نشریه آب و خاک
سال بیست و نهم شماره 3 (پیاپی 41، امرداد و شهریور 1394)

The greatest part of constructed dams belongs to embankment dams and there are many examples of their failures throughout history. About one-third of the world’s dam failures have been caused by flood overtopping, which indicates that flood overtopping is an important factor affecting reservoir projects’ safety. Moreover, because of a poor understanding of the randomness of floods, reservoir water levels during flood seasons are often lowered artificially in order to avoid overtopping and protect the lives and property of downstream residents. So, estimation of dam overtopping risk with regard to uncertainties is more important than achieving the dam’s safety. This study presents the procedure for risk evaluation of dam overtopping due to various uncertaintiess in inflows and reservoir initial condition. This study aims to present a practical approach and compare the different uncertainty analysis methods in the evaluation of dam overtopping risk due to flood. For this purpose, Monte Carlo simulation and Latin hypercube sampling methods were used to calculate the overtopping risk, evaluate the uncertainty, and calculate the highest water level during different flood events. To assess these methods from a practical point of view, the Maroon dam was chosen for the case study. Figure. 1 indicates the work procedure, including three parts: 1) Identification and evaluation of effective factors on flood routing and dam overtopping, 2) Data collection and analysis for reservoir routing and uncertainty analysis, 3) Uncertainty and risk analysis. Figure 2 shows the results of the computed overtopping risks for the Maroon Dam without considering the wind effect, for the initial water level of 504 m as an example. As it is shown in Figure. 2, the trends of the risk curves computed by the different uncertainty analysis methods are similar. As it can be seen, the risk curves computed by the LHS are slightly higher than those curves computed by the MCS method. Also as it is observed, the differences between risk values of the two methods increase in longer return periods. Variations of overtopping risk with increasing the initial water level and return period related to overtopping risk in the 2-year return period for the initial water level of 470 m are shown in Table1. The results show that elongation of return period plays a more important role in increasing the risk, than the increase of initial water level. This study applies MCS and LHS methods to analyze the uncertainty and evaluate the dam overtopping risk consideringthe uncertainties in input variables, such as quintile of flood peak discharge, initial levels of water and spill coefficients. The results show that the uncertainty of water level calculated by MCS is higher than that calculated by LHS. In addition, the overtopping risk calculated by LHS is higher than that calculated by MCS. Furthermore, the increase of inflow rate influences the variations of the overtopping risk more than the increase of the return period. In addition, evaluation of the results indicates that the overtopping risk is an important issue in the Maroon dam. So, a comprehensiverisk analysis procedure in conjunction with uncertainty gives very important information for decision makers to make better judgments in dam operation based on uncertainty in inputs.

For a velocity profile in turbulent flows, the flow conditions in the vicinity of the wall are described by logarithmic law of the wall. However, it has been extensively verified that the log-law does not apply in the outer region of the boundary layer. For example, in free surface flows, the law of the wall holds only for 20 percent of the flow depth from the wall. Coles (1956) conducted an important advancement and argued that away from the wall, the deviations of the profiles of measured velocity from those obtained from the law of the wall could be explained by another universal law, called the wake-law. Combining both laws (wall and wake), a complete approximation to the time-averaged velocity profile in turbulent flows is then feasible (White, 1991). On the other hand, the fundamental problem of characterizing the mean velocity profile in sediment-laden flows remains unresolved. While existence models have been developed to estimate velocity profile, but there is a lack of generalization in the sediment-laden flows. For several decades, it has been controversial about the effects of suspended sediment on hydraulic characteristics of the flow, including flow resistance and velocity distribution. Fig. 1 shows the variations of velocity distribution due to introduction of the suspended sediment. As it is seen in this Figure, the suspended sediment moves faster than the water in the inner layer; on the other hands, there is a velocity-lag due to the introduction of sediment into the outer layer. Accurate estimate of the rate of sediment loads is important in sediment-laden flow. Because velocity distribution is one of the required parameters to estimate the sediment discharge. Until now, many equations have been introduced by many researchers for estimating the velocity distribution in open channels. Generally, there are two different views about the velocity distribution in sediment-laden flows. The first view suggests that the log-law is also applied in the sediment-laden flows and von Karman constantly decreases with increasing sediment concentration. Such researchers as Vanoni (1946), Einstein and Chen (1955), Elata and Ippen (1961) supported this idea. Another view is that von Karman constantly does not decrease with increasing sediment concentration and velocity distribution deviates from the main region of the flow. Because of these contradictions about the effects of suspended sediments on characteristics of the flow and given the existence of several developed models, this question may be raised whether which one is markedly superior to the others or what model gives accurate results in the sediment-laden flow. No attempt was made to make an exhaustive comparison of the models with available experimental data. The present study evaluates and discusses the performance of seven models, by comparing these with experimental data selected from four sources. Then these equations will be assessed using the experimental data, and the best model will be introduced by means of statistical analysis. In this paper, the velocity distribution of sediment-laden flow has been investigated. Such equations as Log-law, modified log-law, wake-law, modified log-wake, log-modified wake, and parabolic law have been studied. The accuracy of each equation has been assessed by using statistical analysis. The mean average error (MAE) is a quantity used to measure how close predictions are to the eventual outcomes. The root-mean-square error (RMSE) is a frequently used measure of the differences between value predicted by a model or an estimator and the values actually observed. Determination coefficient (R2) is a number that indicates how well data fit a statistical model. Experiment data related to Wang and Qian (1989), Vanoni (1946), and Coleman (1981) have been used to test the proposed models. In most data sets, the width-depth ratios are less than 5, i.e., the maximum velocity occurs below the water surface. Thus, the boundary layer thickness is defined as the distance from the bed to the maximum velocity position, where the velocity gradient is zero. The accuracy of each equation has been assessed using some statistical indices. The results showed that the log-wake velocity distribution in both the inner and outer regions estimated the velocity values with reasonable accuracy (with a relative error of 5%). It is recommended that this equation is used to calculate the suspended sediment discharge. On the other hand, parabolic-law doesn’t have a good accuracy and it will cause large errors (with a relative error up to about 15%). In addition logarithmic distributionsare only able to estimate accurately the velocity in the inner region. It was also found that in sediment-laden flows, in the region where y/h ≥ 0.2, the effect of sediment concentration can be neglected as the sediment concentration becomes very low. Therefore, it is more reasonable to look for an equation having acceptable accuracy in the inner layer.

Groundwater is the largest resource of water supplement and shortages of surface water supplies in drought conditions that requires an increase in groundwater discharge. Groundwater flow dependson the subsurface properties such as hydraulic gradient (water table gradient or head loss in artesian condition) and hydrodynamic coefficients. The flow treatment is analyzed with an accurate estimation of effective parameters in groundwater equation. This function is obtained using the continuous equation. Inlet and outlet flows of a cell are equal to storage amounts in the continuous equation. Analytical solution of this equation is complex, so numerical methods are developed including finite element and finite difference methods. For example, Feflow is a groundwater modeling tool that makesuse of finite element method (Reynolds and Marimuthu, 2007). Modflow as a finite difference three-dimensional model simulated underground flow under steady and unsteady conditions in anisotropic and non-homogeneous porous media. Modflow is designed to simulate aquifer systems in which saturated-flow conditions exist, Darcy’s Law applies, the density of groundwater is constant, and the principal directions of horizontal hydraulic conductivity or transmissivity do not vary within the system. In Modflow, an aquifer system is replaced by a discretized domain consisting of an array of nodes and the associated finite difference blocks. Groundwater modeling and water table prediction by this model have the acceptable results, because many different informations of water resource system are applied. Many people and organizations have contributed to the development of an effective groundwater monitoring system, as well as experimental and modeling studies (Lalehzari et al., 2013). The objective of this paper is investigation of hydraulic and physical conditions. So, a numerical model has to be developed by PMWIN software for Bagh-i Malek aquifer to calculate hydrodynamic coefficients and predict water table in the future. Bagh-i Malek aquifer located in Khuzestan province is mainly recharged by inflow at the boundaries, precipitation, local rivers and return flows from domestic, industrial and agricultural sectors. The discharge from the aquifer is through water extraction from wells, springs, and qanats as well as groundwater outflow and evapotranspiration. In this study, conceptual model of Bagh-i Malek aquifer on the framework of finite difference numerical approach has been used in simulating groundwater flow treatment. Water table data of 8 piezometers was collected for the 10 year duration from 2002 to 2012. The study years are divided into 40 seasonal stress periods with daily time step. Hydraulic conductivity, specific yield and recharge were calibrated in these periods. Verification was made between the simulated and measured hydraulic heads in the next calibration year. To simulate the groundwater table elevation in this study area, the PMWIN model is used. Bagh-i Malek aquifer is considered as a single layered aquifer, and therefore only the horizontal hydraulic conductivity is estimated. Modflow was used to simulate both steady state and transient flow systems. In steady conditions it is assumed that the total of time simulation is a time period and it does not change inlet data in the modeling duration. In unsteady conditions,the duration of study is divided into some stress periods that data is changed in every period. Estimation of hydraulic conductivity is the first step of calibration process at steady state conditions. The correct assignment of hydraulic conductivity has a main effect on other parameters accuracy. Hydraulic conductivity mapping indicated that the maximum values are in the Eastern North (6-7 m/day) of the aquifer. The twice calibrated parameter is specific yield in unsteady conditions. Specific yield mapping indicated that the values vary from 0.03 to 0.08 and are maximum in the Southern regions of the plain similar to hydraulic conductivity. The results confirm that the flow model has the tolerable simulation accuracy by variances of 3.1 and 3.84 in calibration and verification processes, respectively. The sensitivity of the flow model to decreasing the hydraulic conductivity is more than increasing it. 50 percentage declined into the hydraulic conductivity causes the increase of the variance from 3.1 of initial value to 44. Mapping of calibrated hydraulic conductivity showed that the Eastern North of aquifer has the higher transmissivity and discharge capability in comparison to Southern parts. At last, the result show that the Bagh-i Malek aquifer model is sensitive to recharge, hydraulic conductivity and specific yield, respectively.

