation of organic compounds and pesticides and adsorption of heavy metals and inorganic anions. Because of concern over potential threats of nanoparticle releases into the soil–water environment, a number of studies have been carried out to investigate the transport, retention and deposition of nanoparticles in saturated porous media. Many of these studies are based on measurements of transport in columns packed with idealized porous media consisting of spherical glass beads or sand. The nanoparticles are usually introduced into the column and breakthrough curve concentrations are measured at the column outlet. To examine the effect of various parameters on the transport of nanoparticles in porous medium, for convenience, all the parameters considered the same in the experiments, and only one parameter in the experiments is changed and investigated.
The objective of this research is quantitative study of modified magnetite nanoparticles transport in saturated sand-repacked columns. The modified magnetite nanoparticles with Sodium dodecyl sulfate were synthesized following the protocol described by Si et al. (2004). The experimental setup included a suspension reservoir, Teflon tubing, a HPLC pump, and a glass column (2.5 cm i.d. and 20 cm height). Therefore, breakthrough curves of modified magnetite nanoparticles with Sodium dodecyl sulfate and chloride were determined under saturated conditions and influence of nanoparticles concentration (0.1 and 0.5 g.L-1) and pore velocity (pressure head of 2 and 10 cm) on nanoparticles transport were investigated. For each medium bed, the background solution were first pumped through the column in the up-flow mode to obtain a steady flow state. Then, a tracer test was conducted by introducing CaCl2 solution into the column. The response curve was followed by analyzing the concentration history of Cl-1 in the effluent. Then, the influent was switched back to the background solution to thoroughly elute the tracer. Following the tracer test, a modified magnetite nanoparticles with sodium dodecyl sulfate was introduced into the column and the nanoparticle breakthrough curves were obtained by measuring the concentration history of total Fe in the effluent. Total iron concentration was analyzed with a flame atomic-absorption spectrophotometer.
One site and two site kinetic attachment-detachment models in HYDRUS-1D software were used to predict the nanoparticles transport. Also parameters of model efficiency coefficient (E), root mean square error (RMSE), geometric mean error ratio (GMER), and geometric standard deviation of error ratio (GSDER) were used to determine the accuracy of the models.
SEM measurements demonstrated that the particle size of nanoparticles was about 40-60 nm. The hydrodynamic dispersion coefficient (D) for each medium was obtained by fitting the classic 1-D convection–dispersion equation (CDE) to the experimental breakthrough data using the CXTFIT code (STANMOD software, USDA). The relative concentration of nanoparticles in comparison with chloride in the collected effluent from soil columns were much lower indicating a strong retention of nanoparticles in studied porous media, thereby attachment, deposition and possibly straining of nanoparticles.
Modeling results showed that in all sites of both models (one site and two-site kinetic attachment-detachment models), attachment was rapid and detachment was slow. These attachment kinetic sites may be because of consistent charges of minerals with attachment. Therefore, considering to same attachment-detachment behavior in two sites of two-site kinetic model, it is concluded that the one site kinetic model had eligible estimation of nanoparticles breakthrough curve in the studied sandy soil columns lonely. Efficiency of one site and two-site models varied from 0.761 to 0.851 and 0.760 to 0.846 respectively that indicated both models had good estimation of nanoparticles transport in the sandy soil. Also, logarithmic form of nanoparticles breakthrough curve showed that both models had good estimation of all ranges of breakthrough curve containing its tail.
Investigation of transport modeling of modified magnetite nanoparticles with Sodium dodecyl sulfate in a saturated sandy soil showed that decreasing the nanoparticles concentration would enhanced the mobility of modified magnetite nanoparticles, but increasing of pressure head had no effect on nanoparticles mobility. The results of models evaluation showed that both one site and two-site models had eligible estimation of nanoparticles transport in the studied sandy soil columns.

Water quality control is very important for people, animals and plants. Predicting the spread of contaminants is important for managing and protecting rivers and streams to the balance of the ecosystem. Pollutants are introduced into waterways, though a variety of sources such as point and non-point sources. Under steady state conditions, where longitudinal mixing is not significant, studying the lateral mixing is essential in evaluating the influence of pollutants on water quality. Lateral or transverse mixing is the hydraulic process by which a plume of contaminant spreads laterally and dilutes. In water quality management, the transverse mixing is more significant than either vertical or longitudinal dispersion, especially, when dealing with the release of wastes from point sources. Hence, a wide range of field, laboratory and numerical modelling approaches, including laboratory and field measurements, and analytical and numerical investigations have been developed, to quantify the lateral mixing coefficient. However, most of the researchers have ignored the effects of vegetation on the lateral mixing process in their studies. Many studies have shown that the flow characteristics through vegetation are different from those in non-vegetated waterways. For example, laboratory studies have revealed that flow velocity and large-scale turbulence tend to be greatly decreased within a plant canopy, because the resistance to flow by the vegetation. Also, vegetation affects the transport of dissolved and particulate material, such as sediment, nutrients and pollutants. In this study, the effect of the floodplain vegetation on lateral mixing coefficient in compound channels is investigated experimentally. Also, a comparison is made between the results of the present study with those obtained by previous researchers.
