نشریه آب و خاک
سال سی و یکم شماره 5 (پیاپی 55، آذر و دی 1396)

The study of flow diversion in open channels which has been, since long, under consideration by hydraulic engineers, is much used to divert flow from a main channel or from a river into an irrigation or hydropower channel. When a water intake with an angle is installed at one side of the channel, the streamlines of the flow deflect towards the intake. As a result, a separation zone is produced in the lateral channel. The separation zone develops in the lateral channel and reduces the discharge capacity and efficiency of water intake by delimiting the channel width available for the flow. Therefore, determination of water intake geometry and flow conditions to produce minimum separation zone is very important and they are the focus of this study. The majority of previous studies was conducted on sharp edged water intake entrances. Therefore, in this study, to find the optimum radius for a round edged entrance water intake, a comprehensive experimental program was carried out in a laboratory flume and the separation zone dimensions and Alpha and Beta coefficients were measured.
The experimental model was built in hydraulics laboratory. The water intake was installed at 55 degrees to the main channel. The main channel consisted of a rectangular cross-section with a base width of 0.5 m, height of 0.4 m and a length of 15.80 m. The lateral diversion channel was 0.25 m wide, 0.40 m high. According to previous experiments that performed by Keshavarzi and Habibi (2005), radii of 10, 15 and 20 cm were selected for the edges of the intakes, upstream of the 55 degree water intake. The velocities of the flow in transverse and flow directions were measured using an electromagnetic velocity meter at three distances Z= 3 cm, 6 cm and 12 cm, in which Z is the distance from the bed. Then the size of the separation zone, Alpha and Beta coefficients were determined.
To find a relationship between the radius of the round edge entrance in the 55 degree water intake and the size of separation, the geometry of the separation zone must be determined. To find the geometry and pattern of separation zone for different flow conditions, the particle traces technique was employed using Tec plot Software version 8.0. In open end flow condition, for discharge ratios of 0.2, 0.4, 0.6 and 0.8, and for the radii of 10, 15 and 20 cm, flow separation occurs at 3 cm and 12 cm distance and only upstream of the intake inlet. The separation size in r=20 cm is less than for other radii. Also, the separation size for Qr = 0.8 is minimized and for Qr =0.2 is the maximum and for r/Wb=0.8, the length and width of separation are minimum. In close end flow condition and for radii of 10, 15 and 20 cm, the size of separation zone at upstream of water intake is much larger than that in downstream. Comparing with the separation length downstream of the intake it can be concluded that with increasing the inlet radius, the separation length upstream of the intake inlet decreases. Therefore, in close end conditions, rounding of the intake inlet is effective to decrease separation length at upstream side of water intake. Also, in close end conditions, flow separation occurs at downstream side of water intake. Furthermore, the separation size for r=20 cm is less than for other radii, therefore, r/Wb=0.8 is the optimum radius ratio with a minimum separation size at the 55 degree water intake.
When a water intake with an angle is installed at one side of the channel, the streamlines of the flow deflect towards the intake. As a result, a separation zone is produced in the lateral channel. The separation zone development in the lateral channel and reduces the discharge capacity and efficiency of water intake by delimiting the channel width available for the flow. In this study, to find the optimum round inlet radius, the experimental tests were carried out at a water intake installed in a rectangular channel with rounded edge with 10, 15 and 20 cm inlet radius. Then separation zone dimensions and alpha and beta coefficients determined. These experiments were carried out in close end and open end flow conditions for diversion flow ratio 0.2, 0.4, 0.6 and 0.8. Using particle trace plot for different flow pattern, the values of length and width of flow separation upstream and downstream of the intake were determined. The result showed that the separation size for Qr = 0.8 is minimized, whereas it is maximum for Qr =0.2. Furthermore, the separation size for r=20 cm is less than for other radius, therefore, r/Wb=0.8 with a minimum separation size was selected as the optimum radius ratio.

The globally growing demand for water has shown the need for its efficient and judicial utilization, and particularly in agriculture being single largest consumer of water. Crop evapotranspiration represents crop water demand and governed by weather and crop conditions and most of the current water demand models are non-spatial models, they use point data. Global scale satellite images can solve these problems. According to the high performance of satellite indices, it is necessary to estimate crop coefficient using combination of reflectance and thermal bands. The aim of this research was to estimate the effective crop coefficient of potato using vegetation indices and principle component analysis.
Principle component analysis (PCA) was used for effective crop coefficient estimation. Modeling of associations between vegetation indices and crop coefficient were conducted using artificial neural network. In the present study, NDVI, RI, EVI, SAVI, MSAVI, NVSWI, TVX, TVI, mNDVI and mTVI were the used as vegetation indices. PCA is designed to transform the original variables into new and uncorrelated variables (axes), namely the principal components, which are linear combinations of the original variables. The new axes lie along the directions of maximum variance. PCA provides an objective procedure of finding indices and information on the most meaningful parameters, which describes a whole data set affording data reduction with minimum loss of original information. Artificial neural networks are a computational model which is based on a large collection of simple neural units, loosely analogous to the observed behavior of a biological brain's axons. RMSE, MAE and MARE were the statistics used for investigating the performance of crop coefficient of vegetation indices with FAO crop coefficient.
Eleven MODIS vegetation indices are derived in the period of 2013 to 2016 for potato over the limited area between Tabriz and Bostanabad. The last year was considered as the validation period. According to the FAO-56 paper, the lengths of initial stage, crop development stage, mid-season stage, late season stage were considered to be 25, 30, 45, 30 days, respectively. The vegetation indices were derived using MODIS sensor with 2×2 pixels. The PCA showed that with increasing the number of components, the eigenvalues decreased. The analysis indicated that the three first components accounted for the 85.45 % of the total variance of data and the eigenvalues of them were greater than 1, the three first components were thus selected. NDVI, RI, TVI, MSAVI and NVSWI in the first component, mNDVI in the second component and LST in the third component had the highest coefficients. NDVI in the first component with high coefficient indicted the importance of index in the crop coefficient determination. The coefficients of SAVI and MSAVI were higher than NDVI. From the three investigations on the kind of principle component, the first investigation led to a 55.75 % decrease in RMSE relative to the second and third investigations. The first and second components together had less error rather than third component. The average of MAE for first, second and third investigations was, respectively, 0.17, 0.22 and 0.2. Therefore, component with exact values of particular vectors resulted in a reduced error. The sensitivity of artificial neural network led to an increase in the simulation accuracy (for example the RMSE decreased from epoch 100 to 50 was 48.27%). Crop coefficient estimation using vegetation indices of principle component analysis was underestimated about 1% in the validation period. Overestimation and underestimation were found in the initial and crop development stages, respectively.
The quantities of statistics showed the improvement of artificial neural network performance with combination of vegetation indices using principle component analysis. The vegetation indices with reflectance bands performed well. The combination of thermal and reflectance bands enhanced the vegetation indices efficiency. In addition to NDVI index for crop coefficient estimation, improvement of indices according to the study area condition increased the indices performance. The kind of mathematical equations of indices can increase the indices performance which using the same bands with different equations have different results. The selected component of principle component analysis has important role in increasing the simulation accuracy. The error reduction of simulated crop coefficients can increase the precision of irrigation consumption and agricultural planning which the principle component analysis has more important role.