Expansion of the area of oilseed crops such as soybean is one of the policies of Iranian agricultural policy makers as Iran is one of the major oilseed importers in the world. However, the area of this crop in Kermanshah province is negligible, but it could be cultivated in most parts of this province. The quantity and quality of the produced grain could be affected by environmental factors such as weather parameters and water availability. The aim of the current study was to investigate the effects of levels of deficit irrigation on the quantity and quality of soybean crop yield in Kermanshah, Iran. For this purpose, a field study was conducted as randomized complete block design with four replications and four irrigation treatments at the research farm of Razi University, Kermanshah in 2012. The size of each plot was 4 * 4 m. Irrigation treatments consisted of four irrigation levels: 20% over irrigation (T4), full irrigation (T3 as control), 20% less irrigation (T2) and 40% less irrigation (T1). The reason to choose T4 treatment was the lack of confidence in estimated crop evapotranspiration as there was no local calibration of crop coefficient (Kc) for this crop. The required water for T3 treatment was calculated based on daily weather data using FAO-Penman-Montith equation. Daily weather data was recorded in a weather station which was located in the research farm and is available in the www.fieldclimate.com. As there was no rainfall during the crop season, all of the required water was supplied through irrigation. The required water for treatments of T1, T2 and T4 was considered as 60%, 80% and 120% of T3 treatment. The required water was applied using a hose connected to a volumetric flow meter with a liter precision. Total amount of applied water during the crop season was 4399, 5865, 7331 and 8797 m3.ha-1 in the treatments. Fertilizers were applied based on the recommendations of soil fertility experts. Weeds were controlled manually. Finally, the area of two square meters in the middle of each plot was harvested in order to determine crop yield in terms of grain, biomass, stem, pod, seed protein content and fat percentage and also water productivity index. Dry weights of the samples were measured after drying samples in the oven for48hours at 70° C. The percentage of fat and protein in the grains are also measured in the laboratory. Water productivity index was calculated for each treatment by dividing crop yield (in terms of grain, biomass, protein and fat) over seasonal water use. Statistical analysis of the results is also done using MSTATC software. The highest and lowest crop yields were measured respectively in the treatments T4 and T1.The mean value of grain yield was 1084, 1367, 1716 and 1940 kg.ha-1,respectively in the treatments T1, T2, T3 and T4. These results showed a 36% decrease in the grain yield by decreasing 40% in the amount of supplied water. However, biological yield was decreasedby the level of irrigation, but the rate of reduction was lower than that of grain yield. By reducing irrigation application, thepercentage of grain protein content increased while the percentage of fat in the grain decreased. Considering simultaneous reduction in grain yield and fat content in the grain, severe reductions in fat yield (oil content) were observed under water stress conditions. Crop yield in terms of fat was reduced by 26.2 and 50.1 %, respectively in treatments T2 and T1 in comparison with T3 (control treatment). The maximum and minimum percentages of protein in the treatments were 31% and 27%, respectively in the treatments T1 and T4. Maximum water productivity in terms of grain, biomass and protein was achieved in T1 treatment respectively with the amounts of 0.24, 0.81 and 0.077 kg.m-3. Maximum and minimum fat percentage was 0.052 and 0.040 kg.m-3, respectively in the T4 and T1 treatments. In addition,the results indicated that water productivity index in terms of grain, biomass and protein increased while they decreased in terms of fat yield.The results of statistical analysis indicated that water productivity index in all terms except protein had significant differences (at 5%) with T3 treatment. Crop yield and water productivity (except in terms of fat) was increased by increasing applied water. Considering all indices of treatment T2 (20% deficit irrigation), itwas suggested as the best treatment.

Production and growth of plants in many parts of the world due to degradation and water scarcity have been limited and particularly, in recent decades, agriculture is faced with stress. In the most parts of Iran, especially in the Khorasan Razavi province, drought is a fact and water is very important. Due to melon cultivation in this province, and the conditions of quality and quantity of water resources and water used to produce the melon product in this province, any research done on the use of saline and brackish waters is statistically significant. To study the effects of different water salinity and water management on some of the agronomic traits of late summer melon with drip irrigation, an experiment with 7 treatments and 3 repetitions was conducted in a randomized complete block design, in Torogh station, Mashhad. The irrigation treatments were: 1- fresh water from planting to harvesting, 2- water (3 dS/m) from planting to harvesting, 3- water (6 dS/m) from planting to harvesting, 4- water (6 dS/m) from 20 days after plantation to harvesting, 5-water (6 dS/m) from 40 days after plantation to harvesting, 6-water (3 dS/m) from 20 days after plantation to harvesting, 7-water (6 dS/m) from 40 days after plantation to harvesting. Row spacing and plant spacing were 3 m and 60 cm, respectively and the pipe type had 6 liters per hour per unit of meters in the drip irrigation system. Finally, the amount of salinity water, number of male and female flowers, number of seed germination, dry leave's weight, leaf area, chlorophyll (with SPAD) etc. were measured and all data were analyzed by using MSTAT-C software and all averages of data, were compared by using the Duncan test. Results and Discussion The results of analysis of data showed the following: Number of seeds germination: Salinity in water irrigation had no significant effects on the number of seed germination. However, there was the most number of seed germinations in the fresh water treatments. However, with increased water salinity, the time of seed germination reduced. The maximum delay in germination of seeds was in the treatment that was irrigated with fresh water from the beginning of cultivation. Number of flowers: First, the male flowers appeared and after 5 to 7 days, the appearance of female flowers began. The effect of irrigation treatments on female flower appearance was significant. With increased water salinity, the number of male flowers decreased. There was the lowest male flower in the treatment that was irrigated with saline water from the beginning, but there was no significant difference among the other treatments. Root, steam and leaves: The effect of saline irrigation water on dried leaves’ weight and dry root weight was significant at 1% and 5% levels, respectively. Fresh treatment and salinity treatment have the least and the most root dries weight, respectively (irrigated from the beginning with fresh or saline water). Two treatments that were irrigated with fresh and brackish water from thebeginning of cultivation have the highest leaf growth. The same trend was true for steams. In general, in all treatments, after applying different quality water to the end of the growing season, the trend of plant growth was similar to the others. Chlorophyll: One of the most common measurements made by plant scientists is the determination of Chlorophyll concentration. The SPAD index was used for comparison of chlorophylls. With an increase of the salt in irrigation water, the SPAD index was also increased. The maximum and minimum SPAD was in the treatments that were irrigated with saline water (treatment A) and fresh water (treatment C) from the beginning of cultivation, respectively. Yield: With increasing the salinity of water, the total yield decreased. Salinity in irrigation water had a significant effect (at the 5% level) on total yield. The mean yield of brackish and salinity irrigation water treatments were 17.5% and 26% less than the fresh water irrigation treatment, respectively.These differences were significant. However, there was no significant difference between the yield of cases using brackish or salt water. The results showed the following: Salinity in irrigation water had no significant effect on the number of seed germinations. However, there was the most number of seed germinations in the fresh water treatments, but by raising the salinity of water, the time of seed germination was reduced. With increasing the salinity of water, the number of male flowers decreased. There was the lowest male flower in the treatment that were irrigated with salt water from the beginning, but there was no significant difference between the other treatments. The effect of salinity water on leaf dry weight and dry root was significant at 1% and 5% levels, respectively. Fresh and salinity treatments have the least and the most root dry weight, respectively (irrigated from the beginning with fresh or salt water). Two treatments that were irrigated with fresh and brackish water from the beginning of cultivation have the highest leaf growth. The same trend was true for steams. Two treatments that were irrigated with fresh and brackish water from the beginning of cultivation have the highest leaves areas. And they had significant difference with other irrigation treatments. With an increase in the salt in irrigation water, the SPAD index also increased. The mean yield of brackish and salinity water irrigation treatments were 17.5% and 26% less than that of fresh water irrigation treatment, respectively.These differences were significant. But there was no significant difference between the yield of brackish and salt water.