Experiments were carried out in a laboratory flume 18m long, 0.9m wide and 0.6m high with an asymmetric compound channel section. Three different densities of cylindrical PVC elements of 1 cm diameter were used in addition to the case without cylinders. Three-dimensional flow velocity measurements were taken using a down-looking four beam Acoustic Doppler Velcimeter (ADV). A highly concentrated solution (C0=10 g/L) of red dye (KMnO4, Potassium permanganate) was injected as a tracer sufficiently far downstream of the beginning of the flume such that the flow was fully developed determined by measuring velocity profiles. Variations of tracer concentration at three locations 4.00, 6.44 and 8.88 m downstream of the injection point were determined using image processing technique. In this technique, digital cameras are used at specified cross sections to capture the pixel intensity before and during the passage of the dye cloud. Using the Beer–Lambert Law, the pixel intensity is related to the dye concentration after a simple calibration. Afterward, the images could be used as input files for MATLAB’s Image Processing Toolbox.
The results showed that due to the strong secondary currents and unstable vortexes in the compound channel, the tracer cloud is periodic. The transverse mixing coefficient in the main channel is also always greater than that in the floodplain and its value increases with relative depth. Another factor that was found to affect the lateral mixing coefficient was the vegetation density. The non- dimensioed transverse mixing coefficient increases with vegetation density in the main channel as well as the floodplain. As vegetation density increases from 0.26 to 0.88%, the non- dimensioned transverse mixing coefficient increased up to 40% of the flow relative depth of 0.15. For low density vegetation (0.26%), the lateral mixing coefficient in both the main channel and floodplain was increase upto 30%. Also, for the vegetation density of 0.88%, the lateral mixing coefficient increases up to 80 and 107% for the floodplain and main channel, respectively. As the flow relative depth increase, the effect of the vegetation on the transverse mixing coefficient decreases on both the main channel and floodplain.
It can be concluded that floodplain vegetation affects the transverse mixing coefficient in the main channel and floodplain, significantly. Also, the flow relative depth and vegetation density are two important factors that control the mixing process in compound channels. The results of the present study were in good agreement with those obtained by Lin and Shiono (1995), Siono and Feng (2003), Shiono et al. (2003), Zeng et al. (2008) and Zhang et al. (2010). More researches are needed to extend the findings of the present study to the field applications.

Soil and ground water pollution with organic matter and toxic materials is an ordinary environmental problem. In this case, oil compounds are among the most important environmental pollutants. Tehran oil refinery is one of the largest and oldest refineries in Iran located south of Tehran city. Since the beginning of its activity in 1968, its waste materials (solid, semisolid and liquid) have been disposed in large lagoons next to the refinery site. During this long period, considerable changes in soil properties have occurred, which are of great research interests for soil and environmental scientists.
The studied area (about 60 ha) was located in the south of Tehran (latitude: 35°30.299' to 35°30.814' N and longitude: 51°25.682' to 51°26.296' E). Six pedons, including four Technosols developed on the oil refinery waste materials (pedons no. 1, 3, 4 and 6) and two reference pedons (pedons no. 2 and 5) were fully described and sampled. Particle size distribution (PSD) of gypsiferous samples was determined by the specific method for gypsiferous soils (Hesse, 1976). PSD of non-gypsiferous samples were determined according to the standard hydrometer method (Gee and Bauder, 1986), but the oil-polluted samples were analyzed according to the standard ultrasound method (Sawhny, 1996). Organic carbon content was determined by Walkley and Black (1934). pH and EC were measured in soil saturation extracts using EC and pH meter (Jenway). Gypsum and CaCO3 contents were determined using acetone (Sparks, 1996), and calcimetery methods, respectively. Mineralogical analysis was done by Decarreau (1990). Micromorphological descriptions were carried out using the terminology of Stoops (2003). Diagnostic horizons were identified and finally the studied pedons were classified according to the Keys to Soil Taxonomy (Soil Survey Staff, 2014) and the World Reference Base (FAO, 2014).
Horizons of both polluted and unpolluted soils were mostly gypseous and/or calcareous especially in the middle parts. Considering the surface and subsurface diagnostic horizons and the aridic-thermic soil moisture and temperature regimes, the studied soils were classified as Gypsids, Calcids or Cambids (Soil Survey Staff, 2014). However, due to the added oil waste compounds and presence of impermeable geomembrane in some of the polluted pedons, they were classified as Technosols in the WRB system (FAO, 2014). Noticeable effects of Pollutants in the soil were decreasing pH and increasing OM and EC. The surface horizons of the unpolluted soils contained less than 2 percent organic matter which regularly decreased by depth. However, In some horizons of the polluted soils, soil organic matter exceeded 12 percent. pH decreased by increasing organic matter (oil waste compounds) possibly due to H dissociation from the oil compounds (Laurent et al., 2012). Electrical conductivity throughout the polluted soil horizons showed more limited variability than the unpolluted ones, probably due to their higher capability in water and liquid dynamics. Liquid limit and plasticity limit in polluted soils are higher than unpolluted soils . Plasticity index in polluted soils decreased with increasing the amount of pollutants. The results of mineralogical studies corroborated that dominant clay mineral in this soils is Smectite. Smectites have high swelling and shrinking capacity.So, the pollutants can intercalate between soil mineral layers and then increase d-spacing of clay minerals. The micromorphology of the polluted soils showed that low dielectric constant of petroleum caused flocculation and formation granular aggregates in soil. Studied soils are inactive in terms of activity of clay.