The hydraulic parameters are very important for perception of water flow in unsaturated soil and using pollutants and nutrient flow modeling in the soil. The effect of soil management and land uses on soil parameters can directly alter soil hydraulic parameters. Because of interactive and tight relationship between soil and plant covering, studying the soil parameters and its changing during different land uses is vital. The main object of this study was evaluating the effects of different land uses on soil saturated hydraulic conductivity.
This study was performed in about 100 hectare fields of Khezrabad region in the 25 km south of the Jiroft county located in south eastern of Kerman province. The region gridded into 1000×1000 meter grids with use of Google earth and Arc GIS software, sampling places has been selected in the center of each grid. Measurement of soil saturated hydraulic conductivity done with the Guelph permeameter in the center of each grid. For the measurement of physical parameters such as bulk density, percent of sand, silt, clay in the laboratory, sampling done from 30cm depth so samples transferred to the laboratory. In this study in order to ensure the normal distribution of variables, the Kolmogorov-Smirnov test has been used with SPSS14 software. The Kriging method was used for interpolation and providing spatial maps.
Agriculture, garden and sterile lands were selected for the object of the present study. The study area includes garden, agriculture and sterile lands at the same time. The study area contains 3 classes of soil texture as: sandy, sandy-loamy and loamy-sand. The results showed that soil saturated hydraulic conductivity (ks) with strong spatial correlation had a high spatial variability. The fluctuation ranges of its values changes from 0.02 to 2325.71 cm per hour. The lowest value of ks was observed in garden land (by having the lowest value of soil bulk density) while the highest value was observed in sterile land (by having the highest value of soil bulk density). The results also showed that semi-variogram of garden, agriculture and sterile land were not the same, and it may gain from different types of agricultural operations, type of land use and various textures so that from garden land to sterile land, the soil texture becomes lighter and level of saturated hydraulic conductivity changes completely different. Several reasons maybe considered including soil different structures due to different type of agricultural operations and type of cultivation for every single land use. The change process of saturated hydraulic conductivity for garden and agricultural land was identical and for both the Gaussian model were fitted. According to the nugget effect ratio to the sill (C0/C0), variability of saturated hydraulic conductivity in agricultural land has a stronger spatial correlation (0.0006) and also has a higher radius of effect range (11740m) compared to garden land in which the ratio of the nugget effect ratio to sill is 0.28 and its radius of effect range is 8030 meters. the radius of effect range in sterile land had the lowest value among studied land uses, though having strong correlation, the effect range of this correlation is low and, compared to other lands, the changes process was more randomly obtained. To mention the reasons of this finding it is possible to refer to area of the sterile land, dispersion of the sampling points and long distance between pair points. The lowest spatial correlation belonged to garden land with middle spatial correlation class and the reason can be explained as due to increase of sand, decrease of clay and silt, bulk density of soil increases as well and leads to increase of coarse pores and consequently increasing saturated hydraulic conductivity of soil.
Results showed that soil saturated hydraulic conductivity (ks) with strong spatial correlation has high spatial variability and these variability consist lowest quantity in the garden lands and highest quantity in the sterile lands. The distribution pattern of Ks was seen similar to the sand and the soils bulk density, this pattern was opposite to the clay distribution pattern, this indicates the effect of soil physical parameters on saturated hydraulic conductivity.
According to the evaluation parameters CRM, MAE and MBA, Gaussian model is the best fitted model to soil saturated hydraulic conductivity data and soil parameters such as saturated hydraulic conductivity consist spatial variability related to sampling scale. The factors of land type and consequently type of land cultivation, lands management system, type of agricultural operations, soil particles size and bulk density of soil have the most impact on variability of Ks.

The environment is contaminated through intensive or inappropriate use of herbicides. Quantifying the fate of applied herbicides in the soil is essential for minimizing their mobility in the soil and environmental pollution. The adsorption behavior of the soil-applied herbicides is one of the most important factors governing its environmental impacts such as degradation, transition and leaching. To date, No studiy has been conducted to investigate the effects of DOM on the sorption of metribuzin by soils. The objective of this study was to investigate the impacts of DOM on metribuzin sorption by two defferent soils.
In this research, DOM (0, 10, 20, 40, 80 and 160 mg of OC/L) adsorption in two different soil samples was assayed under laboratory conditions at constant temperature. The effect of pH and DOM concentrations (0, 10, 40 and 160 mg/L) on metribuzin (1.5, 2, 3, 4, 5 and 6 mg/kg) adsorption was also studied. Soil samples were selected and collected from surface layers (0–20 cm). The soil samples were air-dried and passed through a 2-mm sieve. The DOM sorption in both soils was performed by adding 10 ml DOM solution with a series of initial concentrations in each 15 ml glass tube containing 1.00 g soil. All the DOM solutions contained 0.01 mol/L CaCl2 and 0.01 mol/L thymol, and the pH of the solutions were adjusted to 9.0 (about the pH of the initial extracted DOM solution) with 0.1 mol/L HCl or 0.1 mol/L Ca(OH)2. The tubes were shaken at 140 rpm for 24 h at 22°C. After centrifugation at 4,500 rpm for 15 min, the DOM concentrations in solutions (presented as OC) were measured using a total organic carbon analyzer. Sorbed organic carbon was calculated from the difference between the OC content of the DOM solution, which was initially added, and that found in equilibrium solution with the soil, of which the amount of native DOM released from the air-dried soil samples was subtracted. DOM solutions (10 ml) with different concentrations were added to the soils in 15 ml glass tubes with PTFE lined screw caps. The solid-to-solution ratios were adjusted to attain 20–80 percentage of the initially added metribuzin adsorption by the soils. All the DOM solutions contained 0.01 mol/L CaCl2 to maintain a constant ionic strength and 0.01 mol/L thymol to inhibit potential microbial activities, and the pH values of the solutions were adjusted to 9.0 with 0.1 mol/L HCl or 0.1 mol/L Ca(OH)2. Metribuzin was mixed at high concentration in acetonitrile before being added to the DOM solutions. Acetonitrile concentrations were always less than 0.1 percentage of the total solution volume to avoid the cosolvent effect. The tubes were shaken at 140 rpm for 24 h at 25°C. Preliminary studies showed that sorption equilibrium was approached within this time period. After mixing, the tubes were centrifuged at 4,500 rpm for 15 min, and 1.0 ml of the supernatant was removed into a sampling vial for analysis. All sorption samples were conducted in triplicate. The sorption experiments were conducted at different pH values in the absence of DOM by addition of HCl and Ca(OH)2 as required to solutions containing 0.01 mol/L CaCl2 and 0.01 mol/L thymol. The investigated pH values ranged from 4 to 9.5. The initially added concentration of metribuzin was 5 mg/L. After shaking and centrifugation, the pH values of the supernatants were measured using a pH meter. The samples were analyzed by gas chromatography equipped with a mass (6890N, Agilent, USA). Metribuzin sorption was calculated from the difference between the total amount of metribuzin initially added to the solution and the amount remained in the solution at equilibrium.
Dissolved organic matter (DOM) was adsorbed on the soils and the experimental data was better fitted to the Freundlich isotherm (R>0.999). The KF parameter amount of DOM sorbed on the soils were 3.82 and 0.95 L/kg for the soils of 1 and 2, respectively which suggested that the soils have low affinity to metribuzin . In the presence of DOM, the sorption behaviors of metribuzin by the soils were different. The effects of DOM on metribuzin sorption were dependent on the characteristics of soils and the concentrations of present DOM. Metribuzin sorption by soil 1 and soil 2 was inhibited in the presence of DOM. Metribuzin sorption was quantified by comparing the apparent distribution coefficient of metribuzin in the presence of DOM (Kd*) and the absence of DOM (Kd). The sorption was promoted when the ratio of Kd*/Kd was more than 1, and was inhibited when the ratio of Kd*/Kd was less than 1. The aqueous solubility, sorption, and bioavailability of metribuzin are pH dependent. The effects of pH on the metribuzin sorption by soils showed when pH increased from 4 to 9, metribuzin sorbtion by soils was decreased. When the pH was higher than 6.0, it was clear that the amount of sorbed metribuzin decreased as the solution pH increased in each soil in the absence of DOM. Metribuzin was present in both molecular and ionic forms owing to the ionization in the pH range examined in the study. As the solution pH increases, the protonic form decreases. Therefore, the sorption of metribuzin protonic form and the negatively charged surface of soils become more pronounced and the amount of metribuzin partitioned to soil decreases. In addition, an increasing pH may enhance the release of native organic matter from the soils into the solution that results in the decrease of metribuzin sorption. At the same pH, the amount of metribuzin sorbed by soil 2 was lower than soil 1 which was probably owing to the different organic matter content of the soils.
The effects of DOM on metribuzin sorption were dependent on the characteristics of soils and the concentrations of present DOM. In general, metribuzin sorption by the soils was inhibited in the presence of DOM. Metribuzin sorption by the soils also decreased with increasing the solution pH in the absence and present of DOM. The results of the study will be useful for the better understanding of the behavior of metribuzin in soils and its ecological risks.