Olive (Olea europaea L.) trees are mainly cultivated in the Mediterranean area and are grown for their oil or processed as table olives. Despite the fact that olive is known to be resistant to drought conditions due to its anatomical, physiological, and biochemical adaptations to drought stress, reports indicate that the olive can be adversely affected by drought stress, which has a negative effect on the growth of olive trees. In the absence of adequate supplies of water, the demand for water can be met by using improved irrigation methods or by using reclaimed water (RW). Reports have shown that recycled water has been used successfully for irrigating olive orchards with no negative effects on plant growth.Attention has been paid to reclaimed water as one of the most significant available water resources used in agriculture around large cities in arid and semi-arid regions. On the other hand, irrigation efficiency is low and does not meet the demands of farmers.In order to investigate the possibility of irrigating olive orchards with subsurface leakage irrigation (SLI) in application of reclaimed water, an experiment was carried out with the aim of investigating the effect of reclaimed water on photosynthetic indices and morphological properties of olive fruit. Research was conducted using a split-plot experimental design with two factors (irrigation system and water quality) on the campus of Isfahan University of Technology in Isfahan, Iran, on a sandy-clay soil with a pH of 7.5 and electrical conductivity (EC) of 2.48 dSm-1.PVC leaky tubes were used for the SLI system. The SLI system was installed 40 cm from the crown of each tree at a depth of 30 - 40 cm.At the end of the experiment fruit yield, weight per fruit, volume, length and firmness were calculated. A portable gas exchange system (Li-6400., LICOR, Lincoln, NE, USA) was used to measure the net rate photosynthesis (A), the internal partial pressure CO2 (Ci), and stomatal conductance (gs) between (09.30 – 11.30 h) on a fully expanded current season leaves situated at mid canopy height. Statistical assessments of differences between mean values were performed by the LSD test at P = 0.05. Results and Discussion The results revealed that reclaimed water enhanced fruit yield, weight (15%), volume (23%) and leaf photosynthesis (22%) in plants compared with clear water. Recycled water was found to supply more nutrients than clear water. High nutrient concentrations in RW, compared to those in clear water, result in nutrient accumulation in the soil, making them available to plant roots to promote overall plant growth and fruit production. Improved N, P, K nutrition of wastewater-irrigated plants has been reported (Farooq et al, 2006). Olive leaves and stems represent storage organs for N and release it in response to the metabolic demands of developing reproductive and vegetative organs (Fernandez-Escobar et al., 2004). However, Al-Abasi et al. (2009) found no statistical differences. Irrigation with SLI systems increased the photosynthesis (33%), and stomatal conductance (57%) when compared with surface irrigation systems. The results showed that reclaimed water had a significant effect on photosynthesis and stomatal conductance. However, fruit length and firmness had no significant difference. Substomatal CO2 decreased when the SI systems were used for irrigation. Also SLI system could enhance fruit yield (65%), weight (17%), photosynthesis (32%) and chlorophyll Fluorescence (Fv/Fm) (18%). The SLI systems with recycled water induced greater shoot growth, total leaf surface area, and transpiration during the entire growing period. This led to an overall positive effect on mean fruit weight and total fruit production per tree. The SLI system applying RW led to more photosynthesis by 34% as compared to the SI system. In the present study, the SLI system delivered water directly in the root zone and improved water availability, which enhanced photosynthetic assimilation rates and plant growth to a great extent. David et al. (2003) showed that subsurface drip irrigation versus other irrigation methods reduced evaporation and improved growth and production in peach trees. As a conclusion, the results from this research show that recycled water could be a promising resource for irrigation of olive trees and acted as a source of nutrients and irrigation water.In addition, SLI irrigation system is more efficient in irrigation of olive trees when compared to surface irrigation system and proved beneficial for olive growth.

The frequency of floods is one of the characteristics of river flow statistics so thatanalyzing it has an important role to assess the hydrological and economical water resources projects. For determining flood frequency, the estimation of accurate skewness coefficient of annual peak discharges is required. Estimation of population skew for different regions will be improved when it is computed from the weighted average of the sample skew and an unbiased generalized skew estimate. There are different ways to develop a generalized skewness coefficient. The goal of this study is to analyze the methods for generating unbiased generalized skew coefficient and select the best method for creating the weighted generalized skewness coefficient. In the present study, to calculate weighted generalized skewness coefficient, initially the hurst index is calculated to analyze the adequacy of time series length. The case study of the present research (West Azerbaijan, Iran) has three basins containing different hydrologic regions. These three basins are: the Aras River, Urmia Lake and Zab River basins. Therefore, various hydrologic regions, with the help of provincial border and the borders between sub-basins, are combined to form three larger hydrologic regions.After the formation of three larger hydrologic regions, the homogeneity of skewness variance of annual peak discharge of hydrometric stations within each three hydrological groups are tested using theleuven statistical parameter. Also the Dunnett test is applied to identify areas whichare significantly differentiated with other hydrologic regions. To develop the generalized skewness coefficient of 67 hydrometric stations with different statistical periods (16 to 62 years), three methods containing statewide map of skewness in West Azerbaijan, skewness map with including three hydrologic regions, and weighted average of skewness for the three hydrologic regions were used. Finally, after calculating the errors of three methods of generalized skewness development using Mean Square Error (MSE) coefficient, a weighted technique is used to calculate the weighted generalized skewness using sample skewness and the best generalized skewness (the one which has the least error) and their corresponding errors. The results showed that most parts of the province have negative skewness values. The Hurst test results showed that the hurst coefficient is greater than 0.5 for all 67 hydrometric stations and lengthening of time series for the analysis is not required. Also, the results of the leuven statistical parameter showed that the homogeneous assumption is true for hydrological groups. Therefore, there is no reason for the variance heterogeneity. Moreover, the results of the Dunnett test stated that statistically, skewness means within the hydrological groups are not different. An error analysis showed that the Zab river basin had the least error amongthe studied basins. Among the methods studied for developing the skewness map, the division of the province into three hydrologic regions hada higher accuracy (MSE of Generalized skew coefficient = 0.55) than the other methods. However, this difference was very marginal. According to skewness maps, it can be seen that by considering hydrologic regions, the errors can be reduced in all three hydrologic regions. As the MSE in areas A and B is lower than the provincial level and in the region C, the error rate is close to zero. However, it should be noted that the number of hydrometric stations in region C, are much lower than other parts of the study area and this can be one of the reasons for error reduction in this area. Considering that the aim of this study was to evaluate the accuracy of the generalized skewness estimating methods in the calculation of weighted generalized skewness coefficients, it has been seen that a regional approach, in addition to reducing the error rate, the fracture lines on the skewness map of the annual peak discharges can be reduced. Unlike the regional approach, the averaging method has shown worse results in all three regions.We may conclude that the sample skewness coefficient alone can bring better results than the averaging approach. Also, by comparing errors in areas A, B, and C, it can be concluded that with increment in area of hydrologic regions and inadequate spatial distribution of hydrometric stations, the error rate increases.

The to be limited available water amount from one side and to be increased needs of world population from the other side have caused increase of cultivation for products. For this reason, employing new irrigation ways and using new water resources like using the uncommon water (salty water, water drainage) are two main strategies for regulating water shortage conditions. On the other side, accumulation of salts on the soil surface in dry regions having low rainfall and much evaporation, i.e. an avoidable case. As doing experiment for determining moisture distribution form demands needs a lot of time and conducting desert experiments are costly, stimulator models are suitable alternatives in answering the problem concerning moving and saltiness distribution. In this research, simulation of soil saltiness under drip irrigation was done by the SWAP model and potency of the above model was done in comparison with evaluated relevant results. SWAP model was performed based on measured data in a corn field equipped with drip irrigation system in the farming year 1391-92 in the number one research field in the engineering faculty of water science, ShahidChamran university of Ahvaz and hydraulic parameters of soil obtained from RETC. Statistical model in the form of a random full base plan with four attendants for irrigating water saltiness including salinity S1 (Karoon River water with salinity 3 ds/m as a control treatment), S2 (S1 +0/5), S3 (S1 +1) and S4 (S1 +1/5) dS/m, in 3 repetition and in 3 intervals of 10 cm emitter, 20 cm emitters on the stack, at a depth of 0-90 cm (instead of each 30 cm) from soil surface and intervals of 30, 60 and 90 days after modeling cultiviation was done. The cultivation way was done handheld in plots including four rows of 3 m in distance of 75 cm rows and with denseness of 80 bushes in a hectar. Drip irrigation system was of type strip with space of 20 cm pores. The results of this section of work have shown in the form of chart drawing and calculating identity indices or recognition (R2), maximum error (ME), normalized root mean second error (NRMSE) and coefficient of residual mass (CRM) in the distances on the stack, 10 and 20 cm dropper. The amount of R2, ME, NRMSE and CRM in 10 cm dripper were calculated to be 0/81, 0/46, 11/77 and 0/018 mg/cm3, in 20 cmdripper 0/78, 0/48, 16/44 and 0/1172 mg/cm3 and on the stack 0/75, 2/8, 18/19 and 0/07 mg/cm3. The highest recognition factor was a distance of 10 cm dripper (81 percent) and then reduces to keep distance from dripper recognition factor. This subject is the highest potency close to the dripper. This can happen for less saltiness in the spaces close to the dripper according to drip irrigation features. The high ME amount shows the less attendance computing of the model, it comes to it’s maximum on the stack, however (2/8 mg/cm3), the distances near to the dripper the obtained ME amount shows the good care in estimating soil saltiness. Also, based on being positive CRM parameter amount was seen. It is less in the amount observed in anticipating of saltiness in the anticipated amount. By considering NRMSE factor, higher amount of anticipating is based on observations. Generally, the results obtained from stimulating of SWAP show that this model can stimulate saltiness distribution in soil under drip irrigation with salty water. This model can be used as useful tools for evaluation of saltiness distribution around the dripper.