As observed in the studied soils, their physico-chemical properties such as pH and electrical conductivity (EC) of saturated paste extract, organic matter content, mineralogical and micro-morphological properties were severely affected by the oil wastes. These results show these soils have been limited and in use of these soils, considering these properties is required. In polluted soils, due to small differences between plasticity limit and liquid limit, it is possible to their sliding faster than unpolluted soils and then construction should be avoided.

Earthworms are among the most important organisms in soil and their activities can be an indicator of soil quality. These organisms may be influenced by organic wastes application such as sewage sludge and subsequently affect soil quality. One of the quick and easy methods for soil quality monitoring is the use of biological indicators such as microbial activity. It is due to their quick response to changes in the environment. The purpose of this study was to evaluate the effect of earthworms on nitrification rate and arginine ammonification as microbial activity in a calcareous soil amended with urban sewage sludge.
The studied soil was sampled from Shahrekord University land and sewage sludge belonged to the refinery sludge ponds of shahrekord. Based on dry weight, this organic waste had carbon and nitrogen, approximately 67 and 110 times more than tested soil, respectively. The organic waste in terms of quality and heavy metal concentrations was in class A. Experimental treatments were sewage sludge (without and with 1.5% sewage sludge) and earthworm (no earthworm, Eiseniafoetida from epigeic group, Allolobophracaliginosa from endogeic group and a mixture of the two species) as 2×4 full factorial experiment arranged in a completely randomized design with three replications. After applying sewage sludge, the pots were irrigated three months to achieve a balance in the soil. An adult earthworm per kg of soil was added and in the mixed treatments comparison species were 1:1. To prevent the exit of earthworms, the pots was closed with a thin lace. At the end of the experiment, soil was completely mixed. Part of it was stored in the refrigerator to measure the microbiological parameters. Chemical properties were measured by the air-dried soil. The effectiveness of a factor in the observed changes is shown by partial effect size (Tabachnick and Fidell 2012). So, partial effect size (Eta2p) for each source of variation (SS, earthworm and SS×earthworm) was calculated.
Results According to Eta2p, the role of sewage sludge application to increase total nitrogen was almost twice the earthworm and had a greater effect on the property. Because of low concentrations of heavy metals and high nutrient in sewage sludge, it increased nitrification rate and arginine ammonification by 16.7 and 62.5 percent, respectively. Considering that the indices represent microbial biomass activity, so we can say sewage sludge application increased theri activities. Sewage sludge application increased total nitrogen, because provided the substrate for heterotrophic bacteria. Consequently, ammonium production improved and stimulated activity of Nitrosomonas and Nitrobacter. There was a positive and significant correlation between total nitrogen, arginine ammonification and nitrification rate, that confirmed the occurrence of this process. Earthworm inoculation affected these two indicators (p

Variety of soil reactions govern the distribution of metal micronutrients that includes complexation with organic and inorganic ligands, ion exchange, adsorption and desorption processes, precipitation and dissolution of solids and acid-based equilibria. The relative importance of these reactions depends on many factors such as soil physical, chemical, and mineralogical properties and the nature of metal ions. Environmental factors such as climate, physiographic position, and soil development may affect variability of some soil properties and thereby nutrient availability. The present research was conducted to find relationships between Iron, manganese, zinc, and copper availability and some major soil properties, physiographic condition and soil development.
Golpayegan region is located in northwest of Isfahan province in central Iran. The mean elevation of the studied area is 1790 above sea level. Annual precipitation was about 244mm and mean monthly temperature ranges from -6 in January to 34°C in August. The soils were developed on different physiographic conditions including piedmont plains, alluvial-fan, plateaus, and flood plains belonging to Entisols and Aridisols. Soil samples (0–60 cm) were collected from 98 grid points with 2000m distance in the agricultural area of Golpayegan. Particle size distribution, calcium carbonate, organic carbon, available potassium and phosphorus of the soils were measured by SWRI standard methods. Available Zn, Cu, Mn, and Fe were determined by addition of 10 g soil to 20mL 0.005M diethylentriaminepentaceticþ. The solutions were shaken for 2 h at 25°C, centrifuged, filtered, and Fe, Mn, Zn, and Cu concentrations were measured by an atomic absorption spectrophotometer.
Results Studied soils were developed on calcareous material and about 60% of samples have more than 20% of calcium carbonate. Available Fe ranged from 1.4 to 6.5 mg kg-1 (mean 15.8 mg kg-1). Significant relationships were also found between DTPA-extractable Fe, organic matter (OM) and calcium carbonate. The results indicated that organic matter (OM) is the most influential soil characteristics that predict Fe availability. DTPA-extractable Mn in the soils ranged from 1.8 to 19.8 mg kg-1 (mean 7 mg kg-1). There were also no relationship between available Mn and soil properties. It has been reported that Mn availability in soils is mainly influenced by oxidation-reduction rather than other factors. Available Zn in the studied soils ranged from 0 to 2.4 mg kg-1 (mean 0.8 mg kg-1) and had significant correlations with particle size and OM contents. This result showed the importance of soil exchanger phase (clay and OM) in Zn availability in calcareous soils, and was in agreement with the findings of Wu et al. (2006) in soils of North Dakota. DTPA-extractable Cu ranged from 0.2 to 2.4 mg kg-1 (mean 0.9 mg kg-1). According to the report of Lindsay and Norvell (1978), 90% of soils had sufficient Cu. However, there were variations among soils in available Cu as a function of physiographic position. The highest values were found in the soils developed on piedmont plains. Significant relationships between available Cu and some major soils properties such as sand, clay, OM, and calcium carbonate were also found. This result was in agreement with findings of Wu et al. (2010) who concluded that soil properties influencing the spatial distribution of Cu availability.
