فهرست مطالب هادی معاضد

Recently, desert and desertification issues are known as one of the most problem in most countries especially developing countries. With an attention to the natural resources of Iran we can concluded that the most of Iranian lands are classified as deserts. Desert scientists believe that in addition to natural factors, human factors has a significant and important role in desertification. As natural factors are the most of the desertification criteria, models of desertification potential assessment are provided locally. In this time, using of desertification models is the best method for assessment of effective factors on land degradation and desertification severity from experts viewing. Despite of models abundance, one model is the best that has adapted considering to environmental and human conditions. To assess desertification, various research done in outside and inside of Iran. Zehtabian et al (2008) was evaluated soil and water criteria base on Medalus methodology in Ain-e- Khosh’s Dehloran and presented desertification map at the end of research. Desertification intensity class is critical for the entire region based on desertification map. Shakerian et al., (2012)  Evaluated desertification intensity in Jarghooyeh region, based on IMDPA model.their results showed that, this area classified in low class of desertification. According to the new definition of Desert, more parts of Iran encounter desertification problem. In order to challenging with desertification, it is necessary to do some scientific research and assessment in different parts of the country. The results may help to control and reduce the damages resulted from this phenomenon. The aim of this research would be the effects of climate indicator on desertification with method Iranian Model (IMDPA) in central part of Iran.

As the world's population continues to increase and fresh water decreases, the need for desalination of sea water is increasing. Therefore, the desalination process has become a new challenge as the earth's resources must find sustainable solutions through renewable energies. Condensation irrigation (CI) combines desalination and irrigation, which can produce required energy by solar power. This research was conducted for feasibility study in Research Station of Ahvaz University. The air flow was saturated by passing over the saline water surface in the solar still. Then the saturated airflow was driven into buried drainage pipes (25 m), where the humid airflow cools gradually, and the humidity condenses along the inner pipe surface. This condense water penetrates the soil via drainage pipe perforations, and irrigates the surrounding soil. During the field test, changes in the daily production of condensation water were observed due to the surrounding environment influenced on the input temperature but the average daily fresh water production was 6 L day-1. In addition, a laboratory model was built to identify the effective two entrance temperatures on the performance of condensation irrigation. The result showed that changing the flow temperature has a great impact on the performance of condensation irrigation.

The dust crisis in Khuzestan province is an environmental crisis that is currently one of the main centers of dust production in the desert areas of southern Ahvaz and the destroyed parts of Shadegan wetland. Destruction of vegetation in arid areas is the cause of desertification, which is the biggest cause of dust production. In this study to evaluate the criteria and indicators effective in desertification of the region, with the help of the model (IMDPA) which includes 9 criteria that Two criteria, climate and vegetation, each of which contains 3 specific indicators, have been selected. The numerical value of each criterion is obtained from the geometric multiplication of its indicators and finally the total desertification of the region is obtained from the geometric multiplication of two criteria. Finally, the intensity of desertification in the region was calculated to be 1.99 based on the selected criteria, which was in the medium desertification class according to the model scoring table.

The limitation of fresh water resources in the world, especially in arid and semi-arid regions such as Iran, has inevitably led to the reuse of urban wastewater. One of the most important indicators of sewage pollution and comparison with different standards for reuse or discharge to the water resources is TSS. The present study was conducted in 2016 with the aim of estimation of effluent TSS of Ahvaz wastewater treatment plant using inelegant models.

Regard to costly and time-consuming measurement tests of TSS, the capability of multivariate linear regression model, Artificial Neural Network (ANN), and Adaptive Neuro-Fuzzy Inference System (ANFIS) was studied to estimate (TSS) in wastewater treatment plant output by MATLAB and SPSS 21 software. Accordingly, various compounds of sewage quality parameters were evaluated during the 8-year statistical period (2008-2015) as input of models in two daily and monthly modes.

The results of the regression model indicated that the maximum R2 for training and verification were 0.75 and 0.67 in daily and 0.68 and 0.66 in monthly period, respectively. The root mean square error (RMSE) in this test was 0.033 and 0.025 in the daily period and 0.053 and 0.053 in the monthly period. The maximum R2 in ANN for training and verification were 0.87 and 0.79 in daily and 0.87 and 0.85 in monthly period, respectively. The RMSE in this test was 0.030 and 0.023 in the daily period and 0.034 and 0.031 in the monthly period. Meanwhile, the maximum R2 in ANFIS for training and verification were 0.91 and 0.83 in daily and 0.89 and 0.87 for monthly period, respectively. The RMSE in this test was 0.026 and 0.025 in the daily period and 0.031 and 0.028 in the monthly period.

