University of Tehran Press Iranian Journal of Soil and Water Research 2008-479X 54 6 2023 08 23 Determining the layered flow velocity in the Latyan reservoir using acoustic tomography technology Determining the layered flow velocity in the Latyan reservoir using acoustic tomography technology 859 875 93172 10.22059/ijswr.2023.358568.669491 FA Reza Hosseinzadeh Asl Ph.D. Student of Hydraulic Structures, Department of Irrigation and Reclamation Engineering, College of Agricultural Engineering and Technology, University of Tehran, Karaj, Iran Mehdi Yasi Associate Professor, Department of Irrigation and Reclamation Engineering, College of Agriculture and Natural Resources, University of Tehran, Karaj, Iran. Masoud Bahreini Motlagh Assistant Professor,Water Research Institute, Tehran, Iran 0000-0001-9009-663X Journal Article 2023 04 30 Acoustic tomography technology is an advanced method of remote sensing, which has been used and verified by many researchers in recent years to measure flow velocity and temperature in different water environments. The purpose of this research is the feasibility of using this technology in reservoirs of dams to measure the flow velocity in different layers. The basis of this method is to calculate and record the travel time of acoustic rays in the water environment, including the reservoir of the dam. In the first step, the propagation of sound rays from the first station to the second station was simulated. Then, according to the propagated rays and the obtained travel times and solving the inverse problem with the regularization method, the average flow velocity, and layered flow velocity were calculated. In this research, two acoustic stations with mutual transmission with a frequency of 10 kHz were placed in the reservoir of Latian Dam on October 23, 2020. Five layers with a distance of ten meters in depth were selected. The results of solving the adjusted inverse problem showed that the maximum velocity of 0.0006m/s occurs in the first layer (0 to 10 m depth). For the flow velocity of layers, two to five, 0.0003, 0.0001, 0.0002, 0.0001 m/s were calculated respectively, which according to the close to zero flow velocity of the dam reservoir at the time of data collection, the velocity of the flow was obtained with a relatively good approximation. It is suggested that in future studies, data collection should be done when the water discharge valves are open so that the results can be compared with the results of this research. Acoustic tomography technology is an advanced method of remote sensing, which has been used and verified by many researchers in recent years to measure flow velocity and temperature in different water environments. The purpose of this research is the feasibility of using this technology in reservoirs of dams to measure the flow velocity in different layers. The basis of this method is to calculate and record the travel time of acoustic rays in the water environment, including the reservoir of the dam. In the first step, the propagation of sound rays from the first station to the second station was simulated. Then, according to the propagated rays and the obtained travel times and solving the inverse problem with the regularization method, the average flow velocity, and layered flow velocity were calculated. In this research, two acoustic stations with mutual transmission with a frequency of 10 kHz were placed in the reservoir of Latian Dam on October 23, 2020. Five layers with a distance of ten meters in depth were selected. The results of solving the adjusted inverse problem showed that the maximum velocity of 0.0006m/s occurs in the first layer (0 to 10 m depth). For the flow velocity of layers, two to five, 0.0003, 0.0001, 0.0002, 0.0001 m/s were calculated respectively, which according to the close to zero flow velocity of the dam reservoir at the time of data collection, the velocity of the flow was obtained with a relatively good approximation. It is suggested that in future studies, data collection should be done when the water discharge valves are open so that the results can be compared with the results of this research. https://ijswr.ut.ac.ir/article_93172_c0047dbf26a61bd8d7ba4bd2d27113c5.pdf

University of Tehran Press Iranian Journal of Soil and Water Research 2008-479X 54 6 2023 08 23 The Effect of Irrigation with Magnetically Effluent on Soil Chemical Properties, Water Productivity and Heavy Metals Uptake by Maize The Effect of Irrigation with Magnetically Effluent on Soil Chemical Properties, Water Productivity and Heavy Metals Uptake by Maize 877 893 93171 10.22059/ijswr.2023.357365.669477 FA Mojtaba Khoshravesh Department of Water Engineering, Faculty of Agricultural Engineering, Sari Agricultural Sciences and Natural Resources University, Sari, Iran. Masoud Pourgholam-Amiji Department of Irrigation and Reclamation Engineering, College of Agriculture and Natural Resources, University of Tehran, Karaj, Iran. Journal Article 2023 04 06 This research was conducted to investigate the effects of using the treated magnetic effluent on chemical properties and heavy metals of soil, water productivity, and uptake<strong> </strong>of heavy metals by Maize plants. To conduct the research, a factorial experiment was conducted in the form of a randomized complete block design with three replications in two crop seasons (2021 and 2022) in Babolsar City. The treatments included irrigation with well water, irrigation with a mixture of 25% effluent and 75% well water, irrigation with a mixture of 50% effluent and 50% well water, irrigation with a mixture of 75% effluent and 25% well water, and irrigation with 100% effluent in conditions. All these were in the conditions of application of magnetic field and without magnetic field effect. The results showed that the effect of irrigation water and mixing of water and effluent on electrical conductivity, solutes, and heavy metals in the soil at different depths was significant at the probability level of 1%. On average, irrigation with magnetic water decreased electrical conductivity by 33.05%, lead by 37.45%, and cadmium by 65.28%. The results of maize water productivity showed that the effect of irrigation water and water and effluent mixing on biological, physical, wet