Nutrient availability is one of the most critical concerns of plant production in calcareous soils of Golpayegan . Different pedogenic processes, variable deposition and transport, and different weathering regimes affect micronutrient content, distribution, and availability. Results indicated that Fe deficiencies followed by Mn and Zn in the studied soils are more critical than Cu deficiencies. In fact, 90% of soils had sufficient Cu. Mainly micronutrient availability in the studied soils was related to soil texture and organic matter, although Mn availability showed no relationships with major soil properties. It was concluded that the availability of Fe, Zn, and Cu may be predicted to some extent using some factors such as soil properties and physiographic condition. Availability of Fe, Zn, and Cu in Torrifluvents developed on piedmont plain was higher than in other soils and this may be due to the high amounts of OM and clay, whereas Haplocalcids developed on plateaus had the lowest content. Generally, it was concluded that the mentioned factors affect metal distribution and cycling in the soils and thereby metal availability for plants. On the other hand, prediction of micronutrient availability using these factors can be taken into consideration for better management.

Zinc (Zn) is an important nutrient element for humans and plants that controls many biochemical and physiological functions of living organisms. Zinc deficiency is common in high pH, low organic matter, carbonatic, saline and sodic soils. Salinity is a major abiotic environmental stresses that limits growth and production in arid and semi-arid regions of the world. Bioavailability of Zn is low in calcareous and saline soils having high levels of pH and calcium. Desorption of Zinc (Zn) from soil as influenced by biological activities is one of the important factors that control Zn bioavailability. Few reports on the effects of salinity on the availability and desorption kinetics of Zn are available. Rupa et al. (2000) reported that increasing the salt concentration led to increase Zn desorption from soil due to ion competition on soil exchangeable sites. Different kinetic equations have been used to describe the release kinetics of nutrients. Reyhanitabar and Gilkes (2010) found that the power function model was the best equation to describe the release of Zn from some calcareous soil of Iran, whereas Baranimotlagh and Gholami (2013) stated that the best model for describing Zn desorption from 15 calcareous soils of Iran was the first-order equation.less attention has been paid to kinetics of Zn release by DTPA extractant over time by inoculation of plant growth promoting rhizobacteria and mycorrhizae fungi in comination with soil salinity.The objective of this study was to evaluate the effect of plant growth promoting rhizobacteria (PGPR) and mycorrhizae fungi (MF) inoculation on release kinetic of Zn in a calcareous soil at different salinity levels after in cornplantation
A composite sample of bulk soil from the surface horizon (0-30 cm) of a calcareous soil from southern part of Iran was collected, air dried, passed through 2 mm sieve, and thoroughly mixed. Routine soil analysis was performed to determine some physical and chemical properties. The experiment was conducted in the greenhouse of agriculture college of Shahid Chamran University, Ahvaz, Iran. A factorial experiment as a completely randomized design with three replications was conducted in greenhouse conditions. The first factor consisted of salinity levels (0, 15 and 30 cmol(c) kg-1 salt supplied as a 3:2:1 Na:Ca:Mg chloride salts) and the second factor was microbial inoculation (without inoculation, fungi, bacteria, bacteria fungi).Soil samples were extracted using DTPA extractant for periods of 0.5, 1, 2, 6, 12 and 24 hours. Cumulative Zn released (q) as a function of time (T) was evaluated using seven different kinetic models. A relatively high values of coefficient of determination (r2) and low values of standard error of estimate (SEE) were used as criteria for the selection of the best fitted models. Statistical analysis of data was done using MSTATC package (Mstatc, 1991). Comparison between means was performed using Duncan's multiple range test (DMRT) at the significant level of P Investigation of Zn release patterns showed that the control and all treated soils had a uniform pattern of Zn release. Overall, Zn release patterns were generally characterized by an initial fast reaction at first two hours, followed by slower continuing reaction. It seems likely that the release of zinc is controlled by two different mechanisms. Two-step process of releases (rapid and subsequent slow) is attributed to the existence of places with different energy. The use of all microbial treatments increased the initial release of Zn compared to control. The most and the least Zn initial release observed in fungi-bacterial and bacterial treatment respectively. By application of all microbial treatments, Zn release rate declined compared to control and the lowest decrease observed in fungal treatment. In general, Zn initial release was increased and Zn desorption rate was decreased by increasing of salinity levels. Also, soluble and exchangeable forms of Zn had the highest influence on Zn release control.