The results confirmed the application of three models is appropriate, but the ANFIS was considered as a more appropriate model.

The nitrogen cycle in the soil is an important part of the nitrogen cycle in the world and is largely influenced by climate change. The developed model was calibrated and evaluated by system dynamics method in order to simulate nitrogen behavior in soil in Amirkabir sugarcane Agro-Industry. Data from complete irrigation and fertilization treatments (depth of irrigation was 120 mm and 4 split equal to 450 kg.ha-1) were used to calibrate the model. Also, treatments of 150, 250 and 350 kg.ha-1 were used to evaluate the model. In order to goals of this study, the output of three models of BNU-ESM, CESM-CAM and EC-EARTH was applied with two scenarios RCP2.6 and RCP8.5. The results showed that climate change would increase nitrate losses, mineralization and ammonium sublimation. The amount of nitrate losses in the EC-EARTH2.6 climatic pattern showed an increase of 5% for future period (2016-2035) compared to the base period (1971-2000). Mineralization in the base period was equal to 93.5 kg.ha-1, which is less than the values obtained with less variation models. This phenomenon also reduces the process of denitrification from 29.65 to 20.1 kg.ha-1. The change from the RCP2.6 to RCP8.5 scenario has led to an increase in nitrate losses, mineralization and ammonium volatilization, which indicates the effect of increasing the concentration of carbon dioxide gas on these processes.

Application of drainage water with appropriate management for saline soil reclamation is one of the suggested methods for reuse of drainage water. This research was carried out with the aim of investigating the effect of water and drainage water applying method (mixing before applying or applying in turn) and also the effect of leaching method (intermittent or continuous) on desalinization and desodification of Heavy textured soils of southern Khuzestan province. Leaching experiments were carried out applying 120 cm of water in 1.5 m × 1.5 m plots. Five leaching treatments were D1F1 and D2F2, which respectively consisted of 1-2 times applying of “Salman Farsi sugar cane agro-industry “drainage water with a salinity of 9.0 dS/m, and then, in the same manner, Karoun river water with a  salinity of 2.61 dS/m was applied to the plots. Also, M1, M2, and M4 treatments, in which respectively a mixture of water and drainage water with a salinity of 6.0 dS/m, were applied to the plots by continuous leaching and intermittent leaching with two breaks and intermittent leaching with four breaks. The remaining salts in the soil in M1 and M2 treatments in 0-30 cm soil top layer were 17% and 24%, respectively, and the sodium absorption ratio in these treatments was 57.5% and 24.7% higher than the M4 treatment, which indicates a positive effect of increasing the number of discontinuities in the desalinization and desodification processes.

Increasing surface and groundwater pollution by ammonium and nitrate makes it necessary to find solutions with minimal environmental impacts. Surface absorption is current method to remove soluble contaminations from aqueous medium. For this purpose, using herbal remedies offers cost-effective and availability and environmentally remediation technique. Using herbal nanoparticles as absorbent due to high specific surface and intense reactivity, results in high absorption efficiency.
In this study investigate nitrate removal using Conocarpus Nanostructure as absorbent in aqueous solution. In order to improve absorption capacity Conocarpus Nanostructure has been modified by a chemical method.
The effect of pH, time and absorption dosage has examined in batch system. The equilibrium time and optimum parameters were determined and the kinetic and isotherm models were checked.
The equilibrium time was determined 90 minutes and the optimum adsorption efficiency occurred in pH=3. The optimum absorbent concentration in nitrate solution was determined 0.6 mg/l. the Coefficients and constants related to the kinetic and isotherm models were find. The kinetic and isotherm models evaluation shows that the Ho et. al. and Froundlich models offer the best description.

The purpose of this study was to calibrate and evaluate DSSAT-CANEGRO Modelusing field data from two datasets for cultivar CP57-614, in Khuzestan. The experimental plan was performed at three levels of irrigation water (full and deficit irrigation) with three replicates in a completely randomized block design during cultivation years of 85-86 and 94-95. First of all, model calibration was done to find out the important input parameters by GLUE method. DSSAT-CANEGRO Model consists of 20 Genetic parameters. In order to reduce some parameters, parameterization was conducted using field data. The comparison between predicted and measured data showed that the model efficiency was 0.69 to 0.75 for aerial dry mass, 0.67 to 0.7 for stalk dry mass and 0.18 to 0.25 for sucrose. The results indicated that the sucrose prediction by CANEGRO model is weak as compared to other parameters. This is due to measuring sucrose at the end of grown season.