Zinc is one of the essential micronutrients for plants, mining and industrial activities leading to pollution of heavy metals, including zinc metal contamination in soils. In addition to the total concentration, knowledge of the Zinc fractions is necessary to assess the mobility of zinc in the soils. One of the sequential extraction methods is Tessier method. sequential extraction with plant cultivation simultaneously, is the appropriate approach for assessing the mobility of toxic metals. Therefore this study was conducted to evaluate the chemical forms and determine their relationship to the physical and chemical properties of soils in some fields under cultivation in Khorasan Razavi province.
The experiment was conducted in a completely randomized design with factorial arrangement includes 4 levels of contamination (0, 500, 1000 and 1500 (mg/kg)) and 10 soil types from different regions of Khorasan Razavi province of 0-30 cm depth in the range of electrical conductivity 1 up to 15 ds/m, with three replications at Research greenhouses of Ferdowsi University of Mashhad. An example of mining waste was prepared as a source of pollution. The soil samples were kept at field capacity moisture for 6 months. Then air-dried soil samples were used for planting borage and determine the Zinc fractions. Then soil samples were air dried and used for planting borage and determining the Zinc fractions. Texture, cation exchange capacity, organic carbon, electrical conductivity, pH and Available phosphorus and potassium were measured in the saturation extract. DTPA-extractable Zinc was measured by atomic absorption spectrometry. Borage was planted in greenhouses in 3 kg pots with three replications. During flowering, the plants were harvested and dry digestion method was used to measure the concentration of Zinc. Chemical forms and Pseudo total concentration of zinc in the samples were determined using Tessier and digestion by HCl and HNO3 acids (3:1) methods respectively. The concentration of the extracts was measured by atomic absorption spectrometry. Statistical analysis was done using Minitab and Excel softwares.
Chemical Forms Average of zinc in soils was as follows:Exchangeable In this study, the residual, carbonate and organic fractions are dominant form of zinc in soils, respectively. With increasing level of contamination, percentage of residual zinc decreased and percentage of other fractions increased, particularly organic and carbonate. Increasing the availability of zinc, is a threat to the environment. There is a high correlation coefficient between different fractions of Zinc with each other and with the pseudo total, amount of plant and available plant zinc showed that there is a dynamic relationship in the soil systems. There is a higher correlation coefficient between the available zinc and carbonate and organic fractions of soils, which indicate available plant zinc, are mainly derived from carbonate and organic fractions.

Recently, due to enhancement of industrialization, urbanization and disposal of wastes, fertilizers and pesticides the concentration of heavy metals (HMs)in agricultural soil has increased. Heavy metals are serious threat for environment due to their hazardous effects. Lead (Pb) is one of the toxic heavy metal that threats the health of plants, living organisms and human. Excessive Pb concentrations in agricultural soils result in decreasing the soil fertility and health which affects the plant growth and leads to decrease in plant growth. Plants simultaneously exposed to Pb suffer morphological, biochemical and physiological injury. Pb adversely affect plant absorption of essential elements, chlorophyll biosynthesis and shoot and root growth. Arbuscular mycorrhizal fungi (AMF) and plant growth-promoting rhizobacteria (PGPR) are known to enhance nutrient uptake and improvement of plant growth and tolerance in heavy metal contaminated soils through different mechanisms including producing low molecular weight organic acids, siderophore, antibiotics and hormones. The objective of this study was to evaluate the effect of AMF and PGPR on yield, leaf relative water content (RWC), some biochemical properties and uptake of Pb, Fe and Zn by Hyoscyamus (Hyoscyamus niger L.) under soil Pb contamination.
This study was carried out in greenhouse condition as a factorial experiment based on a randomized complete block design with two factors including Pb concentration (in four levels) and microbial treatment (in three levels including arbuscular mycorrhizal fungi, plant growth-promoting rhizobacteria and control) and in three replications. Consequently, a soil was selected and spiked uniformly with concentrations of Pb (0, 250, 500 and 1000 mg Pb kg-1 soil). The contaminated soil was then sterilized and inoculated with the selected species of arbuscular mycorrhizal fungi (a mixture of Glomus species including G. intraradices, G. mosseae and G. fasciculatum) or plant growth-promoting rhizobacteria (a mixture of Pseudomonas species includeing P. putida, P. fluorescens, and P. aeruginosa). Seeds of Hyoscyamus niger L. plant were grown in pots containing the Pb spiked soil. At the end of growth period shoot length, dry weights of root and shoot, Fe, Zn and Pb concentration in shoot, and some biochemical and physiological properties of plant including relative water content (RWC) chlorophyll a, b and total chlorophyll, carotenoids, proline and soluble sugars, were measured.
Results indicated that with increasing soil Pb concentration, dry weights of root and shoot, shoot length, photosynthetic pigments contents (chlorophyll a, chlorophyll b, total chlorophyll and carotenoids), shoot Fe and Zn concentration decreased, while proline and soluble sugars contents and the shoot Pb concentration increased. With increasing of soil Pb concentration, relative water content decreased, however, this reduction in concentration of 1000 mg Pb kg-1 soil was not significant (P > 0.05) in compared with concentration of 1000 mg Pb kg-1 soil. Amounts of all measured properties in AMF and PGPR treatments were higher than that control treatment. The highest values of shoot weight and root weight, were observed in plants that inoculated with AMF. The lowest shoot weight was recorded in non-inoculated plants that were grown under 1000 mg Pb kg-1 soil concentration. In this study Arbuscular mycorrhizal fungi and plant growth-promoting rhizobacteria inoculation led to a significant increase (P≤0.05) in shoot length (12.9 -71.1%), shoot dry weight (11.5 – 81%), root dry weight (18.4 – 60.6%), chlorophyll (8.5 – 36.5%) and carotenoid (11.5 – 40.0%) pigments, proline (55 – 115.7%), soluble sugars (17.6 – 72.2%) and shoot Fe (9.5 – 57.2%) and Zn (25.0 – 165.5%) concentration in shoot at different levels of soil Pb. The highest and lowest amounts of shoot Fe, Zn and Pb concentration observed in AMF and control treatments respectively. Plant growth promoting rhizobacteria were more effective than arbuscular mycorrhizal fungi in shoot Fe, Zn and Pb concentration, while the mean of shoot length and shoot and root dry weight was higher in plants that inoculated with AMF compared to ones inoculated with PGPR. In general, there were not significant (P ≤ 0.05) differences in amounts of chlorophyll (chlorophyll a, b and chlorophyll a) and carotenoids pigments, proline and soluble sugars between AMF and PGPR treatments.
It could be concluded that microbial inoculation (mixture of AMF and PGPR species) with improvement of plant biochemical properties results in improved Hyoscyamus niger L. yield and increased tolerance to Pb toxicity. Thus, the use of microbial inoculation (mixture of AMF and PGPR species) inoculation might be suggested for enhancement of plant tolerance in Pb contaminated soils.

Salinity and pollution are two environmental stresses that individually influence the population, growth and activity of earthworms as soil bioengineers. It is well-known that the population and activity of these organisms are mostly reduced or even their activity and growth can be stopped in polluted and saline soils. The individual effects of these abiotic stresses on earthworms, however, depend on the level of salinity, pollution and organic matter. Nonetheless, the joint or combined effect of these stresses on earthworms, especially in arid and semi-arid areas, is poorly known. Because of the importance of earthworms in soil ecosystem, the study of salinity and pollution interactions on earthworm population and activity to reduce their detrimental effects using organic materials is essential. The aim of this study was to examine how salinity and lead (Pb) stresses simultaneously affect the earthworms in soil ecosystem.
In this research, the interaction effect of salinity stress using sodium chloride (NaCl) and Pb stress using lead nitrate (PbNO3) on the population, weight and activity of the earthworm Eisenia fetida was studied under greenhouse conditions. This factorial experiment was carried out using 3 factors, including Pb pollution (control and 30 mg kg-1 Pb), salinity (control, 4 and 8 dS m-1) and cow manure (control and 4% by weight) arranged in a completely randomized design with four replicates. The experiment lasted 13 weeks and earthworm’s population and activity including the number of adult worms, total earthworms, wet and dry weights, and wet and dry weights of casts produced by earthworm were measured at the end of the experiment. Concentration of DTPA (di-ethylene-triamine-pentaacetic acid) extractable Pb was also determined to assess how salinity influences the accessibility of this metal in the soil. The Fisher’s least significant difference test was used to determine the significance of any difference between the means values at 5% level with the STATISTICA 8 software. The Bliss Independence Model was used to determine the type of interaction between salinity and Pb pollution for each manure treatment.
The current results showed that increasing salinity level enhanced the accessibility of Pb and subsequently its toxicity for earthworms. In contrast, addition of cow manure reduced the accessibility of Pb by 22-50% at all salinity levels. Earthworm population, wet and dry body weights, and wet and dry weights of casts produced by worms were all significantly (p