Results showed that simplified Elovich, two constant rate and parabolic diffusion kinetics models showed good description of the Zn release. Based on the highest correlation coefficient and the lowest mean standard error of the estimate, simplified elovich determined as the best kinetic model. So it seems that the main mechanism controlling the Zn release in the tested soil is diffusion phenomena.

It is vital to control land degradation, for conserving precious natural treasures. Quantification of runoff production and soil and nutrient loss from wild lands under different managerial systems is one of the scientific and optimal management in agriculture and natural resources, as a major component of sustainable development. Many researches have been conducted to assess the effects of different land uses on soil erosion and runoff generation throughout the globe. Most of which, mainly verified the detrimental effects of human intervention on land degradation. However, limited comprehensive and comparative studies have been conducted to consider the amount of surface runoff generation, and soil and nutrient loss from watersheds with different management patterns viz. untreated and treated small watersheds.
The present study aimed to compare surface runoff generation,soil and nutrient loss in Kakhk treated and untreated watersheds with an area ca. 222 ha and precipitation of some 243 mm per annum. Other physical and geological characteristics of the paired watersheds were also similar to allow assessing the effects of study measures on soil, water and nutrient losses. The area under consideration has been located in Khorasan Razavi Province in northeastern Iran. The present study was performed in plots with standard size of 22.1 × 1.8 m in treating and representative areas, with three replicates and on the storm basis occurred during early 2011 and mid-2014. The treated plots were covered by biological measures viz. seeding, bunching and exclusre. The study plots have been situated on eastern,western and northern aspects with respective slope of 55, 40 and 40 %. The entire runoff from study plots were collected in a container in 0.5×1×1 m. The sediment concentration was also measured in 2-liter samples taken from the container after a complete mixing of the entire collected runoff. The sample was treated by decantation technique, oven dried and weighted by high precision scale. The transported elements, i.e. potassium, phosphorous and nitrogen were also measured in solute and particulate forms. Ultimately, the data bank was developed in Excel 2010 and got ready to be processed in SPSS 19.0 software package and statistically compared with the help of analysis of variance (ANOVA) test.
The results showed that the soil loss, nitrogen concentration, potassium concentration and sediment concentration had significant difference (p

Soil organic matter is considered as an indicator of soil quality, because of its role on the stability of soil structure, water holding capacity, microbial activity, storage and release of nutrients. Although changes and trends of organic matter are assessed on the basis of organic carbon, it responds slowly to changes of soil management. Therefore, identifying sensitive components of organic carbon such as carbon labile lead to better understanding of the effect of land use change and soil management on soil quality.
The main components of sustainable agriculture in arid and semi-arid regions are the amount of water; and soil and water salinity. Water deficit and irrigation with saline water are important limiting factors for cropping and result in adverse effects on soil properties and soil quality. Soil carbon changes is a function of addition of plant debris and removal of it from soil by its decomposition. If the amount of organic carbon significantly reduced due to the degradation of the soil physical and chemical properties and soil quality, agricultural production will face serious problems. To this end, this study was done to evaluate soil quality using soil labile carbon and soil carbon management indices in some agricultural lands of Neyriz area, Fars province, Iran.
Five fields were selected in two regions, Dehfazel and Tal-e-mahtabi, consisted of irrigated wheat and barley with different amount of irrigation water and water salinity levels. Three farms were located in Dehfazel and two farms in Tal-e-Mahtabi region. In each farm, three points were randomly selected and soil samples were collected from 0-40 cm of the surface layer. Plant samples were taken from a 1x1 square meter and grain crop yield was calculated per hectare. Water samples were obtained in each region from the wells at the last irrigation. Physical and chemical characteristics of the soil and water samples were determined. Soil labile carbon and carbon management indices also were calculated. In carbon management index calculation, a reference farm was chosen at the vicinity of two regions which were abandoned for years. Statistical analysis like analysis of variance and correlation coefficients was done using SPSS 16.0 software.
Results revealed that the highest crop yield (with the average of 5.7 tonh-1) was related to the farm which was irrigated with saline water (water EC 8.1 dSm-1) with enough water crop requirement. As this farm received the highest amount of water (with thw volume of 1039.5 mm), it seems that much more irrigation water probably provided the leaching fraction and prevented salt accumulation in the the root zone. Therefore, water salinity could not be a limiting factor for crop growth in this farm. This farm also had the highest content of organic carbon but it didn’t have the highest labile organic carbon and carbon management index (the value of 161.5).
On the other hand, the farm containing the highest labile carbon and carbon management indices (the value of 284), didn’t have the highest crop yield (with the average of 2.6 tonha-1) although it has recieved enough amount of water as well as non-saline irrigation water (water EC 2.28 dSm-1). The more carbon management index represents the higher soil carbon lability and soil quality and it demonstrates that soil have better condition for living microorganisms. Therefore, it can be concluded from the results that the higher soil quality not necessarily resulted in higher crop yield. Many researchers reported that better soil properties are not always resulted in the higher productivity.
Taking everything into account, carbon management index is not related to crop yield, but since it indirectly is related to microbial activity and calculated easily, it could be a useful indicator for rapid assessment of soil quality. Meanwhile, this indicator may be associated with qualitative properties of the crops such as grain protein, which is recommended for future investigations.