This research was developed to assess future climatic changes in the south of Ahwaz using General Circulation Models (GCM) based on IPCC-AR5. Temperature and precipitation data were extracted from 6 models in AR5. Then, EC-EARTH and CESM1-CAM5 for temperature and EC-EARTH and BNU-ESM for precipitation were used in LARS WG for downscaling. The results showed the temperature increase of 0.5 to 4 °C in winter and spring and 2 to 3 °C in summer and autumn. Precipitation will decrease in all months in the period of 2016–2035. This case study predicted the reduction of precipitation in most of the months. Investigation of the number of rainy days showed that this parameter had increased in all patterns. The results of the Mann-Kendall test also revealed that the precipitation didn’t have statistically significant trend.. Only EC-EARTH2.6 had an increasing trend for summer. This increase was significant at the 90% confidence level. In the case of the temperature parameter, the EC-EARTH8.5 pattern was increased in spring and summer and it was statistically significant at the 95% level. This increase was significant at the 99% confidence level for the summer season. CESM-CAM5-2.6 had an increasing trend significant at the 95% confidence level in summer. CESM-CAM5-8.5 had an increasing trend significant at 95% confidence level in autumn and winter. In the annual scale, the temperature parameter had an increasing trend significant at the 90% confidence level. Key words: AR5, Man Kendall, Temperature, Precipitation

Saline irrigated lands are expanding in Iran. Developing irrigation and drainage networks in salt affected soils in south Khuzestan will increase the quantity of saline irrigated lands. Continues and intermittent leaching are the usual methods for reclamation of salt affected soils in arid and semi-arid areas. By intermittent leaching, salts could be diffuse to the outer side of the aggregates in the drainage period and will be leached in the next round of water application. The part one of these series of papers was about the reviewing theoretical and mathematical concepts of salt transports in soil. In this part, applied aspects of salt leaching, considering interruption and water quality will be investigated. Effectiveness of surface and pressurized irrigation methods on salt leaching and their salt distribution patterns, considerations of leaching with saline water, factors which affected intermittent and continues leaching (evaporation, hydraulic conductivity, existence of plants and sodification) and a view to the world and Iran literatures are the main subjects of the paper.

Due to the rapid movement of water and contaminants through preferential flow paths, in this study kinematic– dispersive wave model as an appropriate method to simulate this motion was used. This model had three unknown coefficients which were determined using particle swarm optimization (PSO) method. Four different rainfall intensities of 56.97, 107.64, 133.01, and 161.71 mm h-1 were applied on the surface of a soil column and output water fluxes from the bottom of the soil column versus the soil mobile moisture amount in the column were recorded. Model coefficients were calculated by minimizing the error function between the observed values and the equation of the flow flux prediction. To achieve the best results and the minimum amount of error function, several solutions were evaluated and different values for c1 and c2 that control the best personal and global, respectively and interfere to make the next generation of results were tested. The best values for c1 and c2 were 1.2 and 2.4, respectively. Also to find the best results, several equations as the inertia weight, to control the particles velositeis in the search spaces, were tested and finally the linear decreasing inertia weight was chosen. Generally the results showed that the used algorithm could define the coefficients of kinematic–dispersive wave model in a short time and with a reasonable accuracy.