Water and soil retention curve is one of the most important properties of porous media to obtain in a laboratory retention curve and time associated with errors. For this reason, researchers have proposed techniques that help them to more easily acquired characteristic curve. One of these methods is the use of fractal geometry. Determining the relationship between particle size distribution fractal dimension (DPSD) and fractal dimension retention curve (DSWRC) can be useful. However, the full information of many soil data is not available from the grading curve and only three components (clay, silt and sand) are measured.In recent decades, the use of fractal geometry as a useful tool and a bridge between the physical concept models and experimental parameters have been used.Due to the fact that both the solid phase of soil and soil pore space themselves are relatively similar, each of them can express different fractal characteristics of the soil. This study aims to determine DPSD using data soon found in the soil and creates a relationship between DPSD and DSWRC. To do this selection, 54 samples from Northern Iran and the six classes loam, clay loam, clay loam, sandy clay, silty loam and sandy loam were classified. To get the fractal dimension (DSWRC) Tyler and Wheatcraft (27) retention curve equation was used.Alsothe fractal dimension particle size distribution (DPSD) using equation Tyler and Wheatcraft (28) is obtained.To determine the grading curve in the range of 1 to 1000 micron particle radius of the percentage amounts of clay, silt and sand soil, the method by Skaggs et al (24) using the following equation was used. DPSD developed using gradation curves (Dm1) and three points (sand, silt and clay) (Dm2), respectively. After determining the fractal dimension and fractal dimension retention curve gradation curve, regression relationship between fractal dimension is created. The results showed that the fractal dimension of particle size distributions obtained with both methods were not significantly different from each other. DSWRCwas also using the suction-moisture. The results indicate that all three fractal dimensions related to soil texture and clay content of the soil increases. Linear regression relationships between Dm1 and Dm2 with DSWRC was created using 48 soil samples in order to determine the coefficient of 0.902 and 0.871. Then, based on relationships obtained from the four methods (1- Dm1 = DSWRC, 2-regression equationswere obtained Dm1, 3- Dm2 = DSWRC and 4. The regression equation obtained Dm2. DSWRC expression was used to express DSWRC. Various models for the determination of soil moisture suction according to statistical indicators normalized root mean square error, mean error, relative error.And mean geometric modeling efficiency was evaluated. The results of all four fractalsare close to each other and in most soils it is consistent with the measured data. Models predict the ability to work well in sandy loam soil fractal models and the predicted measured moisture value is less than the estimated fractal dimension- less than its actual value is the moisture curve. In this study, the work of Skaggs et al. (24) was used and it was amended by Fooladmand and Sepaskhah (8) grading curve using the percentage of developed sand, silt and clay. The fractal dimension of the particle size distribution was obtained.The fractal dimension particle size of the radius of the particle size of sand, silt and clay were used, respectively.In general, the study of fractals to simulate the effectiveness of retention curve proved successful. And soon it was found that the use of data, such as sand, silt and clay retention curve can be estimated with reasonable accuracy.

Planning and management of water resource and river basins needs use of conceptual hydrologic models which play a significant role in predicting basins response to different climatic and meteorological processes. Evaluating watershed response through mathematical hydrologic models requires finding a set of parameter values of the model which provides thebest fit between observed and estimated hydrographs in a procedure called calibration. Asmanual calibration is tedious, time consuming and requires personal experience, automaticcalibration methods make application of more significant CRR models which are based onusing a systematic search procedure to find good parameter sets in terms of at least oneobjective function.

Conceptual hydrologic models play a significant role inpredicting a basin’s response to different climatic and meteorological processes within natural systems. However, these models require a number of estimated parameters. Model calibration is the procedure of adjusting the parametervalues until the model predictions match the observed data. Manual calibration of high-fidelity hydrologic (simulation) models is tedious, time consuming and sometimesimpractical, especially when the number of parameters islarge. Moreover, the high degrees of nonlinearity involved in different hydrologic processes and non-uniqueness ofinverse-type calibration problems make it difficult to find asingle set of parameter values. In this research, the conceptual HEC-HMS model is integrated with the Particle Swarm Optimization (PSO) algorithm.The HEC-HMS model was developed as areplacement for HEC-1, which has long been considered as astandard model for hydrologic simulation. Most of thehydrologic models employed in HEC-HMS are event-basedmodels simulating a single storm requiring the specificationof all conditions at the beginning of the simulation. The soil moistureaccounting model in the HEC-HMS is the onlycontinuous model that simulates both wet and dry weatherbehavior.Programming of HEC –HMS has been done by MATLAB and techniques such as elite mutation and creating confusion have been used in order to strengthen the algorithm and improve the results. The event-based HEC-HMS model simulatesthe precipitation-runoff process for each set of parameter values generated by PSO. Turbulentand elitism with mutation are also employed to deal with PSO premature convergence. The integrated PSO-HMS model is tested on the Kardeh dam basin located in the Khorasan Razavi province.

Input parameters of hydrologic models are seldomknown with certainty. Therefore, they are not capable ofdescribing the exact hydrologic processes. Input data andstructural uncertainties related to scale and approximationsin system processes are different sources of uncertainty thatmake it difficult to model exact hydrologic phenomena.In automatic calibration, the parameter values dependon the objective function of the search or optimization algorithm.In characterizing a runoff hydrograph, threecharacteristics of time-to-peak, peak of discharge and totalrunoff volume are of the most importance. It is thereforeimportant that we simulate and observe hydrographs matchas much as possible in terms of those characteristics. Calibration was carried out in single objective cases. Model calibration in single-objective approach with regard to the objective function in the event of NASH and RMSE were conducted separately.The results indicated that the capability of the model was calibrated to an acceptable level of events. Continuing calibration results were evaluated by four different criteria.Finally, to validate the model parameters with those obtained from the calibration, tests perfomed indicated poor results. Although, based on the calibration and verification of individual events one event remains, suggesting set is a possible parameter.

All events were evaluated by validations and the results show that the performance model is not desirable. The results emphasized the impossibility of obtaining unique parameters for a basin. This method of solution, because of non-single solutions of calibration, could be helpful as an inverse problem that could limit the number of candidates. The above analysis revealed the existence of differentparameter sets that can altogether simulate verificationevents quite well, which shows the non-uniqueness featureof the calibration problem under study. However, the methodologyhas benefited from that feature by finding newparameter intervals that should be fine-tuned further inorder to decrease input and model prediction uncertainties.The proposed methodology performed well in the automatedcalibration of an event-based hydrologic model;however, the authors are aware of a drawback of the presentedanalysis – this undertakingwas not a completely fair validationprocedure. It is because validation events represent possiblefuture scenarios and thus are not available at the time ofmodel calibration. Hence, an event being selected as a validationevent should not be used to receive any morefeedback for adjusting parameter values and ranges.However,this remark was not fully taken into consideration, mostlybecause of being seriously short of enough observed eventsin this calibration study. Therefore, the proposed methodology,although sound and useful, should be validated inother case studies with more observed flood events.