Results showed that labile organic carbon is more sensitive to crop management than total organic carbon. Amount of irrigation water and its salinity can influence the labile organic carbon content and thus the soil quality even in the fields with the same crop yield and management. Although, a higher amount of carbon management index does not result in higher yield production, it may be associated with crop quality attributes. More investigation is needed to give better idea in this regard.

Penetration resistance is one of the criteria for evaluating soil compaction. It correlates with several soil properties such as vehicle trafficability, resistance to root penetration, seedling emergence, and soil compaction by farm machinery. Direct measurement of penetration resistance is time consuming and difficult because of high temporal and spatial variability. Therefore, many different regressions and artificial neural network pedotransfer functions have been proposed to estimate penetration resistance from readily available soil variables such as particle size distribution, bulk density (Db) and gravimetric water content (θm). The lands of Ardabil Province are one of the main production regions of potato in Iran, thus, obtaining the soil penetration resistance in these regions help with the management of potato production. The objective of this research was to derive pedotransfer functions by using regression and artificial neural network to predict penetration resistance from some soil variations in the agricultural soils of Ardabil plain and to compare the performance of artificial neural network with regression models.
Disturbed and undisturbed soil samples (n= 105) were systematically taken from 0-10 cm soil depth with nearly 3000 m distance in the agricultural lands of the Ardabil plain ((lat 38°15' to 38°40' N, long 48°16' to 48°61' E). The contents of sand, silt and clay (hydrometer method), CaCO3 (titration method), bulk density (cylinder method), particle density (Dp) (pychnometer method), organic carbon (wet oxidation method), total porosity(calculating from Db and Dp), saturated (θs) and field soil water (θf) using the gravimetric method were measured in the laboratory. Mean geometric diameter (dg) and standard deviation (σg) of soil particles were computed using the percentages of sand, silt and clay. Penetration resistance was measured in situ using cone penetrometer (analog model) at 10 replicates. The data were divided into two series as 78 data for training and 27 data for testing. The SPSS 18 with stepwise method and MATLAB software were used to derive the regression and artificial neural network, respectively. A feed forward three-layer (8, 11 and 15 neurons in the hidden layer) perceptron network and the tangent sigmoid transfer function were used for the artificial neural network modeling. In estimating penetration resistance, The accuracy of artificial neural network and regression pedotransfer functions were evaluated by coefficient of determination (R2), root mean square error (RMSE), mean error (ME) and Akaike information criterion (AIC) statistics.
The textural classes of study soils were loamy sand (n= 8), sandy loam (n= 70), loam (n= 6) and silt loam (n= 21). The values of sand (26.26 to 87.43 %), clay (3.99 to 17.34 %), organic carbon (0.3 to 2.41 %), field moisture (4.56 to 33.18 mass percent), Db (1.02 to 1.63 g cm-3) and penetration resistance (1.1 to 6.6 MPa) showed a large variations of study soils. There were found significant correlations between penetration resistance and sand (r= - 0.505**), silt (r= 0.447**), clay (r= 0.330**), organic carbon (r= - 0.465**), Db (r= 0.655**), θf (r= -0.63**), CaCO3 (r= 0.290**), total porosity (r= - 0.589**) and Dp (r= 0.266*). Generally, 15 regression and artificial neural network pedotransfer functions were constructed to predict penetration resistance from measured readily available soil variables. The results of regression and artificial neural network pedotransfer functions showed that the most suitable variables to estimate penetration resistance were θf, Db and particles size distribution. The input variables were n and θf for the best regression pedotransfer function and also Db, silt, θf and σg for the best artificial neural network pedotransfer function. The values of R2, RMSE, ME and AIC were obtained equal to 0.55, 0.89 MPa, 0.05 MPa and -14.67 and 0.91, 0.37 MPa, - 0.0026 MPa and -146.64 for the best regression and artificial neural network pedotransfer functions, respectively. The former researchers also reported that there is a positive correlation between penetration resistance with Db and a negative correlation between penetration resistance with θf and organic carbon.
The results showed that silt, standard deviation of soil particles (σg), bulk density (Db), total porosity and field water content (θf) are the most suitable readily available soil variables to predict penetration resistance in the studied area. According to the RMSE and AIC criteria, the accuracy of artificial neural network in estimating soil penetration resistance was more than regression pedotransfer functions in this research.

Salinity is one of the main problems which limits crop production, especially in arid and semi-arid areas such as Iran. Iran is the most important producer of pistachio in the world. However, its performance is low in many areas. Most pistachio plantations are irrigated with saline water and with low quality (28). On the other hand, nitrogen is a dynamic element which is a constituent of amino acids, proteins, nucleic acids and Enzymes and it has a vital role in plant physiology, growth, chlorophyll formation and production of fruit and seeds (34). Gibberellic acid is known as phytohormon which varied physiological responses in plants under stress. acid gibberellic increases the photosynthesis and growth under stress and impact on the physiology and metabolism of plant (29). Based on previous studies, production and activity of plant hormones are affected by natural factors and plant nutrient requirements and the nitrogen has an important influence on production and transmission of acid gibberellic plant shoot. Therefore, in this study the effect of acid gibberellic and nitrogen on some characteristics of physiology parameters and micronutrient pistachio seedlings (Cv. Qazvini) under saline conditions was studied.