Humans are constantly exposed to ionizing radiation. Most of the radiations originate from radioactive decay of natural radionuclides in the environment. Most of the ionizing radiations resulting from the decay of natural radioactive series of 238U, 235U, 232Th and 40K radionuclides in soil, rock and water. The average amount of uranium in the earth's crust is estimated 2.7 mg/kg that its amount increases up to 120 mg/kg in phosphate rocks. Phosphate rocks are main row material of chemical fertilizers production. Chemical fertilizers are chemical compounds that are used in order to increasing crops and improving properties of land. Yearly, many different types of fertilizers are produced such NPK, phosphate, etc.. Even though fertilizers can improve nutrient-deficient symptoms in farms but they contain heavy metals and radionuclides. Radionuclides in fertilizer enter to the soils and directly or indirectly can be absorbed by human body by inhalation of the radon gaseous or consumption of foodstuff. Radium salts with other salts are also dissolved in water and penetrate to deep layers of soil and can cause groundwater pollution. The consumption of chemical fertilizers containing radionuclides increases the radiological parameters of soils. Nuclear radiations is emitted from these elements are harmful to the body's tissues and may cause diseases such as cancer or genetic abnormalities. Therefore, the investigation of natural radioactivity contents in soils and radiological parameters are very important. In this research, the specific activities of natural radionuclides in agricultural and virgin soil samples determined using gamma ray spectrometry method in Arak and Saraband cities in Markazi province, Iran..For all samples, radiological parameters were calculated and compared with world average and some countries.
In this study, twenty two samples of agricultural and virgin soils were collected in different areas of Arak and Saraband cities of Markazi province in Iran, from surface up to 30 cm depth. The weight of each sample was about 2 kg. After drying the samples at room temperature, they were powdered by electric mill in the laboratory of Arak university. Soil samples were pulverized and passed through a 0.297mm sieve. They were kept in oven for 24 h at 100°C in order to remove the moisture content. After that, 950 g of each sample was packed in a Marinelli beaker container and sealed. Gamma ray spectra were registered after 50 days. The collected samples required particular care since radon is a short-lived gaseous nuclide and tends to escape from the samples. In this work, standard containers were sealed. After the minimum 50 days of preparing samples, gamma ray spectra were registered. This time is necessary for taking radioactive decay chain equilibrium, in which the decay rate of the daughters became equal to that of the parents. Specific activity measurements were performed by gamma ray spectrometry method employing high purity germanium (HPGe) P-type coaxial detector (GCD30195BSI) manufactured by Baltic Scientific Instrument LTD (005-Latvia) with 30% relative efficiency, which was connected to a multi-channel analyzer of 8192 channels. The energy resolution (full width at half maximum) of this detector is 1.95 keV for gamma energy line at 1332.520 keV due to 60Co and a Peak-to-Compton ratio of 60, and operating voltage was 3000 V. The detector and preamplifier are shielded in a chamber of three layers composed of 10 cm thick lead, 1.5 mm thick cadmium, and 3 mm thick copper. This shield serves to reduce background radiation.
Based on the results, the specific activities of 226Ra, 232Th and 40K radionuclides in soil samples varied in the range (39.60-51.94), (50.90 – 73.84) and (676.09 – 1094.50) in agricultural soils and (12.98 – 61.60), (18.15 – 60.98) and (257.48 – 866.58) in virgin soils, in Bq/kg. The mean specific activities of corresponding radionuclides were obtained 45.54, 69.09 and 926.71 Bq/kg for agricultural soils and 37.26, 43.17 and 604.04 Bq/kg for virgin soils. For all results calculated and have been tested variety of variance which show increasing in agriculture soil amount of 232Th and 40K compared with virgin soil. For 226Ra, the significant variation in probability level of 0.05 was not observed because of more mobility of radium salt than other salts and penetration into deeper layers. The increases the amounts of studied radionuclids in agricultural soils compared with average of worldwide virgin soils are 74.12, 72.30 and 131.68 percent, respectively. The average absorbed dose in air calculated for agricultural and virgin soils that obtained 105.22 and 70.59 in nGy/h, respectively. The average of Annual Gonadal Dose Equivalent (AGDE) and Excess Lifetime Cancer Risk (ELCR) for agricultural and virgin soils were obtained as (0.72 and 0.48) and (0.45×10-3 and 0.29×10-3), respectively. For virgin soil samples, radiological parameters were in good agreement with mean world value but in agricultural soil samples, increase was observed compared to virgin soil and agricultural soils of some countries.
The obtained data showed that the amount of mean specific radioactivity of natural radiouclides in agricultural soils were higher than some countries. The radiological parameters of agricultural soils in most samples were more than the world average of virigin soil values. The results of this research on virgin soil were in good agreement with the world average. This study showed that consumption of fertilizers in these cities was more than other countries. But all of radiological parameters of soil samples were less than maximum acceptable criteria and thus have no damaging effect for people health. However, the long term unsuitable usage of chemical fertilizers can have the effect of increasing of radioactivity in soils that can be harmful for the health of farmers and consumers of the crops.

population growth, urbanization and land use changes cause negative effects in natural ecosystems and water resources. Soil erosion is one of the most important problems in agriculture and natural resources of Golestan province. Using low cost and accurate methods for planning and proper management of land and water resources are essential for estimating consequences of soil erosion and providing appropriate solutions to reduce soil losses.
The study area is located in eastern part of Golestan province with an area of 1524 square Kilometers. The average annual precipitation of the region is 496 millimeters. In this watershed, rainfall decreases from south and south west to north and north east (due to the remoteness from the Caspian Sea), while evapotranspiration, temperature and the number of dry months increase in the same direction. Also the average annual temperature of the watershed and its relative humidity and evaporation are 17.8°C, 68.5 % and 1398.34 millimeters, respectively. Tamer watershed was divided into 15 sub-watersheds by adding an outlet in the site of Tamar gauging station. In this study, the SWAT model was used to simulate erosion and sedimentation. To compare the measured and simulated data and evaluation of the SWAT performance in terms of simulating flow and sediments, daily flow (cubic meters per second) and sediment (tons per day) data at the Tamar gauging station located in Tamar’s watershed outlet was collected from the studies of water resources organization (Tamab). Simulated values were generally consistent with the data observed during calibration and validation period. At this stage of calibration, the SUFI-2 model was used to optimize the parameter values. In this study, daily rainfall and temperature data recorded during an 8-year period by the stations within the watershed were imported into the model. The daily discharge data and daily sediment data of Tamar station recorded during 1999- 2006 were selected. Then model was run using runoff and sediment parameters, and ranges of parameters were adjusted at each iterations, and therefore SWAT model was calibrated using SUFI-2 model. After calibration, model must be validated and its ability to predict future events must be determined. Validation was performed using the runoff and sediment data recorded in Tamar gauging station from 2007 to 2010.
NS, R2, R-factor and P-factor were estimated for runoff calibration about 0.76, 0.77, 0.06 and 69 and for runoff evaluation 0.72, 0.75, 0.05 and 69 respectively. The same parameters were also measured for sediment calibration about 0.54, 0.62, 0.15, and 16 and sediment evaluation 0.55, 0.61, 0.35, and 12 respectively. The results showed that irrigated agriculture 24.95 and 15.56 t ha -1y-1 respectively, with average erosion and sediment ha of agriculture by an average of 20.23 and 12.33 t ha -1y-1 respectively erosion and sediment erosion and deposition are tons per hectare maximum value. Results also showed that the soil loss caused by erosion in this watershed is average 6.49 t ha -1y-1 in sediment and 10.28 t ha -1y-1 in erosion.
The assessment factors showed that model has successfully simulated the daily runoff discharge during calibration and validation phases with a Nash-Sutcliffe coefficient of 0.76 and 0.72. A Nash-Sutcliffe coefficient above 0.5 could be acceptable for sediment simulation. However, sediment load simulated for rainy seasons has been lower than actual value while this value has been higher than actual value during dry seasons. In most months of the year, model results are higher than measured values and this issue is more pronounced in the peak runoffs. This issue is due to limitations in spatial distribution of rainfall, so when a small area in watershed experience a severe rainfall, model considers the impact for the entire watershed and therefore overestimates the total runoff. The results showed that SWAT model can be a useful tool for the simulation of flow and sediment basins in the loess land.
Simulation results showed that land use changes have resulted in corresponding increases in surface runoff and sediment. Rates were highly variable both spatially and temporally, and the agricultural lands were most significantly affected. These land use changes have negative implications for the ecological health of the river system as and local communities.