Nitrate is a common ion in nitrogen cycle. Nitrate can reduced to nitrite, nitrogen and other forms through microbial activities. In recent decades, high nitrate concentrations in drinking water have been became a serious concern in the world. Nitrate distribution in the groundwater is controlled through hydraulic parameters, concentration of dissolved oxygen and availability of carbon source as electron donors. There are some methods for nitrogen removal such as biological processes, chemical processes, and Biological denitrification. Biological denitrification is the process by which nitrate is reduced to nitrogen gas, through a sequence of enzymatic reactions. Changing methods of use or increase the absorption of nitrate nitrogen in agricultural systems has been known as the best way to reduce pollution of groundwater nitrate to prevent the transmission of groundwater in the first place. Denitrification beds have been known as the most common method for nitrate removal with high efficiency. In this study, salinity effect on performance of denitrification beds, constructed of mix of soil and sugarcane bagasse, was surveyed. This study was done in the research laboratory of Shahid Chamran University, Ahvaz, Iran. A physical model consists of 9 polyethylene columns with 350 mm length and 76.2 mm diameter was constructed. A 5-cm layer of fine sand was placed at the top and bottom of the soil columns to ensure that the inlets and outlets of the columns did not clog. Three replications were made for each treatment. The columns were fed via an upward flow by falling head. An upward flow was used to ensure the entire pore volumes of the columns were filled. Three treatments with different salinity levels, 2, 5 and 8 ds m-1, were considered. Water samples were collected from the effluent of the columns in clean plastic containers during the 14-week experiment, and were then subjected to nitrate, ammonium, and pH measurements. Sampling of influent and effluent was done in the beginning of experiments, daily for one week. After one week, sampling was limited to once in a week and finally once in every two weeks. The nitrate and ammonium concentrations were analyzed immediately in the samples by using spectrophotometer (DR5000, Hach, USA) at wave lengths of 275 and 425 nm, respectively. For all samples, the outflow discharge rates were conducted through collecting of a given volume of water in a specific time. Duration of experiments was 98 days. Entrance constant head of 102 cm were used. Fourier transform infrared spectroscopy (FTIR) (Bruker model, Germany) was employed according to the potassium bromide (KBr). The changes in functional groups of sugarcane bagasse, before and after use in biofilters, were examined by FTIR spectra. Also, the external morphology of the biomass was studied by scanning electron microscopy (SEM, 1455VP, LEO, Germany). All statistical analyses were performed using SPSS 21 software. Correlation analysis was done for determining correlation kind (positive or negative) and the values of significant. All significant testing was at the 95 % confidence level. Reported error values were ±1 standard deviation. The results of this research were shown that nitrate removal efficiency reduced with increasing of salinity. The removal efficiency was 83.87, 78.72 and 63 %, respectively in the salinity levels of 2, 5 and 8 ds m-1. But, there was a threshold for salinity level. Moreover, in the constant hydraulic loading rate, the lowest nitrate removal rate was belonged to the highest salinity level. Also, it was be observed that the values of C:N reduced with increasing of salinity. The results of correlation analyzes between the effective parameters on performance of beds indicated which hydraulic loading rate, hydraulic retention time and salinity has significant effect on removal efficiency. Also the results showed that, hydraulic factors such as hydraulic retention time and hydraulic loading rate have positive and negative impacts on performance of bioreactor beds, respectively. The SEM images showed considerable differences between sugarcane bagasse images before and after experiment. The results of FTIR and SEM analyze approved degradation of sugarcane bagasse during the experiments through activities of bacteria available in beds. In the higher salinity level, carbon source was consumed faster and more than other lower salinity levels. The FTIR and SEM results confirmed reduction of C:N ratio in the highest salinity level than other levels.

Aquifers are vulnerable to pollution from industrial and agricultural activities, the share of the agricultural sector is higher than the rest. Nitrogen fertilizers have the highest consumption in agriculture. Nitrate ion with negative charge is not absorbed by soil particles; therefore, it is subjected to surface and ground water leaching which is more intensive in sandy loam. Analytical and numerical models are used to investigate nitrate transport between soil and groundwater and its effect on groundwater contamination. The application of these models depends on the determination of dispersion and retardation factors. Therefore, quantitative estimation of these factors is necessary to solve the problems related to solute and metal transport in the soil. The parameters were estimated by comparing laboratory and field data versus theoretical ones. The objective of this study is to determine dispersion and retardation factors of nitrate and ammonium ions with three different methods including breakthrough curve (BTC), least square and HYDRUS models in a saturated sandy loam soil. The study was conducted in the soil columns of 50 centimeter and 10.5 diameter with three replications. Before leaching, ammonium nitrate fertilizer was added to soil columns with concentration of 10 g per liter. Concentration of nitrate and ammonium in leached water at the end of soil column with time, commonly known as the breakthrough curve (BTC), is determined. BTC as the first method, resulting from a step input of solute is often of sigmoidal shape and the dispersion and retardation factors are determined with this curve. The second method was least square one. In this method an error function model that fits to a breakthrough curve is presented with two unknown parameters. The parameters can be estimated by using laboratory data and a least square method. The last method is HYDRUS model. In HYDRUS model, the convection-dispersion and mobile-immobile models through inverse modeling were used to estimate the parameters. Dispersion and retardation factors for nitrate ion were in the range of 0.09-0.15 and 0.44-0.48 and for ammonium ion were in the range of 0.042-0.053 and 0.24-0.37, respectively. For quick and accurate estimation of dispersion and retardation factors from a soil column data, three methods were used in this study. The models applied in this study have almost identical results in estimating dispersion and retardation factors. The nitrate ion has been absorbed into the soil particles more than ammonium ion and consequently has a lower dispersion and retardation factors and less leaching than ammonium ion.