The accumulation of heavy metals (HMs) in the soil is of increasing concern due to food safety issues, potential health risks, and the detrimental effects on soil ecosystems. HMs may be considered as the most important soil pollutants, because they are not biodegradable and their physical movement through the soil profile is relatively limited. Therefore, root uptake process may provide a big chance for these pollutants to transfer from the surface soil to natural and cultivated plants, which may eventually steer them to human bodies. The general behavior of HMs in the environment, especially their bioavailability in the soil, is influenced by their origin. Hence, source apportionment of HMs may provide some essential information for better management of polluted soils to restrict the HMs entrance to the human food chain. This paper explores the applicability of multivariate statistical techniques in the identification of probable sources that can control the concentration and distribution of selected HMs in the soils surrounding the Zanjan Zinc Specialized Industrial Town (briefly Zinc Town). The area under investigation has a size of approximately 4000 ha.It is located around the Zinc Town, Zanjan province. A regular grid sampling pattern with an interval of 500 meters was applied to identify the sample location, and 184 topsoil samples (0-10 cm) were collected. The soil samples were air-dried and sieved through a 2 mm polyethylene sieve and then, were digested using HNO3. The total concentrations of zinc (Zn), lead (Pb), cadmium (Cd), Nickel (Ni) and copper (Cu) in the soil solutions were determined via Atomic Absorption Spectroscopy (AAS). Data were statistically analyzed using the SPSS software version 17.0 for Windows. Correlation Matrix (CM), Principal Component Analyses (PCA) and Factor Analyses (FA) techniques were performed in order to identify the probable sources of HMs in the studied soils. Comparing the measured HMs contents with their normal range in uncontaminated soils demonstrated the contamination of soils by Pb, Zn and Cd, with average concentrations of 152.8, 294.2 and 5.6 mg kg-1, respectively,whereas Ni and Cu did not show any pollution risk. The total concentration of Zn, Pb and Cd in the soil showed a great degree of variability, indicated by large coefficients of variation (CV) from 228.5 % of Cd to 354.8 % ofPb. These elevated CVs may indicate that these elements’ distribution in the studied area is influenced by an anthropogenic source. In contrast, the relatively low calculated CVs for Ni and Cu may imply that natural sources are responsible for these elements’ distribution in the studied soils. Correlation matrix (CM) analysis revealed high correlation coefficients between Zn-Cd and Ni-Cu, indicating the influence of the same factors in controlling their distribution. On the other hand, Pb contents showed low correlation with Ni and Cu values, whereas its correlation with Zn and Cd was relatively high. Therefore, it seems that Pb distribution in the studied soils is more influenced by the factor which controls the Zn and Cd distribution, rather than another factor that is responsible for accumulation of Ni and Cu in the studied soils. According to the PCA analysis, two significant components were extracted explaining about 84% of total variance. FA analysis showed that studied variables have a relatively high communality with two extracted principal components, indicating that almost all of the measured total variation can be efficiently explained by the extracted principals. Industrial activities in the Zinc Town seem to be the main factor which caused the high concentrations of Pb, Zn and Cd in the soil environment in this area; whereas Ni and Cu were associated with the natural sources including geology of the studied area (parental material’s factor). The obtained results from this study coincide with the prior studies indicating that multivariate statistics is a powerful technique for identification of probable sources of HMs in the soil. The studied soils are classified as polluted soils with Zn, Pb and Cd,whereas Ni and Cu did not show any pollution risk. PCA and correlation analyses between HMs indicated that HM pollution in the studied area may originate from natural and anthropogenic factors. It can be concluded that Zinc Town controls the distribution of Zn, Pb and Cd in the surrounding soils, but Ni and Cu distribution in the studied area is mainly influenced by natural factors.Totally, industrial activities related to Zn production caused simultaneous entrance of several HMs to the adjacent soils and led to degradation of the lands in the studied area.

Field plots are widely used in studies related to the measurements of soil loss and modeling of erosion processes. Research efforts are needed to investigate factors affecting the data quality of plots. Spatial scale or size of plots is one of these factors which directly affects measuring runoff and soil loss by means of field plots. The effect of plot size on measured runoff or soil loss from natural plots is known as plot scale effect. On the other hand, variability of runoff and sediment yield from replicated filed plots is a main source of uncertainty in measurement of erosion from plots which should be considered in plot data interpretation processes. Therefore, there is a demand for knowledge of soil erosion processes occurring in plots of different sizes and of factors that determine natural variability, as a basis for obtaining soil loss data of good quality. This study was carried out to investigate the combined effects of these two factors by measurement of runoff and soil loss from replicated plots with different sizes. In order to evaluate the variability of runoff and soil loss data seven plots, differing in width and length, were constructed in a uniform slope of 9% at three replicates at Koohin Research Station in Qazvin province. The plots were ploughed up to down slope in September 2011. Each plot was isolated using soil beds with a height of 30 cm, to direct generated surface runoff to the lower part of the plots. Runoff collecting systems composed of gutters, pipes and tankswere installed at the end of each plot. During the two-year study period of 2011-2012, plots were maintained in bare conditions and runoff and soil loss were measured for each single event. Precipitation amounts and characteristics were directly measured by an automatic recording tipping-bucket rain gauge located about 200 m from the experimental plots. The entire runoff volume including eroded sediment was measured on storm basis using the collection tanks. The collected runoff from each plot was then mixed thoroughly and a sample was taken for determining sediment concentration by weight. The per-storm soil loss was then obtained. A wide range of rainfall characteristics were observed during the study period.The results indicated that the maximum amount of coefficients of variation (CVs) for runoff and soil loss from replicated plots were 60 and 80 percent, respectively, which were considerably higher than the variability of soil characteristics from these plots. CV of runoff and soil loss data among the replicates decreased as a power function of mean runoff (R2= 0.661, P.

Spatial variation of soil properties is significantly influenced by numerous environmental factors such as landscape features, including position, topography, slope gradient and aspect, parent material, climate and vegetation. Soil properties vary spatially in south- and north-facing hill slopes. This factor (different slope aspects) can affect the distribution of soil organic matter, the presence or absence of a layer, pH, nutrient levels, soil mineralogical and micromorphological properties. Topographic factors such as the orientation of the hill slope and the steepness of the slope affect microclimate, vegetation establishment, water movement and erosion. Aspect and slope control the movement of water and materials in a hill slope and contribute to differences in soil properties. Temperature, precipitation and climate vary with elevation and influence pedogenic processes. Accelerated rates of weathering and soil development were found to occur in soils on south-facing slopes. Slopes with a south aspect are dominated by stone and bare soil patches, while slopes with a north aspect are dominated by biotic components. Northern slopes have higher productivity and species diversity compared to Southern slopes. Slope aspect has a significant effect on the composition, species richness, structure and density of plant communities, differed significantly between North- and South- facing slopes. In the present study, the effects of two slope aspects on some soil properties and soil evolution was investigated in Northern Rostam Abad region in the Guilan Province. Five profiles in Southern hill slope(South-facing hill slopes) and five profiles in Northern hill slopes(North-facing hill slopes) with 40% slope and same parent material (basaltic andesite) and same plant cover were dug. The elevation of two slope aspects was 240 meters from the sea level. Average annual temperatures and precipitation are16 degrees centigrade and 1359 mm, respectively. Thus, the soil moisture and temperature regimes are udic and thermic, respectively. The physical and chemical analysis were carried out on soil samples including particle size distribution, bulk density, pH, organic carbon, total nitrogen, available phosphor and cation exchange capacity. This study was done in a completely randomized design several observational with five replications. The total of 34 soil samples were collected in the two slope aspect of the profile and all samples were tested and statistical analyzed. For the micromorphological study, thin sections were prepared from undisturbed samples. The samples were impregnated with polyester resin and later sectioned. The thin sections were prepared and analyzed in petrographic microscope equipped with polarized light. The results of multivariable analysis of variance (MANOVA) and Hotteling's T2 showed that there is significant different in soil properties between two hill slopes(p≤0.01). Also, the results of t-test showed the values of pH, content of sand, sand to clay ratio and available phosphorous significantly was higher in Southern hill slope in comparison with Northern hill slope(p≤0.01). Whereas, clay content and cation exchange capacity significantly were higher in Northern hill slope in comparison with Southern hill slope(p≤0.05). Also observed micromorphological studies showed biological activity was stronger in Northern hill slope in comparison with Southern hill slope. Properties observed in thin sections of Northern slope aspect include fungal hyphae, spherical and ellipsoid excrement of microorganisms in root residual (related to oribatid mites) which indicated stronger biology in Northern slope aspect soils as compare to Southern slope aspect soils. Also, more accumulates* of clay inside voids, nodules, fragmented of coating of well-oriented, micro laminated, reddish-brown clay, chamber voids in Northern slope soils toward Southern slope soils were observed. B-fabricobserved in Northern hill slope soils is stipple speckled in surface horizons and in subsurface horizons is grano-striated and stipple speckled and b-fabric observed in Southern hill slopes soils in surface horizons and subsurface horizons is stipple speckled. Higher content of clay, Cation exchange capacity, Accumulation of clay in pores, Fragments of clay coating (papule), chamber pores, Fe/Mn oxide nodule and micro-laminations in Northern hill slope and higher values of pH, higher content of sand, sand to clay ratio and available phosphorous, lithorelict in Southern hill slope showed that weathering was higher in Northern hill slope in comparison with Southern hill slope. Generally, Southern hill slope had less developed soils (Entisols and Udorthents great group) and Northern hill slope had high developed soils (Alfisols and Hapludalfs great group).