Drought stress is one of the most important limiting factors for plant growth in the arid and semi-arid regions. This stress affecting crop production such as maize (Zea mays L.). Maize can play an important role in providing forage for silage animals, especially in the winter season in most parts of Iran due to high production capability . The application of plant growth regulators such as jasmonic acid and humic acid is one of the fastest ways to increase crop tolerance to environmental stresses viz. drought stress. The role of these acids is to prevent aging and falling of leaves, hormonal effects and improve nutrient uptake, which leads to increase of root and shoot biomass. Due to the expansion of industrial livestock, maize silage supply is essential. On the other hand, maize pollination and grain filling occur in the summer season and it overlaps with the peak of water limitation. Thus, in this experiment, the effect of jasmonic acid and humic acid on morpho-physiological characteristics and water use efficiency of forage maize under drought stress were studied.
In order to investigate the effects of jasmonic acid and humic acid to mitigate the impact of drought stress during pollination of forage maize (KSC 704), an experiment was conducted in research farm of the Shahrekord University, in 2016. The experiment was performed as a split plot in a randomized complete block design with three replicates. The treatments consisted of different levels of drought stress (no drought stress (field capacity), moderate drought stress (0.75 field capacity) and severe stress (0.50 field capacity)) as main plots and plant growth regulators (without hormone, jasmonic acid and humic acid) as sub plots. In no hormone condition, distilled water was used. Foliar application was done 10 mM jasmonic acid and humic acid content of 1500 grams per hectare before maize flowering. The volume of water consumed for each irrigation was measured by contour system. In this experiment leaf relative water content (RWC), proline, chlorophyll content, carotenoids, leaf area index (LAI), leaf weight, stem weight, ear weight, forage yield and water use efficiency (WUE) were measured. The analysis of data was performed using SAS software. Mean comparisons of study characteristics were done by LSD test at the 5% probability level.
The results showed that the relative water content, proline, chlorophyll, carotenoids, leaf area index, shoot weight, ear weight, forage yield and water use efficiency were affected by drought stress conditions. Although drought stress was reduced forage yield and related traits, the use of jasmonic acid compared to the control and humic acid under mild stress was significantly increased relative water content (61.1 and 39.3 %, respectively), leaf weight (60.4 and 41.8%, respectively), stem (14.8 and 25.12%, respectively), ear weight (13 and 23.8%, respectively), proline content (16 and 32.1 %, respectively), forage yield (24.4 and 24.2%, respectively). Under severe stress conditions, jasmonic acid significantly increased relative water content of leaf, weight of leaf, weight of stem and leaf area index. Under severe drought stress, jasmonic acid and humic acid had no significant difference. It was observed that under non-stress conditions, jasmonic acid wasn’t effective on water use efficiency and humic acid showed a negative effect. Under moderate drought stress, jasmonic acid was effective with increase 21.15 %, in moderating drought stress for maize and under severe stress jasmonic acid and humic acid had no significant effect.
According to the results, the occurrence of drought stress during pollination has a significant effect on maize yield. So that the severe drought stress (50% soil moisture depletion) leads to decrease in yield of maize forage due to decrease weight of leaf and ear. Although the most positive results of the use of growth regulators on maize yield were obtained under non-stress (full irrigation), the effect of moderate drought stress was mainly observed on forage production on jasmonic acid. The positive effect of foliar application of jasmonic acid in reducing the damage of drought stress and increasing of water use efficiency under moderate drought stress indicated that the use of this hormone could be useful in increasing production and quality of maize silage.

Soil microorganisms are the essential part of forest ecosystems which play a key role on soil nutrient changes. The biological activity in soil is largely concentrated in topsoil. Despite the small volume of microorganisms in soil, they have a key role on nitrogen, sulphur and phosphorous cycles and the decomposition of organic residues. Soil microorganisms have been identified as the sensitive indicators for soil quality. The composition of microorganisms and their fractional activities in soils significantly affect biochemical cycles, carbon sequestration and soil fertility. As soil microbial communities respond differently respected to environmental conditions, it seems that variation in forest ecosystem could significantly affect microbial community. Plants are one of the important variables for assessing soil microbial communities which their effect is related to root secretions and litter decomposition. The phospholipid fatty acid (PLFA) analysis is one of the methods that can overcome the problem of selective growth of microorganisms on culture media which is a major defect in the identification of microbial diversity. The objective of this study was to investigate the effects of different tree compositions and soil properties on soil microbial community using PLFA analysis approach.
This study was conducted in ShastKalate forest, an experimental forest station of Gorgan University, located at eastern Caspian region, North of Iran (36° 43′ 27″ N ,54°24′ 57″ E). Eleven different tree compositions were selected and the surface soils collected from 0-10 cm depth of 33 plots. Soil samples were air dried and passed through a 2mm sieve. Then one portion of the sieved samples was used for physical and chemical analyses. The other portion was rewetted to 65% of field capacity and incubated at 37 °C for 3 days to analyses PLFA. Soil particle size distribution (clay, silt and sand) was determined using the hydrometer method. Soil pH in 1/ 2.5 soil to water suspension and electrical conductivity (EC) in the same extract were measured.. Calcium carbonate equivalent (CCE),soil organic carbon (OC) and total nitrogen (TN) was determined, too. Biological analyzes including soil microbial respiration determination and PLFA analysis were carried out. The PLFA detection and quantification were performed with a Hewlett-Packard 5890 Series II gas chromatograph (GC) equipped with an HP Ultra 2 capillary column and a flame ionization detector. The normalized data were employed for Pearson's correlation analysis and ANOVA to determine the effects of soil properties and different tree compositions on soil microbial community.
Gram and Gram- bacteria were the most microorganisms and protozoa were the least microorganisms in soil samples. The results of the correlation between soil properties and microorganisms showed that OC and TN had significant positive effects on microorganism’s communities. EC was significantly correlated with Arbuscular Mycorrhizal Fungi (AMF), actionbacterial, protozoa and total PLFA. In addition, soil microorganisms and total PLFA were significantly correlated with soil respiration. However, there was no significant correlation between TN and OC with protozoa. The correlations between pH, EC, CCE and sand with protozoa were significantly negative, but in the case of silt, this correlation was significantly positive. Different studies showed that soil organic matter is the main nutrient source for soil microorganisms and soil microorganisms are also the essential part of C and N cycles. The effects of tree compositions on 16:0 10-methyl, 18:2 w6c, 20:2 w6c, 20:3 w6c and 20:4 w6c were significant(p

World cereal demand is growing at present in accordance with the global expansion of human populations. Deficiency of micronutrients in cereal cropping is one of the major worldwide problems. Beside of lowering grain yield, it may cause some healthy problems in human populations. Iron is an essential micro element in the soil that mainly had been found as the insoluble (Ferric or Fe3) form. Although ferric iron is relatively insoluble in water, the solubility of total inorganic iron decreases between pH of 7.4 to 8.5 range which is dominant in calcareous soils. It is estimated that nearly half of the world population is affected from Fe deficiency problem. Major reason for widespread occurrence of Fe deficiency in human populations is very little dietary diversity and high consumption of cereal-based foods with very low amount and poor availability of Fe. Bread wheat is the most widely grown cereal grain with 65% (6.5 million hectares) of the total crop cultivated area in calcareous soils of Iran. Most wheat cultivars currently used have been selected for high yields under optimum fertilizer conditions. Consequently, research is needed to select efficient genotypes that will grow and produce under conditions of lower fertilizer input or soil micronutrients deficiencies. This is especially true for the expansion of wheat cultivation which is often growing in calcareous soil of Iran. These soils are characterized with low fertility, high pH value, low organic matter content and low micronutrients availability. Environmental concerns in wheat production for human population indicate that to improve wheat quality and quantity, the zero or possible lowest amounts of chemical fertilizers would be applied. In this regard, the use of iron-efficient genotypes that have also high yield can be considered as a key strategy.
In order to investigate Fe efficiency in various wheat genotypes, a factorial experiments a randomized complete block design was carried out with three replications in agricultural and natural resource research and education center of Khorasan Razavi province, Mashhad (Torough Station), Iran, during 2009-2011. Treatments were consisted of two levels of Fe fertilizer (0 and 10 kg h-1 as Fe-EDDHA) and six genotyps of wheat including: three cultivars and one line of bread wheat (Alvand, Falat, Toos, and C75-5, respectively), two species of wheat known as Thriticosecale and Durum. The trial plots’s size was 9×3.6 (32.4 m2). According to the results of soil analysis, total nitrogen, available forms of phosphorus and potassium were 0.05%, 7.2, and 180 mg kg-1, respectively. DTPA extractable of iron, zinc, manganese and copper were 2.4, 0.52, 3.4 and 0.7 mg kg-1, respectively. Soil texture was silt loam. Soil organic carbon percentage and equivalent CaCO3 percentage (T.N.V) were 0.48% and 18.7%, respectively. The electrical conductivity (EC) and pH measured in saturated extract were 1.4 dSm-1 and 8.1, respectively. At defined phonological stage (SG6 based on Fix’s Index), the Fe concentration in shrub was measured. Moreover, grain yield and Fe uptake by grain were determined at the end of ripening stage. Iron use efficiency, agronomic efficiency and apparent recovery efficiency were calculated and studied as dependent variables.
The grain yield is the most integrative trait of a particular genotype. The results showed that Fe application increased significantly grain yield by 9.9% in comparison with control. In our research the highest grain yield increase due to Fe application was found in Durum wheat (17.1%), and the lowest grain yield increase, were found in Toos cultivar (4.1% yield increase). Application of Fe increased Fe concentration and uptake in grain about 5.7% and 16.4%, respectively. In terms of iron uptake by grain, Thriticosecale wheat and C75-5 cultivar had the highest (339.6 g ha-1) and the lowest amounts of Fe uptake (260.3 g ha-1), respectively. Also, application of Fe had no significant effects on Fe concentration in shoot. Fe use efficiency in bread wheat genotype, Durum and Thriticosecale wheat was ranked as: Durum There were various abilities to uptake and use Fe by different wheat genotypes. Fe-efficient genotypes of wheat were Toos and Falat also Triticale. Moreover, these genotypes also had higher grain yield.