In recent decades, the study and move pollutants in saturation zone due to the many chemical and physical effects that is subsurface water quality has become a significant issue. The increasing use of nitrogen fertilizers due to high dynamics of nitrate in the soil would be a serious threat to groundwater, and therefore, to human health. Brigham and Fried-Combernous models are important models of persistent contaminant transport in homogeneous saturated porous media under constant flow, which are proposed for calculating the dispersivity in short and long travel distance, respectively. The purpose of this study is evaluation and comparison of Fried-Combernous and Brigham mathematical models for calculating nitrate dispersivity in homogeneous saturated sandy soils under laboratory conditions. For the study of dispersivity with Fried-Combernous and Brigham models, pure potassium nitrate salt solution under the sustainable regime with concentration of 160 (mg⁄lit) was added in the sandy soil columns ( in three sizes coarse, medium and fine - distance transmission at 80, 40 and 20 cm ) as persistent contaminants, then for extracting the needed parameters the concentration of output nitrate in three different porosities volumes were measured and Breakthrough curves were plotted for each column. Laboratory analyze data showed that dispersivity increases as the hydraulic conductivity and soil particle size increases. The results also demonstrated that the obtained dispersivity for fine sandy soil in both Fried-Combernous and Brigham models has significant difference with obtained dispersivity for coarse and medium sandy soil. So that by increasing the average travel distance in medium and coarse sand the nitrate dispersivity increased. But the dispersivity of fine sand decreased as the travel distance increased. Check calculated values of β parameter for fine sand showed the value of this parameter increases dramatically with increasing travel distance. This represents a higher pollutants velocity transition than the water velocity in the pores at the shorter distances in fine sand, and therefore the travel distance is increased with increasing dispersivity. The findings showed that the results of Fried-Combernous and Brigham models in the short travel distance is different, and it also cannot be generalized to long travel distances. Thereforre, the Fried-Combernous model was not efficient enough for short travel distance.

In recent years, concern over the long-term effects of heavy metals has been increased as environmental pollutants. Environmental pollution of heavy metals is one of the major environmental issues. Unfortunately, due to the uncontrolled entry of various types of industrial waste, their input is increasing into air, water and soil sharply. Heavy metals are irresolvable and tend to accumulate in the organs and tissues of living organisms that cause a variety of diseases and disorders for humans and other living organisms. Recently, biological methods and technologies such as biosorbent and bio-accumulation have been used to help researchers to confront the problem of removing heavy metals from sewage. In bio-accumulation technology is used living biota to remove metals. However, in the second method, or biological absorption is used of dead or inactive biologically is this purpose. The main objective of this research is to determine the capability of the storage of cadmium as heavy metal by modified Ceratophyllum demersum biomass. In addition, the effect of pH on adsorption rate, contact time on adsorption rate, adsorbent adsorption, initial concentration of adsorbant (cadmium) were evaluated on adsorption. Also, kinetic and isotherm models of absorption were determined.

In the present study, the effect of modification of Ceratophyllum demersum on the removal of Cadmium from aqueous solution was investigated. Ceratophyllum demersum or blue fork is a submerged plant that is commonly found in aqueous humorous streams containing moderate to high levels of nutrients. One of the suitable environments for growth of Ceratophyllum demersum is low depth and laminar flow of water channels. In this regard, a search was conducted on irrigation channels inside Shahid Chamran University of Ahvaz and large quantities of this plant were observed in many parts of these channels. The plant was collected from the entrance channel of the Karoon River to the university. After collecting the plant and washing it with urban water and distilled water and drying it in free air was dried at 70 ° C. After that the dry matter was milled and it passed through the standard No. 50 sieve. In this study, alkaline solutions (0.5M NaOH solution) were used to modify biomass. This method has been shown to be effective in similar studies, and has greatly increased the absorption capacity of adsorbents. Preparation of cadmium storage solution was performed based on the methods presented in the standard reference for water and wastewater testing.

The morphology characteristics of biosorbent surface by Scanning Electron Microscope (SEM) were studied and desirable effects of modification on characteristics of biosorbent surface were proved. The result of study showed that by increasing pH from 3 to 8, the removal efficiency increased from 93% to 97% at pH 7, and then decreased to 85% at pH 8. In addition, adsorption capacity, in similar way, increased from 7.04 to 7.35 and then decreased to 6.44 mg/g. Therefore, pH 7 was determined as optimum pH. Increasing contact time, from 5 to 240 minute, caused changes in removal efficiency from 67% to 98% after 180 minute, and then decreased slightly. Adsorption capacity, in similar way, increased from 6.25 to 9.13 mg/g and then decreased slightly and contact time of 60 minute was determined as equilibrium time. Increasing dose of biosorbent from 0.02 to 4 g/L, causing increase of removal efficiency from 37% to 99% and decrease of adsorption capacity from 169.5 to 2.35 mg/g and finally dose of 10 mg/L was determined as proper dose of biosobent. Increasing of initial concentration of Cadmium solution from 10 to 200 mg/L led to decrease in removal efficiency from 96% to 31%, and increase in adsorption capacity from 9.18 to 59.7 mg/g, and concentration of 10 mg/L was determined as optimum initial concentration of Cadmium. Finally, kinetic and isotherm adsorption models were studied. In kinetic models, pseudo-second order kinetic model, with correlation coefficient of 0.99 described biosorption better than pseudo-first order. In isotherm models, the Langmuir isotherm with correlation coefficient of 0.99 described biosorption process such better than other models. Based on results obtained in this study, the high capability of modified Ceratophyllum demersum, as a favorable biosorbent for cadmium removal from aqueous solution was proved.