Soil structural stability affects the profitability and sustainability of agricultural systems. Particle size distribution (PSD) and aggregate stability are the important characteristics of soil. Aggregate stability has a significant impact on the development of the root system, water and carbon cycle and soil resistance against soil erosion. Soil aggregate stability, defined as the ability of the aggregates to remain intact when subject to a given stress, is an important soil property that affects the movement and storage of water, aeration, erosion, biological activity and growth of crops. Dry soil aggregate stability (Mean Weight Diameter (MWD), Geometric Mean Diameter (GMD)) and Wet Aggregate Stability (WAS) are important indices for evaluating soil aggregate stability.To improve soil physical properties, including modifying aggregate, using various additives (organic, inorganic and chemicals), zeolites are among what has been studied.According to traditional definition, zeolites are hydratealuminosilicates of alkaline and alkaline-earth minerals. Their structure is made up of a framework of[SiO4]−4 and [AlO4]−5 tetrahedron linked to each other's cornersby sharing oxygen atoms. The substitution of Si+4 by Al+3 intetrahedral sites results inmore negative charges and a high cation exchange capacity.Zeolites, as natural cation exchangers, are suitable substitutes to remove toxic cations. Among the natural zeolites,Clinoptilolite seems to be the most efficient ion exchanger and ion-selective material forremoving and stabilizing heavy metals.Due to theexisting insufficient technical information on the effects of using different levels of zeolite on physical properties of different types of soils in Iran, the aim of this research was to assess the effects of two different types of zeolite (Clinoptilolite natural zeolite, Z4, and Synthetic zeolite, A4) on aggregate stability indicesof soil. In this study at first, after preparation of two different types of soil with light and medium texture and doing identification tests such as determination of gradation and hydrometer tests and Atterberg limits, zeolite in four levels, 0 (control), 1%, 5%, and 10%w/w, was mixed with two soil textures (sandy loam and silty loam) in three replications. Then, each treatment was saturated for 48 hours in each month, during 6 months. Dry soil aggregate stability (Mean Weight Diameter (MWD), Geometric Mean Diameter (GMD), and Wet Aggregate Stability (WAS)), were determined. The experiment was carried out using factorial method in a randomized complete design. The results showed that, in sandy loam texture, there was no significant difference between two types of zeolites, their level of using and their interaction on MWD (p

Saffron is one of the most important economic plants in the Khorasan province. Awareness of soil quality in agricultural lands is essential for the best management of lands and for obtaining maximum economic benefit. In general, plant growth is a function of environmental factors especially chemical and physical properties of soil (20). It has been demonstrated that there was a positive and high correlation between soil organic matter and saffron yield. Increasing the yield of saffron due to organic matter is probably due to soil nutrient, especially phosphorous and nitrogen and also improvement of soil physical quality (6, 28, 29). The yield of saffron in soils with high nitrogen as a result of vegetative growth is high (8). Shahandeh (6) found that most of the variation of saffron yield depends on soil properties. Due to the economic importance of saffron and the role of soil properties on saffron yield, this research was conducted to find the relationship between saffron yield and some soil physical and chemical properties, and to determine the contribution of soil properties that have the greatest impact on saffron yield in the Ghayenat area. This research was performed in 30 saffron fields (30 soil samples) of the Ghayenat area (longitude 59° 10΄ 10.37˝ - 59° 11΄ 38.41˝ and latitude 33° 43΄ 35.08˝ - 33΄ 44΄ 02.78˝), which is located in the Khrasan province of Iran. In this research, 21 soil properties were regarded as the total data set (TDS). Then the principal component analysis (PCA) was used to determine the most important soil properties affecting saffron yield as a minimum data set (MDS) and the stepwise regression to estimate saffron yield. To estimate the yield of saffron in stepwise regression method, saffron yield was considered as a dependent variable and soil physical and chemical properties were considered to be independent variables. According to the PCA method, among the 21 studied properties, 7 out of them including calcium, iron, zinc contents, sand, calcium carbonate equivalent percent, mean weight diameter of aggregates (MWD) and manganese (Mn) had the higher Eigenvalues. Therefore, the above properties were introduced as the most important soil properties in saffron fields. Calcium carbonate had the negative effect on the availability of micro-nutrients (26). Christensen et al. (15) found that by increasing the calcium carbonate in soil due to high pH and formation of insoluble components, the uptake of micro-nutrients is especially limited. The results of stepwise regression method (equation 1) showed that soil acidity (pH), zinc content, bulk density, MWD, iron content, salinity (EC), organic carbon and available potassium in soil were the most important properties that affect the yield of saffron, so that the determination coefficient (R2) of the regression model was high (Table 2) and it can explain 74% of the variation of saffron yield. Y = 6924.51 – 1187.31 pH – 89.65 EC + 71.6 Fe – 826.02 Zn + 471.55 OC, + 5490.96 K + 1353.56 BD + 752.82 MWD (1) where Y: saffron yield (kgha-1), pH: soil acidity, EC: electoral conductivity (dSm-1), Fe: iron concentration (mgkg-1), Zn: zinc concentration (mgkg-1), OC: organic carbon (%), K: soil potassium (%), BD: soil bulk density (Mgm-3), and MWD: mean weight diameter of aggregates (MM). Based on the absolute values of standard ß in the regression model (Table 3), pH value and then after Zn concentration had the most effect on saffron yield. In general, responses of different plants to soil pH is varied, and saffron grows satisfactory in pH = 7.8 (5). Soil pH influences the uptake of soil nutrients by plants (15), so that this parameter had the most effect on saffron yield and by increasing the soil pH, the yield of saffron decreases. According to the regression model, Zn concentration was the second parameter in saffron yield. Zn has the important role in structure of plant enzymes (30). After these 2 parameters, Bd, MWD, Fe concentration, EC, Organic carbon and K concentration in soil had more effect on saffron yield (Table 3). According to both PCA and regression methods, the concentration of iron and zinc and MWD were determined as the important and effective soil properties on saffron yield in the Ghayenat area. In addition, soil pH in stepwise regression method and calcium carbonate in PCA method were determined as the effective properties on saffron yield. Therefore, it is suggested that the parameters of Zn, Fe, and MWD along with soil pH and calcium carbonate which were regarded individually in two methods, were considered as the most soil properties in saffron yield.

Estimation of cation exchange capacity (CEC) with reliable soil properties can save time and cost. Pedotransfer function (PTF) is a common method in estimating certain soil properties (e.g. CEC) that has been wieldy used for many years. One of the common techniques that have been used to develop PTFs is multiple linear regressions. In this method, all easily obtained soil properties are linearly related to certain soil properties. In addition to multiple linear regressions method, more complex techniques such as artificial neural networks and regression tree have been used to develop PTFs. The regression tree method is a well-known method for analyzing the environmental science which determines optimal separation point of independent variables.The purposes of this study were to evaluate and compare tree and multiple linear regressions in estimating cation exchange capacity with reliable soil properties. For this work, 106 soil samples of Unsaturated Soil hydraulic database (UNSODA), which contain a wide range of soil texture classes, were used. The examples were divided into 2 sets including 81 and 25 soil samples for developing and validating multiple linear regression and tree regression, respectively. For estimating CEC with tree and multiple regressions, soil texture properties, organic matter, pH and bulk density were used. To develop multiple linear regressions and create the tree structure, at first, correlation between cation exchange capacity with other soil properties were evaluated; then, soil properties that had significant correlation were chosen to introduce software. As well, the suggested linear function and tree structure were compared with 2 famous pedotranser functions including Bell and Van-kolen and Breeuwsma et al., which have been used for estimating CEC.For investigating the performance of multiple linear regression and tree regression to estimate CEC 1:1 lines, determination coefficient (R2), mean error (ME), root mean square error) RMSE), and geometric mean error (GMER) were used. Statistica 8.0 software that was developed by ESRI was used to develop multiple linear regressions and generate tree structure. The results showed for developing multiple linear regression model to estimate CEC among all inputs parameters (sand, silt, clay, organic matter, pH and bulk density) only just two parameters including organic (with r=0.70) and clay percentage (with r=0.59) had a significant coefficient, so organic and clay percentage appeared, and suggested multiple linear regression models based on this two parameters, with coefficient of 3.183 and 0.274, respectively, were developed. Also, only organic matter and clay percentage from inputs parameter in tree were shown. In tree structure most nods were divided into 2 Childs nods based on organic matter and only in the left side of tree structure in the second level clay percentage was appeared. Regression tree in two data sets (validation and development) based on R2, RMSE, ME and GMER had a high quality for CEC estimation than regression methods. Proposed linear regression model had high performance than Bell and Van-kolen and Breeuwsma et al. to estimate CEC. The main aim of this study was to investigate the efficiency of multiple linear regression model and regression tree to predict cation exchange capacity (CEC) based on relationships between CEC and easily measurable soil properties. For this work, 106 soil samples of UNSODA data set were used. Results showed that just clay percentage and organic matter that had higher correlation with CEC appeared in suggested linear regression and tree structure. Based on 1:1 lines, R2, RMSE, ME and GMER, tree regression model had higher performance than all linear regression models (suggested function, Bell and Van-kolen and Breeuwsma et. al.) to estimate cation exchange capacity. As well, suggested function had more efficiency than Bell and Van-kolen and Breeuwsma to predict CEC.

Recently, air pollution due to the occurrence of dust storms is one of the worst environmental problems in Western and Southwestern Iran, especially the Khuzestan Province (12, 13). According to the reports of the Meteorological Organization of Iran the average number of dusty days in the cities of Ahvaz and Abadan in the Khuzestan Province reaches 68 and 76 days each year, respectively (6). Previous studies have shown that the yearly damage costs of wind erosion and occurrence of dust storms in the Khuzestan Province reach about 30 Billion Rials (5). However, very few studies have been conducted on the characterization of dust particles and also the identification of their origins in Iran, especially the Khuzestan Province. Hojati et al. (10) reported that dust deposition rate, mean particle diameter, and concentration of soluble ions in samples taken from Isfahan and Chaharmahal and Bakhtiari Province decrease with altitude, with a significantly lower gradient in periods with dust storms. They reported three factors that control the rate and characteristics of dust deposited across the study transect: 1) climatic conditions at the deposition sites, 2) distance from the dust source, and 3) differences between local and transboundary sources of dust.Therefore, this study was conducted to investigate the effects of dust storms on deposition rate, mineralogy and size distribution patterns of dust particles from twelve localities around the Houralazim lagoon.