Khuzestan province with 4.6 million hectares area has suitable agricultural lands that gully erosion destroyed some parts of them. One of the major basins in which much of its agricultural land threatened by gully erosion is located in Modarres watershed of Shushtar. Gully erosion progression in this basin causing the loss of farmland and thus the farmers are leaving farming and consequently would lead to poverty and migration to urban areas and social consequences. Therefore, presenting a model to determine the factors that impact on gully erosion and erosion hazard zonation for conserving and stability of the land need to research and investigate on gullies of Khuzestan province.
Study area is located in Shahid Modares basin that large parts of these farm lands destroyed by gully erosion. The aim of this project is to identify the main factors affecting on linear gully development and modeling them. For this purpose, distribution maps of climate and the gully was determined. Then a Watershed from each climate class with the highest losses was selected. At last Haddam watershed with warm-arid climate and Sharif watershed with warm-semi arid climate were selected. And 15 gullies were selected from each watershed then some parameters studied and measured in these gullies. Finally relationship between the length and volume development of gully with watershed characteristics, Physio-chemical soil properties, the percentage of vegetation cover, pebbles, bare soil, litter, slope and upstream area of head cuts, rainfall and different land use area a 20-year period (1993-2012) were analyzed. Modeling of the gully development was done using multivariate regression.
The results showed that in Haddam watershed the gully number A17 had most elongation (78.8 meters) while the gully number B2 had lowest elongation (3.8 meters). In Sharif watershed the gully number B3 had the most elongation (108.1 meters) while the gully number B4 had the lowest elongation (1993-2012). Gully clustering results showed that gullies of Haddam’s watershed were in two clusters and gullies of Sharif’s watershed in the three clusters. The final equation for the development of Haddams gullies in the cluster one shows the amount of development in these gullies depends on three variables including upstream area of initial point (X4), the percentage of bare soil (X6) and slope of initial point (X2). At cluster two the amount of progress in these gullies depends on silt percent (X18) and PH(X23). The final equation for the development of Sharif’s gullies in the cluster one shows the amount of progress in these gullies depends on upstream area of head cut(X3). At cluster two the amount of development depends on two variables upstream area of initial point (X4) and Sodium content (X22). In Haddam’s watershed more than 80 percent of land use is covered by rain fed and irrigated land. Unlike Sharif’s watershed that more than 80 percent of pasture land form. In addition, measurement of upstream watershed area reflects very poor range condition. In this region, due to the slight slope in gully head cut the surface runoff has not velocity but also due to lack of canopy cover in gullies’ watershed and low soil permeability because of silt frequency and high salinity in the soil profile increases the risk of gully development. In this research, slope of head cut upstream and slope of initiates point is less than 5 percent at total gullies that are correlated with development of gully elongation. However, due to poverty and lack of vegetation cover conditions provided for gully linear growth.
Gully erosion is a form of progressive erosion that allocated the largest portion of soil degradation in different climates to itself. Gullies behavior against its spreading and growth is affected by different environmental factors. In this research, available data analysis in Haddam’s watershed showed that the most important factors on the gully development were watershed characteristics on gully headcut (area and slope), the fine geological formation (silt), acidity and high soil salinity. These factors along with poor vegetation cover and agricultural land had created an excellent platform for gully elongation so that over a 20 year period have at least 3.8meter per year and a maximum elongation 78.8 m. In Sharif ‘s watershed showed that the most important factors on gully development were upstream area of head cut, upstream area of initiate pointed amount of sodium which caused to 10.1 and 108.1 meters minimum and maximum linear development respectively.

Sepiolite is a fibrous clay mineral which is usually found in Tertiary sediments in arid environments. The most abundance of sepiolite is between 30⁰ to 40⁰ latitudes of both northern and southern hemispheres. Sepiolite is an Mg-rich clay minerals which is very sensitive to weathering. Sepiolite is an industrial mineral with a variety of applications due to its structural and chemical properties. However, the clay (e.g. palygorskite and smectite) and no-clay (e.g. dolomite and quartz) impurities reduce the quality of sepiolite. Therefore, removing the impurities enhances the quality of the main clay mineral. Mineral purification consists of a series of chemical (e.g. acid treatment) and physical (e.g. particle size fractionation, sieving, ultrasonic treatment) procedures. There is a sepiolite mine in the northeastern Iran, near the city of Fariman. The sepiolite is a sensitive clay to weathering, especially in acidic solution. Therefore, the objective of this study was to propose a simple physical method based on particle size fractionation to purify the sepiolite.
Material and Sepiolite mine is located around Elyator, a village near the city of Fariman. The relatively hard sepiolite samples were grinded and passed through a 2 mm sieve. To determine the mineralogical composition, the powdered samples were analyzed by X-ray diffractometer (model: Explorer). XRF spectroscopy (model: PHILIPS-PW148) was used to identify the elemental composition. Pipette method was used to separate the particle size fractions. Firstly, the samples were passed through a 270 mesh (50 µm) sieve. The 0-50 µm fraction was then transferred to the cylinder containing dispersion solution (0.1% sodium carbonate and sodium hexametaphosphate solution). Based on the settling time of the particles in the suspension, three classes of particle size of 20-50, 0-20 and 50 µm size (sand size) were about 20 % and those with less than 2 µm size (clay size) consisted 37 % of the sample. Silt size particles (2-50 µm) were about 43 % of the sample. The XRD diffractograms indicated that particle size fractionation considerably decreased the amount of quartz. Dolomite peaks were completely absent in the diffractogram of the 50 µm. The ratios of the sepiolite indicator peak to the dolomite, palygorskite and quartz indicator peaks in bulk sample were 5.11, 7.28 and 2.82. This ratio was very high for dolomite in Dolomite, palygorskite and quartz were the impurities in Fariman sepiolite. There is no chemical treatment to remove the quartz and palygorskite. Dolomite can be easily removed using HCl, but it dissociates the sepiolite, too. The result indicated that particle size fractionation as a simple physical method purifies sepiolite effectively.