The images from the SEM device showed that adsorption modification increased the absorption capacity to absorb cadmium ions. The highest efficiency was achieved in pH equal to seven. According to the economic considerations and optimum consumption of the energy 60 minutes was determined as the time of equilibrium. Kinetic modeling shows that Pseudo second order has the best matching with experimental data.

Saline irrigated lands in Iran are expanding and with developing irrigation networks in south Khuzestan, their quantity will be much more. Leaching is the only known method for reclamation of saline soils, which requires large amount of water. Cognation of theoretical and mathematical concepts will help understanding the leaching process and prevent mistakes and misconceptions, which led to enhancement of leaching operation, reducing the time and of course, reducing in water consumption. Leaching is an example of miscible displacement in pores medium. To describe salt movement in the structured soils, bi-continuum concept should be used. After introducing theoretical concepts and mathematical equations of salt transport in pores medium, salt transport models in soil will present specifically. These equations consist: general equation of salt transport, salt transport by diffusion, salt transport by dispersion and simulating models of salt transport in soil as a bi-continuum pores medium. In part two of these series of papers, through the window opened in part one, advantages and disadvantages of different leaching methods will be investigated. In addition, effect of environmental and systematic factors will be considered using these concepts. Understanding the concepts that introduced in this paper is not only useful for primary leaching in reclamation period, but it is useful for salt management in fields.

Nitaret is one of the stable components of nitrogen in the nature. Nitrate compounds are highly soluble and can easily imported to the surface and groundwaters and finally lead to be polluted of them. Denitrification is one of permanent removal methods of nitrate from terrestrial and aquatic ecosystems. In this study, denitrification process and nitrate removal rate changes with time in a column experimental study was evaluated on two types of denitrification beds, first type was a mixture of bagasse and soil (30 % of the volume of bagasse and 70 % of the volume of soil) and second type was only soil without bagasse. All experiments were performed under saturation conditions (anaerobic conditions). The influent nitrate concentraion to the all beds was considered an average of 45 mg/l. With sampling of inflow and outflow of the columns, nitrate removal changes were assessed over a period of three months. The maximum percentage of nitrate removal in columns with mixture of soil and bagasse were occurred in the end of the experiment (94%) and in columns without the bagasse were ocured in the first of the experiment (89%).The results showed that sugar cane bagasse as a carbonic source can be very useful in the design of carbonic filters and denitrification walls for nitrate favorable removal of inlet concentrated solutions. Overall, the results confirm that the denitrification process is one of the main mechanisms of biological nitrate removal from anaerobic enviroments.

Heavy metals pollution is a topic with worldwide concern because of its high toxicity to human beings, animals, and plants. The clay minerals, being important constituents of soil, have been playing this role always by taking up various contaminants as water flows over soil or penetrate underground. The high specific surface area, chemical and mechanical stability, layered structure, high cation exchange capacity (CEC), Bronsted and Lewis acidity, etc., have made the clays excellent materials for adsorption. In this study, retention process of Cd(II) contaminant using Bentonite and Nanoclay Cloisite Na詻��櫗. Based on data obtained in this study it can be concluded thatthe retention capacity of Nanoclay Cloisite Na is much more than Bentonite for Cd ions, because of high specific surface area and high cation exchange capacity of Nanoclay Cloisite Na.