Experiment under greenhouse condition and factorial in a completely randomized design with three replications was conducted in greenhouse agriculture college, Vali-E-Asr University of Rafsanjan. Treatments consisted of three levels of salinity (0, 1000 and 2000 mg of sodium chloride per kg of soil), three levels of nitrogen (0, 75 and 150 mg per kg of ammonium nitrate source) and three acid gibberellic levels (0, 250 and 500 mg per liter). Adequate soil with little available salinity conditions was collected from the top 30-cm layer of a pistachio-culture region of Kerman province. After air drying and ground through passing a 2 mm sieve, some of the physical-chemical properties of this soil include pH (7/63), Tissue (Sandy loam), electrical conductivity (ECe) (1 dS m-1), Silt (23.1%), Clay (5.5%), Organic matter (0.5%), Olsen phosphorus (P) (5.35 mg kg-1), Ammonium acetate-extractable K (100 mg kg-1) were determined. Nitrogen treatments 3 weeks after planting, dissolved in irrigation water was added to pots. Salinity, after the establishment of the plant (5 weeks after planting), divided into two equal parts and one-week interval dissolved with irrigation water was added to the pot. as well acid gibberellic treatments, as spray after salt treatment was applied at three times and at intervals of one week.
The results showed that the salinity content of carotenoid and Chlorophyll fluorescence parameters significantly reduced but with increasing acid gibberellic and nitrogen application, mentioned parameters were significantly increased, compared to controls. The ability of photosynthesis improved and increased productivity. Mozafari et al studied the pistachio, reported that with increasing salinity from zero to 150 and 300 mM NaCl, carotenoids decreased more than 16% and 22% compared to control respectively. Carotenoids play a most important role in light, protecting plants against stress condition. Salinity application increased leaf proline, but with application of 150 mg nitrogen and 500 mg per liter foliar application of acid gibberellics, this parameter increased by 55 and 26 percent, respectively. Also, combined use of these two treatments increased proline content by 79 percent compared to control. The researchers stated that the increasing gibberellin concentration caused leaf proline increased, so spraying 100 and 200 mg per liter gibberellin significantly increased leaf proline compared with the non-application of gibberellin. The results also showed with increasing salinity increased iron, manganese and zinc concentrations shoots and roots and decreased copper concentrations, but using 150 mg of nitrogen and acid gibberellic consumption concentrations of copper element increased. Hojjat nooghi and Mozafari (28) reported, the used salinity of 60 mM NaCl increased shoot Fe concentration, but by applying the same amount of salinity in the root iron concentration decreased compared with the control. Research has shown that the copper concentration in the leaves and shoot of corn planted in soil decreased with increasing salinity. Micronutrient absorption reduction such as copper in salt condition can result in greater absorption of nutrients such as sodium, magnesium and calcium. The researchers in the study reported that with increasing nitrogen in the form of nitrate and ammonium, zinc concentration in plant tissues increased along with increasing salinity and lower shoot dry weight, zinc concentration was increased in two wheat cultivars too.
The results of this experiment showed that under saline conditions, acid gibberellic and nitrogen applied alone or in combination improved physiology parameters and increased nutrient concentration of pistachio seedling.

Zinc (Zn) is an essential trace element for plants as well as for animals and humans. On the other hand, Zn is a heavy metal and its high concentration can cause some environmental problems. There are significant relationships between soils, plants and humans Zn status in a certain agro-ecosystem.Therefore, mass flux assessment of Zn in agro-ecosystem is important regarding to plant and human nutrition in one hand and environmental quality on the other hand. Therefore, assessing the Zn accumulation trend in agricultural soils is essential to prevent Zn deficiency as well as soil pollution by Zn.
This investigation was conducted in order to model Zn accumulation rate in agricultural soils of Kermanshah province using inputs and outputs fluxes mass balance. Mass Flux Assessment (MFA) model were applied for the modeling accumulation rate of Zn uses a random method of element balance with the combination of Latin Hyporcube method and Mont-Carlo simulation, in several agricultural ecosystems of some townships (Kermanshah, Songhor, Gilanegharb, Ghasreshrin, Shaneh, Sarpolezahab, Kangavar, Paveh and Javanrood). In this study, mass flux assessments were done at both provincial and township scales. Various routes of Zn considered in this study were livestock manure, mineral fertilizers, pesticides, atmosphere deposition, municipal waste compost (input) and uptake by plant (output). Agricultural information, including crop type, crop area and yield, kind and number of livestock, application rates of mineral fertilizers, compost, pesticides and atmospheric deposition rates and also a metal concentration in the plants, livestock manure, mineral fertilizers, compost and dust was used to quantify Zn fluxes and Zn accumulation rate. Given that the other sources of Zn input such as sewage sludge and output such as leaching are not important fluxes in the study area, the calculations performed here presented a good estimation of the average net effects of the dominating Zn inputs and outputs of the Zn status in agricultural soils of the study region.