Cation Exchange Capacity (CEC) refers to the amount of negative charges available on the soil colloids surface. Clay and organic colloids carry a negative charge on their surfaces. Cations are attracted to the colloids by electrostatic bonds. Therefore, the charge of the soil is zero. For fertility map planning and commonly indicator of soil condition, CEC is an essential property. CEC is commonly measured on the fine earth fraction (soil particles less than 2 mm in size). CEC could be obtained directly but its measurement is difficult and expensive in the arid and semi-arid regions with high amounts of gypsum and lime. Pedotransfer functions (PTFs) are appropriate tools to estimate CEC from more readily measured properties such as texture, organic carbon, gravel, pH and etc. Regression PTFs, artificial neural networks (ANN), and hybrids technique (HA) could be used to developing pedotransfer functions. The prior research revealed that could provide superior predictive performance when developed ANN model. Furthermore, ANN technique has no comprehensive method to select network learning algorithm and stopping algorithm in the minimum local. Therefore, application of optimization algorithms such as Genetic (GA) and firefly (FA) is necessary. The Purpose of the present study was to evaluate the performance of FA and GA to predict the soil cation exchange capacity by ANN technique based on easily-measured soil properties.
220 soil samples were collected from 39 soil profiles located in Golfaraj (Jolfa) area of East Azarbaijan province. The study site lies from 45° 30ʹ to 45° 53ʹ east longitudes and from 38° 42ʹ to 38° 46ʹ north latitudes. Then, soil samples were air-dried and passed through a 10 mesh sieve for removing gravels and root residues. Soil textural class, organic matter content and CEC were, respectively, determined by hydrometer, Walkley and Black, and bower methods. The artificial neural network (ANN), artificial neural network-Genetic algorithm (ANN-GA) and artificial neural network-Firefly algorithms (ANN-FA) models were applied to predict the soil cation exchange capacity on the basis of the easily-measured soil properties. In ANN-GA and ANN-FA models, soil CEC was estimated via an artificial neural network and were then optimized using a genetic algorithm and firefly algorithm. The Genetic algorithms are commonly used to generate high-quality solutions to be optimized by relying on crossover, mutation and selection operators. The firefly algorithm is modeled by the light attenuation over fireflies’ mutual gravitation, instead of the phenomenon of the fireflies light. The schema of flashes is frequently unique for specific types. The techniques’ results were then compared by four parameter, i.e., correlation coefficient (R2), root mean square errors (RMSE), Nash–Sutcliffe (NES) and Geometric mean error ratio (GMRE).
The correlation coefficients of soil characteristic factors with CEC were analyzed through correlation matrix analysis. According to this analysis, the factors which had insignificant influence on the CEC were excluded. The clay, silt, sand and organic matter content were selected as input data. The parameter of the best deployment for MLP network could be used to predict CEC in the studied site. This model comprised 4 neurons (sand, silt, clay percentage and OM) in input layer. The optimum number of neurons in hidden layer was estimated to be 5. Additionally, the most efficient activity function in hidden layer was Axon sigmoid. Results showed that three CEC models performed reasonably well. ANN-FA model had the highest R2 (0.94), lowest RMSE (1.31 Cmol Kg-1) and highest Nash–Sutcliffe coefficient (0.53) in training stage and high R2 (0.97), lowest RMSE (1.06 Cmol Kg-1) and highest Nash–Sutcliffe coefficient (0.59) in test stage. ANN-GA model had also higher R2 (0.91), lower RMSE (1.77 Cmol Kg-1) and higher Nash–Sutcliffe coefficient (0.45) in training stage and higher R2 (0.93), lower RMSE (1.50 Cmol Kg-1) and higher Nash–Sutcliffe coefficient (0.48) in test stage indicating good performance of the model as compared with ANN models. The results showed that both ANN and Hybrid algorithm methods performed poorly in extrapolating the minimum and maximum amount of CEC soil properties data. In addition, the comparison of ANN-FA, ANN-GA results with ANN models revealed that ANN-FA was more efficient than the others.
The results of present study illustrated that ANN model can predict CEC with acceptable limits. Therefore, FA and GA algorithms provide superior predictive performance when is combined with ANN model. Firefly algorithm as a new method is utilized to optimize the amount of the weights by minimizing the network error. Final results revealed that this suggested technique improves the modeling performance.

First and the most important requirement of human being is food and food supply, which is directly, or indirectly associated with agriculture. Iron is a critical element for the growth, expansion and survival of the plant, since multiple metabolic and a physiological process is essential for the proper functioning. Agricultural areas in the world have a high pH in soil, which in turn decreases iron absorption by plants. Iron deficiency depending on many soil and environmental factors as well as plant genetic that in turns can decrease the yield and product quality. One method of overcome iron deficiency in plants is foliar application. A foliar application of iron fertilizer in agriculture is the common practice, especially in soils that accompanied with iron deficiency. The proper use of various types of fertilizers is the main solution to improve and maintaining soil fertility and increase crop production. The objective of this study is to evaluate the effect of foliar application of iron sources on growth parameters, concentration and absorption of iron in shoot and root and enzymes activity of catalase (CAT), ascorbate peroxidase (APX) and guaiacol peroxidase (GPOX) on forage sorghum plant to determine the best combination of iron fertilizer.
An experiment was conducted in a completely randomized design with factorial arrangement and three replications in greenhouse condition on forage sorghum (Sorghum Bicolor (L.) Moench) varieties of speed feed. The treatments included two levels of iron (0.25 and 0.5 g Fe.L-1 with Control (C)) from nine iron sources (Iron chelate (F1), Iron sulfate (F2), Iron oxide nanoparticles (F3), Monodisperse iron oxide nanoparticles (F4), Green nano iron (F5), Polymeric iron chelate (F6), Polymeric iron sulfate (F7), Polymeric iron oxide nanoparticles (F8) and Polymeric monodisperse iron oxide nanoparticles (F9)). The soil was obtained from educational and research greenhouses of Zabol university and after air drying and sieving passing 2 mm, some physical and chemical characteristics of soil such as texture, pH, electrical conductivity, cations exchange capacity, calcium carbonate equivalent, organic matter, total nitrogen contents, available P contents, available K contents and available Fe contents was measurement. Spraying of iron resources performed in two stages (4 leaf and the two weeks after first spraying). After two months of planting, the shoot cut from the surface of the soil and roots of the plants collected. Some parameters such as shoot and root dry weight, chlorophyll a, b and carotenoids, iron concentration in shoot and root, iron absorption in shoot and root, and activity of the enzyme (catalase, ascorbate peroxidase, guaiacol peroxidase) was measured. The experimental data examined using Excel and SAS 9.4 statistical software and the averages were compared using Duncan’s Multiple Range Tests at 0.01 and 0.05 significance level.
Results analysis of variance indicated that the interaction effects between iron resources and iron level on the dry weight of shoots and roots, chlorophyll a and b, iron absorption in shoots and roots, enzymes guaiacol peroxidase. Ascorbate peroxidase and catalase were significant at the level of 5 percent and iron concentrations in shoots and roots were significant at the level of 1 percent. The carotenoid content in leaves in the simple effects of iron resources was significant at the level of 5 percent. According to the results, foliar application of treatments on dry weight of shoots and roots, Fe concentration and Fe absorption by shoots and roots, chlorophyll a, b and the enzyme activity of APX, GPOX in addition CAT were significantly increased compared to Control. Foliar application at 0.25 g Fe.L-1, chlorophyll b in the treatment of monodisperse iron oxide nanoparticles, Fe concentration and Fe absorption in the shoots in treatments of polymeric iron sulfate and polymeric iron chelate, respectively. Fe concentration and Fe absorption in the roots in treatment of polymeric monodisperse iron oxide nanoparticles and APX activity in iron chelate treatment increased significantly compared to control. At level of 0.5 g Fe.L-1, dry weight of shoots in the treatment of iron chelate, dry weight of roots and CAT enzyme in the treatment of green nano iron, chlorophyll a in the treatment of polymeric iron chelate and GPOX enzyme in the treatment of monodisperse iron oxide nanoparticles were compared with the control increased significantly. The simple effects of iron sources indicated that the highest level of carotenoids observed in the foliar application of polymeric iron chelate.

Study of various aspects of daily rainfalls is so crucial from the view of scientific management of water resources in every region. Iran is located in subtropical high-pressure belt, which had low annual rainfall. The precipitation regime is very irregular both in time and space. The East and West Azarbaijan provinces are known as the important areas of agriculture, especially cereal production in Iran. Therefore, study of temporal and spatial distribution of daily rainfalls is very important in this region. The purpose of this study is to extract the best model for normalized rainfall curves (NRC) in the four selected stations namely, Tabriz, Maragheh, Urmia and Mahabad.
In this study, daily rainfalls of four stations namely, Tabriz, Maragheh, Urmia and Mahabad were used to fit the normalized rainfall curves (NRC). For this purpose, the two custom hydrologic models i.e. and were employed for NRCs. In order to find the values of (cumulative percentage of daily rainfalls) firstly the amount of daily rainfalls observations were arranged in ascending Order. Then, cumulative percent of rainfall calculated during the time period. The NRC curves of each station, plotted by drawing the versus for a total statistical period, separately. This was done for a given month (eg, January) data across the whole period and whole day's rainfall during the consecutive months of the years of the study period. In the latter case, the daily rainfalls of the first month of the first year of the study period were written consecutively in a distinct column of Excel spreadsheets. Then, daily rainfalls of the second year were written similarly, following the first years data. Daily rainfalls of the third, fourth and so on were written consecutively in the same mentioned column of Excel spreadsheets. Similarly, another column attributed to the number of rainy days in the studied period. Then, the values of non-zero daily rainfalls (arranged in ascending order) accumulated consecutively, and the resulted value were divided to the total number of observed rainfalls in the period (R). Similarly cumulative rainy days were divided to the total days (N). Moreover, the other fifteen models (including the power, exponential ...), were tested for the stations observations separately. Among the mentioned models, the most suitable one is selected according to RMSE and criteria.
Results showed that the maximum amount of daily rainfall experienced in Mahabad station in the rainiest month of the year or April (equivalent to 68 mm per day). The minimum value of daily rainfall belonged to the August (equivalent to 6 mm per day). The shape of NRCs created in this study for period in each of the four stations, showed that these curves were concave in almost all of the cases. This implies that a small amount of rainfall fell in a long period. In addition, the results showed that nearly in all of the stations the model of had the lowest value of RMSE and the largest value of . Therefore, this model selected as the most suitable one for NRCs of the stations. Although, the Exponential Association (3) model (in Tabriz) in April and the 4th degree Polynomial model (in Mahabad) in August selected as the most suitable model for them. Furthermore, the difference of statistics for the two models (at both of the time series) obtained as less than 0.0001. In the rainiest month and driest month of a year, the range of RMSE varied between 0.2559 mm in April (Maragheh) and 0.6709 mm in April (Tabriz). Moreover, the values varied between 0.9992 in August (Maragheh) and 0.9999 in April (Maragheh). In general, it can be concluded that the amount of precipitation receives in half of the rainy days is less than fifteen percent of the total rainfall depth. In this study, the values of of the most appropriate model for Tabriz, Urmia, Maragheh, Mahabad obtained as equal to 0.9996, 0.9997, 0.9996 and 0.9994, respectively.
Among the 17 candidate models, the model number 2 showed the highest , and the lowest RMSE. Therefore, the model was selected as the most appropriate model for drawing NRCs. Also, the mentioned model, were selected as the most appropriate model for all the months (in the four stations). The results showed that the NRCs were concave and in most cases, a small amount of total rainfall fell during the large number of days. In addition, in the two stations namely, Tabriz and Urmia the amount of rainfall receives in the 25, 50, 75 and 90 percent of rainy days were about two, 10, 30 and 60 percent of the total rainfall depth, respectively