In this study the effects of substrate and hydraulic retention times of 1, 3, 5 and 10 days on lead removal efficiency in horizontal subsurface constructed wetland under crop the common reed were evaluated. The results showed that the removal efficiency increased with increasing hydraulic retention time so observed significant difference at 5% level in sand substrate among hydraulic retention times 1, 3 and 5days in average removal efficiency of lead but there was no significant differences between retention times 5 and 10days and in the fine and medium gravel substrate between retention times of 1 and 3day was significant different at 5% but there was observed a significant difference at 5% level among retention times 3, 5 and 10 days, So the best hydraulic retention time was obtained in the sand, Fine and medium substrates respectively 5, 3 and 3 days with maximum efficiency of 88.51, 81.53 and 80.35 percent. The analysis results also showed that the substrate had a significant effect at 5% level on the lead removal efficiency in retention time 3 and 5 days so that sand substrate had higher efficiency than the other two substrates; therefor can be concluded the sand substrate has more effect to intensify in the physical, chemical and biological effective processes on removal of lead synthetic wastewater.

The increasing use of nitrogen fertilizers due to high dynamics of nitrate in the soil would be a serious threat to groundwater, and therefore, to thuman health. This study is aimed to investigate the disperdivity values of nitrate in the coarse, medium and fine sandy soils in the short travel distance of 20, 40 and 80 cm in vitro using the HYDRUS-1D model. For this purpose, pure potassium nitrate salt solution under the sustainable regime with concentration of 160 (mg/lit) was added to the soil columns as persistent contaminants, then for extracting the needed parameters the concentration of output nitrate in three different porosities volumes were measured and Breakthrough curves were plotted for each column. The results showed that dispersivity increases as the soil particle size increases. Also, by increasing the average travel distance in medium and coarse sands nitrate disperdivity values increased. But in the fine sand the disperdivity values decreased as the transmission distance increased. The disperdivity values for fine, medium and coarse sand were from 30/50 to 42/55 cm, 57/06 to 68/51 cm, and 68/50 to 97/06 cm, respectively. The average model error percent (Er) was less for fine sandy soil, and coefficient of determination (R2) was relatively more for fine sandy soil than the coarse and medium sandy soils, which means the lower error value and higher precision of the overall process in simulation of nitrate transfer in this model for the fine sandy soils.

Increased use of nitrogen fertilizers due to high dynamics of soil nitrate is a serious threat to groundwater and as a result for human health. The purpose of this study is evaluation of nitrate dispersivity values in the sandy soils of coarse, medium and fine-distance transmission at 80, 40 and 20 cm in laboratory conditions with three models including, Brigham, Fried-Combernous and CXTFIT code. For this purpose, pure potassium nitrate salt solution as sustainable contaminant under the steady regim with concentration of 16 was added to the soil column. In order to obtain the required parameters for the three models, output nitrat concentration were measured in the different nolum porosity and Breakthrough curves were plotted for each column. The results showed that in all three models with a moderate increase in transmission distance of medium and coarse sand, the amount of nitrate dispersivity increased. At various distance of transportation, dispersivity values were measured for fine sand from 0.09 to 3.06 cm,0.23 to 1.6 cm for medium sand and 0.43 to 2.18 cm for coarse sand, respectively. But the Brigham and CXTFIT models showed that the dispersivity of fine sand increases when the distance increases. It was also found that for the fine sand with reduction of transport distance, Brigham model and CXTFIT code showed better results.

Modeling of water flow through vadose zone under unsaturated conditions necessitates the knowledge of soil hydraulic properties, which are water retention curve and water field capacity of soil. Indirect prediction of these characteristics based on readily available soil properties in the form of pedotransfer functions (PTFs) as a fast and low-cost solution has been widely practiced and very useful in irrigation and drainage. This study aimed to present the proper PTFs using mathematical modelling for estimating soil moisture at point of field capacity for Khuzestan province soils under laboratory and field conditions. The buried probes of the time domain reflectometry device (TDR) were inserted at various depths in order to monitor soil moisture conditions in both the physical model and experimental field under a surface-point source drip irrigation with discharge rates of 4 lph. Then, physical soil properties and soil water contents at their specific matric potentials were measured to calculate the hydraulic parameters of Van Genuchten-Mualem model with the RETC program. The results of this research to evaluate the performance of several well-known Point-PTFs showed that quasi-empirical models based on physical principles that have been tested in the field can be a good alternative to traditional methods for estimating water field capacity of soil. So that, the PTF of Twarakavi et al. could carefully predict that water field capacity of soil with indices of normalized root mean square error (3.1 percent) and standard error (0.5 percent) and more accurate than Rosetta artificial neural network approach or Dexter equation. Accordingly, another two PTFs were proposed to improve the accuracy of the water field capacity prediction in the form of regression equations on the basis of the parameters of Van Genuchten model and readily available soil properties for the semi-arid region of Khuzestan province. Results of obtained PTFs showed clearly negative effects of soil compaction and the amount of sand on the water field capacity of soil. On the contrary, the amount of clay and silt had positive and increasing effects on the water field capacity of soil, significantly.