Dust samples were collected monthly during a 6 month experiment from August 2011 to February 2012. In order to differentiate between the contribution of dust production by local soils and other sources, surface soils were also sampled from the vicinity of the dust sampling sites. The collection trays were made of a glass surface (100 × 100 cm) covered with a 2 mm-sized PVC mesh on the top to form a rough area for trapping the saltating particles (Fig. 2). Dust samples were collected by scraping materials adhered to the glass trays using a spatula. All the trays were wet cleaned before the next collection. The collected dust and soil samples were examined for their grain size distribution using a Malvern Hydro 2000g laser particle size analyzer, as well as their mineral compositions by a Philips PW1840 X-ray diffractometer and a LEO 906 E transmission electron microscope (TEM).

The results showed that wind speed and direction patterns during the periods with dust storms and those without dust storms were different. Accordingly, in periods with dust storms (3, 5 and 6) the contribution of winds with speeds greater than 11.1 m/sec, especially from the Northwest direction, increased when compared with those from the periods without dust storms (1, 2 and 4). Besides, the direction of prevailing winds in periods without dust storms were mainly from the West and the Northwest. However, in periods with dust storms East-directed winds were also observed (Fig. 3). These show that the source areas of dust particles in these periods are probably different. The results also illustrated that the average amount of deposited particles in the periods with dust storms (12.5 g m-2 month-1) was considerably more than that of the periods without dust storms (7.5 g m-2 month-1) (Figs. 4 and 5). The difference in dust deposition rate between periods having dust storms and those without dust storms seems to be due to dust input from a source outside the study area. Particle size distribution analysis showed that dust particles collected from the study area in both periods (with and without dust storms) are mainly silt-sized particles. This fraction contributes to 60 to 76 % of the particles collected from periods without dust storms and 66 to 82 % of particles affected by dust storms (Table 2). The results also imply that in both periods (with and without dust storms), dust particles collected from the study area had a bimodal distribution pattern which suggests mixing of settled particles from different sources and/or deposition processes (Fig. 6). Mineralogical composition of dust particles were collected from both periods (with and without dust storms) and those from the soils contained quartz, calcite, feldspar, halite, dolomite and palygorskite (Figs. 7 and 8). Moreover, the TEM images of dust particles collected in periods with dust storms showed higher amounts of palygorskite than in periods without dust storms (Fig. 9).

The similarity in the physical properties of local soils and deposited particles of the periods with and without dust storms implies that the contribution of local soils and sediments in producing dust particles is high. However, it seems that in periods with dust storms the contribution of a transboundary origin such as Iraqi arid lands in producing dust particles increases.

Recycling organic wastes has vital roles in sustainable agriculture, reducing pollutants in the environment, and nutrient enrichment of soils. Compost is the product of recycling organic waste through anaerobic treatment, which can be a good alternative.Again the use of chemical fertilizers is inappropriate. Vinasse is brown material and it is a product of industrial production of alcohol from molasses. Vinasse, a by-product of ethanol production from molasses, is a highstrength effluent with a high content of organics, mainly organic acids, reducing substances, cultured matter and glycerol. The wastewater is characterized by high concentrations of potassium, calcium, chloride and sulphate ions, a high content of suspended solids, a high CoD (Chemical oxygen Demand) level and a high temperature at the moment of generation.Vinasse can be used as a supplement for enhancing compost fertilizer quality, because it has plenty of organic matter and minerals. This research was done with the purpose of surveying application of vinasse in different levels on indices of compost producing (temperature, microbial population, nitrogen, carbon, the ratio C/N, nitrate, pH and EC) and producing time in different phases (during the production and after compost production) for 5 months in the waste resumption complex of Aradkooh in Tehran. The method used for compost production from solid waste material was ventilating the fixed mass. In this research, the volume of ventilation was 0.6 lit air for 1 lit waste material in a minute.Four different treatments (each three replicates) were applied to the compost:C0 without vinasse (control), C1, C2 and C3, respectively 10, 20 and 30 ml vinasse per kg waste material. The following factors were measured during each phase: Total-N was measured by the Kjeldahl method and organic carbon was measured by the Walkley-Black method. Thermometers were used for temperature monitoring at different locations in the riff-raff. The microbial population size was obtained by the CFU method.Electrical conductivity and pH of the water extracts from the samples were determined by shaking the samples mechanically with distilled water at a solid-to-water ratio of 1:10 (w/v). Additionally, NO3–N was determined by spectrophotometric method. At the beginning of this study, theresults showed that, after the formation of the riff-raff, temperature was increasing rapidly all over the riff-raff, which indicates a specified microbial activity. Minimum time to reach the thermophilic temperature, 30 ml per kilogram of vinasse raw materials, was for (C3) and maximum of them was for the control treatment (C0). Adding vinass in the second phase led to an increase in the compost mass temperature. Treatment C3 with the highest and treatment C0 has the lowest microbial populations. Total nitrogen content increased during composting of the waste materials in comparison with its initial concentration. In both phases treatment C3 has the highest and treatment C0 has the lowest total nitrogen content. According to results of the measurements of organic carbon in the first phase, at the beginning of composting process, most of the organic matter was in treatment C3and the lowest organic matter was in C0. However, with increasing the composting process, the vinass treatment had lost jts organic carbon with more gradient. In the second phase by adding vinass, the originally organic carbon increased because of the high levels of organic matter. But,with further vinass treatment, they lost their organic carbon more vigorously. During five months,changes in the ratio of carbon to nitrogen C/Nwas variable. In vinass treatment, the ratio ofC/N increased more vigorously until it reached one quarter and then it fell less sharply. In the first month, this ratio fell less sharply in the control group, and in the final months it fell with more intensity. In the second phase, decreasing the ratio of carbon to nitrogen was observed and the decrease treatment was more than the other treatments. The monthly analysis of riff-raff samples showed that the higher increase in pH mostly occurs in the first month, and in all cases the value of the electrical conductivity increased during composting. Until the second month of pH and EC treatment, C3 and C2 increased and decreased in the third to fifth months.In the second phase pH at vinasse treatment increased and pH at C0 treatment decreased. Maximum amount of nitrate was observed at C3 treatment and at Epsom salt phase nitrate has the maximum amount. Eventually, it is recognized that treatment C3 and C2it is adequate to add context of organic waste and this treatment decreases the production time of compost up to two months.The second phase was not suitable compared with the first phase due to the inability of increasing nitrate-nitrogen and pH.