Snow water equivalent (SWE) provides important information for water resources management and recently has attracted the attention of many researchers using remote sensing. Remote sensing presents a possibility for observation of snow characteristics, like water equivalent, over larger areas. Validation of remote sensing data of snow water equivalent (SWE) has always been an important issue for the researchers. Previous studies have assessed the global SWE data. Although it has been tried by using large-scale models of the world to estimate SWE, but regional effects such as snow density, topography and local meteorological conditions may lead to uncertainty.
The Northwestern Iran was selected as the study area in this research. Reasons for choosing this area are being mountainous with much snowfall. Also this region compared to the other parts of Iran, has more dense snow survey stations. In this study the AMSR-E sensor data and Global Land Data Assimilation System (GLDAS) was used to estimate SWE in the basins of the northwestern Iran. After processing AMSR-E sensor data and GLDAS model with related software, SWE was estimated in the snow survey stations and evaluated with observed data. To specify the snow density effect on SWE data in AMSR-E sensor from the snow density data, the stations were used. To determine the accuracy of estimation of SWE at different heights, snow survey stations is arranged by considering height and were divided into four height classes that contain enough observational data to evaluate computational data in each height class. To verify SWE obtained estimations in the stations, Root Mean Square Error (RMSE) and Pearson correlation coefficient (r) assessment criteria were used. After evaluating, the SWE data of AMSR-E sensor and GLDAS model for the GLDAS model monthly data to estimate SWE was used for the period 2000 to 2015. With calculating average annual SWE from monthly data, SWE trend changes in mentioned period, the moving averages graphs 3, 5 and 7-year-old was drawn.
According to the obtained results, SWE computational data with observational data had significant correlation at the 1% level. Using in situ snow densities, the correlation coefficient between AMSR-E and situ SWE increased from 0.27 to 0.55. The results showed that the best estimation of SWE is in the stations, which have the height of 1,350 to 1600 meters. Also with increasing altitude, the estimation accuracy is significantly reduced. In most years maximum of the SWE was obtained in January and February and in the period of June to September, the area was out of snow storage. According to the average annual SWE and moving averages graphs 3, 5 and 7-years old, the SWE of Northwestern Iran basins in period 2015-2001 has a reducing trend.
In the regions like the Northwestern Iran mountainous where snowfall constitutes a significant fraction of total precipitation, the snowpack delays the resulting runoff into the time of year where water demand is greater. So measurement of snow on the ground has been an important component of hydrologic forecasting for a century. Various remotely sensed snow data have been widely utilized for cold regions to explore the relationships between snow distribution, river discharge, and climate change. The accuracy of remotely sensed snow products should be well understood and incorporated in any investigations using such data. The main objective of the present study was to quantitatively compare the AMSR-E and GLDAS model for an understudied region of the earth. AMSR-E global SWE data and GLDAS data were compared by situ SWE measurements performed in the snow courses. The results showed that the snow density is an effective factor in derived algorithm for the SWE AMSR-E data. Also with increasing height, precision of the estimation significantly decreased. The determination of SWE from satellite imagery in progress updated with new learning. The obtained results from passive microwave in smooth terrain are promising, but involvement of different mechanisms become more complicated as the terrain gets more complex. Nevertheless, it is believed that if the above discussions are taken into account, AMSR-E would provide valuable SWE information even for a mountainous region like Northwestern Iran. It is also hoped that this study would be a starting point in the water scarce, developing Iran to plan and use the limited supply in a suitable manner.

Despite our scientific development and awareness of the consequences of regional and global climate change little attention has been paid to the effects of the changes in the Middle East and Central Asia yet. In the Middle East, climate change is a big challenge, especially if successive droughts and persistent increase as well as growing demand for water and water shortages attention, the challenge take on a large scale. Iran is a vast country with a different climate Rainfall distribution. Also precipitation is influenced by air mass entering the country from the neighboring countries, so rainfall in different regions of Iran is heavily influenced by the situation in neighboring countries. The aim of this study is evaluation of the trend of annual and monthly precipitations of the South-West of Asia with modified Mann-Kendall test by considering the effect of autocorrelation.
In this study monthly and annual precipitation data of 4152 rain gauge stations in Iran and its 15 neighboring in a period of 1970-2014 was used and been downscaled to evaluate the trend of monthly and annual precipitations. In this study the monthly and annual precipitations time series of Afghanistan, Azerbaijan, India, Iraq, Kuwait, Oman, Pakistan, Saudi Arabia, Syria, Tajikistan, Turkey, Turkmenistan, Qatar, Yemen and Iran were used. The purpose of the trend test is to specify the presence or absence of ascending or descending order in the data series. Since there are assumptions in the parametric methods such as the normality, stationary and independent variables and this assumption is often not valid for hydrological variables, the nonparametric Mann-Kendall method that is applicable to the hydrological and meteorological studies can be used.
The results of evaluating the trend of annual precipitation of study stations in the period of 1971-2014 using the Mann-Kendall modified by omitting the effect of autocorrelation indicated that all of the regions of Iran has decreasing trend in annual precipitations and there are significant decreasing trend in the western regions of Iran and western areas of Caspian sea, some central and eastern regions of Iran in five percentage significantly. The rest of the decreasing trend in annual rainfall amounts included in the country has experienced. In annual terms in countries, that border the study area is faced with an increasing trend in annual rainfall amounts so that the country at the center of the crisis (lack of rain) is located. The southern part of India, southwestern Saudi Arabia, the northern region of Turkmenistan and the eastern regions of Afghanistan and Pakistan with the increasing trend in annual rainfall amounts over the 1970-2014 statistical has faced. The trend of monthly rainfall amounts for the month of January (second month) showed that the amount of rainfall during the month trend of central and eastern regions of the study area is decreasing. In February (second month of the year) rainfall conditions in the study area as well as in the country in terms of changes time has improved and areas of Iran is faced with increasing precipitation. Changes decreasing the amount of monthly precipitation in March moved to the West study area and focus a significant decline in rainfall in the western regions of Iraq and Syria and Iran. However, in May (fifth month) most regions of Iran, Turkmenistan, northwestern Turkey and the West areas of India has been facing a decreasing trend in rainfall amounts. Other areas showed an increase in precipitation. In July (the seventh month), India (regions Northeast and East), Pakistan, Qatar, Saudi Arabia, the South East of United Arab Emirates has significant decreasing trend in rainfall amounts. Focus of decreasing monthly precipitation for the August moved to India and much of the country is included. Unlike other months of the study, in the eighth month (September) process to reduce the amount of monthly precipitation moved to south western parts of the study area (South West Asian countries) and Saudi Arabia in this month is central of decreasing.
The results of the annual trend of precipitation in Iran indicated that in an annual scale the North West of Iran is faced with the significant decrease trend in rainfall. The annual rainfall across eastern and northern part Iran also has significant decreasing trend and Central regions had a decreasing trend of precipitation in the period of studied. Iranian medium-scale review of the annual and monthly precipitation showed that the annual precipitation is reduced about 1.06 mm per year that the average amount of it’s in the study area (South-West of Asia) equal to the reduction of 0.33 mm per year which represents more than three times decreasing precipitation of Iran's regional in a year as South West Asia. Also the results of evaluating the slope of trend line in different months indicated that in December, March, January, the Iran’s precipitations is most decreasing as average of annual precipitation in studiing regions about 5, 3 and 5 times respectively