Generally soil preferential flow occurs through soil macropores. These flows can transport a large amount of water and any type of pollutant to groundwater in a short time. This issue causes the water and soil pollution and in terms of environmental and health, affect the lives of animal and human. In this study the movement of water in preferential routes in the soil was investigated using a physical model. Also this movement was evaluated using Kinematic–Dispersive Wave (KDW) model which is a second degree non-linear partial differential equation and optimization of its coefficients. At first, the model coefficients were obtained using Particle Swarm Optimization (PSO) method. After that, the model was validated using experimental observation of rainfall hydrograph which was passed through the preferential routes of physical model and was recorded from the bottom of soil column. The results showed that the numerical model has very good agreement with experimental observations, and this prediction is better in lower rainfall intensity. Since dispersive mechanism was applied in this model and the effect of dispersive is disappeared graduatly with increase of input rainfall intensity, this effect in lower velocities causes the model to predict much better the observation. Consequently, this model can be a way to predict the preferential water flow and contaminant in soil to be eligible to make a reasonable decision in environmental management planning.

These days the problem of water and soil pollution is one of the factors threatening the sustainability of agricultural production and human’s life and other living things. Also, preferential flow of water and solute is a common phenomenon in the natural saturated and unsaturated soil which generally results in fast contaminant transport and thus greatly increases the risk of groundwater contamination. So mathematical models are widely used in soil physics and hydrology for predicting preferential water flow and contaminants transport through the unsaturated zone. Preferential flow which is the cause of water transport in soil macropores such as underground channels formed by worm activity and root plants growth, is the reason of rapid water and contaminants transport to ground water and its contamination. For process predicting and describing of these types of water flow in soil, in this research the kinematic dispersive wave- van Genuchten model is introduced which is the innovation of this research.
In this research, the experiments were conducted with four different rainfall intensities of 56.97, 107.64, 133.01 and 161.71 mm h-1, which were applied on the surface of a soil column and output water fluxes from the bottom of soil column and mobile water content of whole soil column were recorded. Model coefficients were calculated by minimizing the error function between the observed values and something modeled by equation using particle swarm optimization (PSO) method. To achieve the best results and the minimum amount of error function, several solutions were tried and different values for c1 and c2 which are the learning factors (weights) or acceleration coefficients of optimization algorithm which interfere to make the next algorithm results and control the personal and global best respectively, were tried and chosen and also several equations as the inertia weight, w which used to control the particles/results velocities in the search spaces, were tried.
After applying several amounts for c1 and c2, finally the amount of 1.2 and 2.4 for c1 and c2 respectively, leads to best results and lowest error function. Also for the optimization, after reviewing the results of several different equations, the linear decreasing inertia weight equation which was presented by Xin et al., in 2009 was chosen (31). Based on results, in all rainfall intensities, optimization algorithm could find the best results after 3500 iteration and making frequent generation.
Generally the results have shown that the used algorithm could define the coefficients of kinematic dispersive wave- van Genuchten model in a short time and with reasonable accuracy.

FAO-56 Penman-Monteth (FPM) model is one of the most applied methods to estimate crop evapotranspiration; yet the accuracy of the model in greenhouses is still undetermined especially in non-standard conditions of water deficit and salinity. This study focused on the performance of the FPM model in estimating greenhouse and outdoor eggplant evapotranspiration (ETc), crop coefficient (Kc) and water stress coefficient (Ks) under different levels of water deficit and salinity. An area in the greenhouse and the outdoor field was assigned to grass cultivation as a reference crop. Daily reference (ET0) and crop evapotranspirations were measured by diurnal weighting of microlysimeters throughout the growing season (from May 19th to September 5th, 2012). The performance of the FPM model was evaluated by four statistical difference criterions along with regression indices. The ET0 values were properly estimated in the outdoor conditions but showed about 12 percent underestimation in the greenhouse; however, the trends of daily ET0changes were well predicted in both environments. Apparent differences in daily ETc variations were met during the growing season, for various levels and combinations of water stress. Best estimations of daily and mean 10-day ETc values were those of daily irrigated (I1) treatments in both environments. In mean 10-day ETc, better correlations were obtained between the measured and estimated values due to smoothened fluctuations in weather and data and soil moisture changes. Actual and calculated values of Ks along with the correctness of their estimations decreased with the intensity of water stresses in both environments. The variation patterns of daily Kc values was similar to those of the daily ETc. Mean 10-day values of Kc were properly estimated by the FPM model; yet outdoor estimations were accurate in all treatments.