Sulfur is the key element for higher crops and plays an important role in the formation of proteins, vitamins, and enzymes. It is a constituent of amino acids such as cysteine and methionine, which act for the synthesis of other compounds containing reduced sulfur, such as chlorophyll and utilization of phosphorus and otheressential nutrients.Deficiency of this nutrient in soil is usually compensated by using chemical fertilizers. However, these fertilizers have harmful effects on the environment and decrease the quality of the agriculture products. Therefore, biological fertilizers are more useful for using in agricultural ecosystems.Sulfurshould be addedto the soil, usually in a reduced form such as elemental sulfur. Use of S oxidizers enhances the rate of natural oxidation of S and speeds up the production of sulfates and makes them available to plants consequently resulting in an increased plant yield. The role of chemolithotrophic bacteria of the genus Thiobacillus through oxidation process in the soil is usually emphasized. Sulfur oxidation is the most important step of sulfur cycle, which improves soil fertility. The result is formation of sulfate, which can be used by the plants, while the acidity produced by oxidation helps to solubilize nutrients in alkaline soils. These bacteria can solubilise the soil minerals through the production of H2SO4 that reacts with these non-soluble minerals and oxidised them to be available nutrients to the cultivated plants. Arbuscular MycorrhizalFungi isan important component ofthe microbiota, mutualistic symbioticsoilfungithatcolonizesthe rootsofmost cropplants.The AM symbiosis involves an about 80% of land plant species and 92% of plant families. They have theability to enhance host uptake of relativelyimmobile nutrientsparticularly phosphorus (P) andzinc (Zn),Manganese (Mn) andiron(Fe).Arbuscular mycorrhizal fungi increased plant uptake of phosphorus, nitrogen and water absorption. Inoculation withthesefungihas increased the yield of numerous field-grown crops. This study was aimed to evaluate the effects of thiobacillus bacteria and sulfur application on soil pH, and also their interactions with mycorrhizal fungi in order to improve nutrients uptake and grain yield of maize under alkaline soil condition. Treatments arranged as factorial experiment were based on RCBD with three replications. Treatments consisted of mycorrhizal inoculation: inoculated (m1) and non-inoculated (m0), thiobacillus in two levels of inoculated (t1) and non-inoculated (t0) and three levels of sulfur (S0: 0 kg.ha-1, S1: 250 kg.ha-1 and S2: 500 kg.ha-1). Four-row plots were prepared with row width and intra-row space of 60 and 20 cm, respectively. Seeds of maize (Zea Mays, Sc:647) were surface sterilized in a 10% (v/v) solution of hydrogen peroxide for 10 min, were rinsed with sterile distilled water. Before sowing, 300 kg of urea per hectare were applied according to the results of soil analysis. In order to facilitate oxidation of sulfur to sulfate form,, S was applied and thoroughly mixed into top 30 cm of soil 30 days before sowing. One week before sowing, thiobacillus (Thiobacillus thiooxidans) was inoculated. Inoculum of AM fungus Glomus intraradices, were added to soil just before planting at about 2 centimeters below seed sowing dept. To measure Arbuscular Mycorrhizal colonization, root plants collected one week before harvesting, cleared in 10% KOH at 80˚C for 2 h, and then acidified in 1% HCL for 60 min. Then the cleared roots were stained in a solution of Trypan blue. For nutrient analysis, the following procedure was applied. Zn, Fe, S, and P were determined by Inductively Coupled Plasma-atomic emission spectrometry apparatus. For this purpose, ash of seed samples was prepared at 500-550 degree of Celsius and then 5 ml of HCl 37% was added and with dionized water to reach to 50 ml. Kjeldahl method was used to determine nitrogen. Analysis of variance was performed on all experimental data and means were compared using the least Significant Differences (LSD) test with SAS software. The significance level was p>0.05 unless stated otherwise. Results showed sulfur application increased significantly the amount of S, P, N, Fe, Zn, shoot dry weight and leaf chlorophyll of maize. With increasing Sulfur, sulfur concentration in plant shoot increased with linear trend. The highest S concentration was obtained with 200 mg.kg-1 S and the lowest amount was obtained from control plots. Applications of 50, 100, 150 and 200 mg.kg-1 S increased P content about 0.45, 3.91, 4.74 and 5.56 %, respectively. The highest N contentwas obtained with 100 mg.kg-1 S. The thiobacillus significantly increased P, Fe, Zn anddecreased root colonization and soil pH compared to control. Thiobacillus bacteria increased shoot P only with application of 100 mg.kg-1 S. Mycorrhizal inoculation increased the amount of N, P, S, Fe, Zn, shoot dry weight and root colonization. Inoculation with G.intra and G.mosseae increased shoot P content about 4.18 and 3.34% in comparison with the control plots. Single or combination of sulfur and thiobacillus had a negative impact on the root colonization. Based on the results it seems that sulfur, thiobacillus and mycorrhiza in alkaline soils improved crops nutrition and growth. S application and thiobacillus interaction on S concentration of maize shoot were significant. In condition of 0 or 50 mg.kg-1 S application, inoculation of thiobacillus is recommended. Also, the effects of mycorrhiza on P shoot was significant with no application of S.

Weather features and their variations have an important role in the yield of agricultural products, especially in rain-fed conditions. The main metrological variables that affected yields consist of precipitation, temperature, soil moisture and solar radiation. Also, drought is one of the major constraints to production, especially the mid-season drought which occurs during the podand seed formation stages and the terminal drought which occurs during the pod filling stage. The results of investigating the relation between drought indices such as Standardized Precipitation Index (SPI), Palmer Drought Severity Index (PDSI), Crop Moisture index (CMI) and Z index with crop yields indicated the capability of these indices to estimate variations in crop yields. The objective of this study in the first step is investigation of relations among wheat and barley crop yields with climatic variables and SPI and RDI drought indices based on Principle Component Analysis (PCA) method at Bojnourd, Mashhad and Birjand stations. In addition, by selecting the prominent variables via PCA method, the best models of estimating each crop’s yield based on multivariate regression methods at selected stations were determined. In this study, the relationship between yields of rain-fed wheat and barley with weather variables consisting of minimum, mean and maximum temperature, precipitation, evapotranspiration and drought indices including SPI and RDI were investigated and modeled at Bojnourd, Mashhad and Birjand stations. For this purpose, the values of each variable were calculated for 34 time scales of 1, 2, 3, 4, 6, and 9 months and wet periods (nine 1-month periods, eight 2- month periods, seven 3- month periods, six 4- month periods, two 6- month periods, one wet period (5 or 7-month) and one 9-month period). After that, the main influencing variables were chosen among investigated time periods for each variable by using the method of principal component analysis (PCA). In continuation, the selected variables via PCA technique were used in the multivariate regression methods to create the best model of predicting wheat and barley yields based on each mentioned variable and combination of them. The performance of the established model was evaluated based on Ideal Point Error (IPE) criteria and the best predicting model of wheat and barley was selected for each region. The results showed that applying PCA technique as a powerful statistical tool leads to decrease of the error and inflation of constructed models. This is done by reducing the volume of data and selecting influencing variables. Based on the PCA results by choosing only four components the 90 percent and greater than variation of crop yields are estimated and the first component includes time periods of spring and winter months. Investigation of the results of the best model at the given stations based on IPE criteria show that the constructed models based on variables of SPI index have more accuracy for predicting yields of wheat and barley at station of Bojnourd, at Mashhad station the created models based on a combination of variables and at Birjand station a model based on a combination of variables and a created model according to RDI variables was used that has more accuracy for predicting yields of wheat and barley, respectively. Comparing the estimated and actual values of wheat and barley yields indicate that the correlation coefficients of the models when applied to estimate the yield of wheat and barley at Bojnourd station resulted in 68 and 69 percent, at Mashhad station 89 and 86 percent and at Birjand station 66 and 74 percent, respectively.The performance evaluation graph shown in Fig. 1 can be used to illustrate model performance and to diagnose model bias. According to the results, a relation between crop yields and combination of metrological variables and drought indices is more positive and stronger than only metrological variables combination. The results showed that the variables of temperature, precipitation and evapotranspiration are to be considered. Also, the evaluation model indicated that the RDI index is more suitable for predicting rain-fed wheat and barley yields.

Over the past hundred years, human activity has significantly altered the atmosphere and increase of concentration of greenhouse gases lead to warm the earth's surface. This global warming leads to change of climatic extreme index and increases the intensity and frequency of occurrence of extreme climate events. Investigation of extreme values for planning and policy for the agricultural sector and water resource management is important.In this study, a comprehensive review of extreme indices of temperature and precipitation are discussed. This paper aims to investigate extreme temperature and precipitation indices defined in accordance with CCL, and the study of other climatic parameters in the North East of Iran. In this research, statistics and data of some stations in the North East of Iran during the period 1992-2012 were used. To evaluate the extreme climate indices trend, 27 indices of rainfall and temperature, were defined by the ETCCDMI. They were calculated by RClimdex software. In this software, prior to the index calculation, data by quality control software became quantitative and incorrect data were controlled and outlier data were examined. The indices were calculated by daily data. 11 rainfall and 16 temperature indices were calculated by this software.The target of the ETCCDMI process is to delineate a standardized set of indices allowing for comparison across regions. These extreme indices were classified in five categories which included the percentile-based extreme indices, the absolute extreme indices, the threshold extreme indices, the periodic extreme indices, and the other indices. They were estimated at the 0.05 significant levels. The Mann-Kendall test was used to investigate the climatic parameters, maximum relative humidity, sunshine duration and maximum wind speed. Thermal analysis results are consistent with warming patterns, and they have showed that hot extremes indices have increased. Hot days index (SU25), shows a significant positive trend in all studied stations. Number of tropical nights has a positive trend in all stations. Hot day frequency (TX90P) and hot night frequency (TN90P) in all stations show a positive trend, indicating an increase in the number of warm days and nights. Cold extreme indices show a decreasing trend. (TX10P) and (TN10P) show significant negative trends in all stations and indicate a decrease in cold days and nights. Number of frost day index shows a decreasing trend. Overall, the results revealed a decrease in the severity and frequency of cold events, while warm events during the study period were significantly increased. These results are consistent with the results of the Intergovernmental Panel on Climate Change and global and regional studies. Rising temperatures could lead to increase in the maximum wind speed in the area. In the study of the maximum wind speed process, this trend was observed in most stations, and incremental changes can be associated with a reduction in the maximum relative humidity (which was observed in the results). The sunshine hour parameter depicted a decreasing trend in the most station trend. In the study of all rainfall indices in all studied stations there were a decreasing and negative trend for rainfall, although few significant trends over time were observed. Comparison of years with the highest rainfall and those with the lowest, showed that the amplitude of fluctuations in precipitation in different years is very high and the distribution of rainfall at distinct stations is different. In general, due to the high dispersion and low rainfall in most stations, providing a clear and uniform regional rainfall pattern is not possible. Due to the effects of temperature and precipitation extreme indices in a wide range of human activities, such as agriculture, water management and building design, it is necessary to consider the effects of these extreme climatic events in the future planning and policies in different sectors. Conclusion The results showed that hot extreme indices, such as summer day index, the number of tropical nights, warm days and nights have increased, while, in the period of study, cold extreme indices have decreasing trend, which shows a decrease in the severity and frequency of cold events.The trend of the maximum wind speed was increased in most stations. Rainfall indices show decreasing and negative trends, although over the studied period few significant trends were observed.