The results showed that the maximum and minimum of the Zn accumulation rate were seen in agricultural soils of Paveh (1172 g ha-1yr-1 in average) and Kermanshah (-26 g ha-1yr-1 in average)respectively. The average net flux of Zn accumulation rate for Kermanshah province was also 1538 g ha-1yr-1. The negative Zn accumulation rate of Kermanshah soils implies depletion of this element that is due to higher uptake of Zn by plants, especially crops with high performance such as maize and sugar beet. The calculated accumulation rates were less than the critical accumulation rate (calculated for the next 200 years in the study area). The results showed the high range (difference between the simulated maximum and minimum) of the Zn accumulation rate in Paveh was 1307 g ha-1yr-1, and the lowest in Songhor was 175 g ha-1yr-1. The major part of the uncertainty in the Zn balance resulted from manure source. According to the calculated SRCAP (Standardized Regression Coefficients Aggregated in Percent) values, Zn input with manure and then Zn output with crop removal were the main sources of Zn net flux uncertainty at township and province 9 levels. The uncertainty associated with livestock manure fluxes explained 67-94% of the total uncertainty. This large contribution was mainly due to large uncertainty in the numbers of dominant livestock, in particular cattle and poultry, and in the Zn:P concentration ratios of their manures. The influence of crop removal on Zn net fluxes uncertainty ranged from 3-29% among the townships. Differences in contributions of individual crops to the total cultivated area and in the Zn concentration of dominant crops as well as uncertain crops yield data were the main reasons for this large variation among townships.
The most important routes of Zn entry into the agricultural soils were livestock manures (69-93%) and atmosphere deposition (9-28%) in township level, while in provincial scale, they were compost (61%), livestock manures (33%), and atmosphere deposition (5%) respectively. The uncertainty analysis results indicated that livestock manure was the most effective rout on Zn accumulations rate uncertainty (79% in province scale and 67-94% in township scale). The results also indicated that current agricultural management generally leads to accumulation of Zn in soils of the study area (with exception for Kermanshah township soils). This can cause some difficulties such as soil contamination or soil fertility loss by nutritional elements imbalance in future.

The forest residuals play an important role in runoff rate, soil erosion, and soil infiltration capacity of protecting mineral (surface) soils from the direct impact of raindrops. By intercepting rainfall, the forest residuals serve as a temporary reservoir and allows more time for infiltration into the mineral soil beneath (Kosugi et al., 2001). Hydraulic properties of forest residuals were unknown to some extent and could not be measured with similar methods used for mineral soil. In recent years, several studies on the forest floor have been published (Kosugi et al.,2001; Schaap et al.,1997). The objective of this study was the comparison of accuracy of van Genuchten and Brooks & Corey models for simulating water flow in forest floor using the HydroGeoSphere Code of broad-leaved, needle-leaved and mixed-stand floor. First, saturated hydraulic conductivity, porosity, and water retention curve parameters (van Genuchten equation) which were unknown parameters in the forest floor were estimated by inverse method. Second, estimated hydraulic properties were compared statistically.
Forest floor samples were collected from broad-leaved (beech and others), needle-leaved (coniferous) and mixed-stand (coniferous and broad-leaved) trees in Guilan province, Iran. In the laboratory, a plastic wire-netting, composed of 0.3 mm diameter was attached to the bottom of each core sample to support forest floor. Then the samples were piled up to make long columns of 18.1 cm in inner diameter and about 40.88 cm in height. Artificial rainfall experiments were conducted on top of the columns and free drainage from the bottom of columns was measured in the laboratory. Applied rainfall intensities were randomly changed in the range of 0-0.01 cm/sec. Drainage at the bottom of the tray was collected and measured using an electronic balance. First, a constant intense rain was applied to reach to steady state condition as a constant discharge rate from the bottom was established in order to accurately define the initial condition required for the numerical simulation of unsaturated water flow. After reaching to state steady experiment, transient condition was carried out. In transient condition, the random rainfall experiment was conducted and the transient discharge rate from the bottom was continuously monitored. In this study, we developed an inverse method for estimating parameters based on the Levenberg-Marquardt (Marquardt 1963) minimization algorithm in the C programming language along with HydroGeoSphere (Therrien et al., 2008) as a forward model. The model was used to address two specific issues. First, it was used to estimate the hydraulic conductivity, porosity, and soil water retention curve parameters (van Genuchten and Brooks & Cory equations) which were unknown parameters in the unsaturated porous media. Second the water flow in the forest floor was simulated using van Genuchten and Brooks & Cory equations along with HydroGeoSphere code.
The results of calibration periods showed that the estimated free drainage using the optimized parameters exhibits a good fitting with the observed free drainage for all treatments. The good agreement between simulated and observed free drainage in the validation period for all the forest floor samples illustrated that the estimated hydraulic properties efficiently characterized the unsaturated water flow in forest floor. So one could conclude that Richard's equation along with Brooks & Cory and van Genuchten's retention functions can successfully describe the unsaturated water flow in the forest floors.
Estimated hydraulic properties succeeded to reproduce the observed free drainage in the transient condition, indicating van Genuchten functions along with Richard's equation can be used to simulate water flow in the entire forest floors. The results of the study showed that the forest floor samples have large saturated hydraulic conductivity values like light soils. The results showed that inverse method was not sensitive to residual water content. Also the results showed that HydroGeoSphere code along with van Genuchten's retention function with 0.2753 mimics free drainage better than Brooks & Corey's retention function with 0.3400 but there is no significant difference (P