forage, and dry forage productivity was significant and increased the values of biological, physical, wet forage, and dry forage productivity by 11.51, 10.92, 12.78, and 14.6%, respectively, compared to non-magnetic effluent. By using magnetic water, the concentration of lead, cadmium, zinc, and nickel metals in maize seeds decreased by 19.84%, 19.76%, 15.48%, and 23.01% respectively. The use of magnetic technology enables the optimal use of unusable water and increases the yield and water productivity of plants. Also, this technology can be effective in reducing the accumulation of heavy metals in the soil and maize plants using effluent. This research was conducted to investigate the effects of using the treated magnetic effluent on chemical properties and heavy metals of soil, water productivity, and uptake<strong> </strong>of heavy metals by Maize plants. To conduct the research, a factorial experiment was conducted in the form of a randomized complete block design with three replications in two crop seasons (2021 and 2022) in Babolsar City. The treatments included irrigation with well water, irrigation with a mixture of 25% effluent and 75% well water, irrigation with a mixture of 50% effluent and 50% well water, irrigation with a mixture of 75% effluent and 25% well water, and irrigation with 100% effluent in conditions. All these were in the conditions of application of magnetic field and without magnetic field effect. The results showed that the effect of irrigation water and mixing of water and effluent on electrical conductivity, solutes, and heavy metals in the soil at different depths was significant at the probability level of 1%. On average, irrigation with magnetic water decreased electrical conductivity by 33.05%, lead by 37.45%, and cadmium by 65.28%. The results of maize water productivity showed that the effect of irrigation water and water and effluent mixing on biological, physical, wet forage, and dry forage productivity was significant and increased the values of biological, physical, wet forage, and dry forage productivity by 11.51, 10.92, 12.78, and 14.6%, respectively, compared to non-magnetic effluent. By using magnetic water, the concentration of lead, cadmium, zinc, and nickel metals in maize seeds decreased by 19.84%, 19.76%, 15.48%, and 23.01% respectively. The use of magnetic technology enables the optimal use of unusable water and increases the yield and water productivity of plants. Also, this technology can be effective in reducing the accumulation of heavy metals in the soil and maize plants using effluent. https://ijswr.ut.ac.ir/article_93171_03893fe900219dba0ee3ca9655767568.pdf

University of Tehran Press Iranian Journal of Soil and Water Research 2008-479X 54 6 2023 08 23 Effect of Seed Priming with Zinc on Seed Germination Characteristics, and Morphological Characters, and Mineral Content of Rice Tissues of Hashemi Rice Cultivar Effect of Seed Priming with Zinc on Seed Germination Characteristics, and Morphological Characters, and Mineral Content of Rice Tissues of Hashemi Rice Cultivar 895 914 92952 10.22059/ijswr.2023.356947.669473 FA Shahram MahmoudSoltani Assistant Professor of rice research institute of Iran Maryam Hosseini Chaleshtori Associate Professor of Rice Research Institute of Iran, Agricultural Research, Education and Extension Organization, Rasht, Iran Shahram Nazari 1Assistant Professor of Rice Research Institute of Iran, Agricultural Research, Education and Extension Organization, Rasht, Iran Maryam Shakouri Katigari Research Assistant of Rice Research Institute of Iran, Agricultural Research, Education and Extension Organization, Rasht, Iran. 0000-0001-7764-9578 Journal Article 2023 03 20 Nutripriming of rice seeds with micronutrient (Zn) is considered to have the potential of optimizing Zn application, faster germination, uniform seedlings’ growth, better establishment of transplanted rice seedlings. The current experiments were designed and conducted to explore the effects of rice seeds nutripriming of with micronutrient (Zn) on macro and micronutrient content of primed seeds, morphological characteristics of rice seedlings and uptake of macro and micronutrients (N, P, K, Zn) for Hashemi rice cultivar through two laboratory and open-air pot experiments during 2021 at rice research institute of Iran. The highest increase in seed germination vigor index (2.9 times) ad reduction in germination dynamics or three germination fractions (t 10, t 50, and t 90) compared to control were recorded at nutripriming with zinc sulfate (5g. L^-1) for 12 hours by about 2.28, 2.49, and 2.47 times, respectively. The maximum increase in Zn content of rice seeds (17.5 times) were observed at nutripriming with zinc sulfate (5g.L^-1) for 24 hours compared to the control. Also, the highest positive, significant increase in the length of coleoptile and radicle by seed nutripriming with zinc sulfate (5g.L^-1) for 6 hours compared to the control by about 25.87 and 18.67%, respectively. The maximum significant and positive increase in root wet and dry weight of rice seedlings were found at about 24.36, 20.00, 38.23, and 38% compared to the control through nutripriming of seeds with zinc sulfate (5g.L^-1) for 6 hours in soils with Zn deficiency and sufficiency, respectively. The highest significant and effect on Zn content of shoot and root of rice seedlings were observed about 2.71, 2.91, 2.27, and 2.51 compared to the control through nutripriming of seeds with zinc sulfate (5g.L^-1) for 6 hours in soils with Zn deficiency and sufficiency, respectively. Nutripriming of rice seeds with zinc sulfate (5g.L^-1) solution for 6 hours could be an alternative solution for traditional methods of macro and micronutrients application (soil and foliar) by farmers in seed nursery. Nutripriming of rice seeds with micronutrient (Zn) is considered to have the potential of optimizing Zn application, faster germination, uniform seedlings’ growth, better establishment of transplanted rice seedlings. The current experiments were designed and conducted to explore the effects of rice seeds nutripriming of with micronutrient (Zn) on macro and micronutrient content of primed seeds, morphological characteristics of rice seedlings and uptake of macro and micronutrients (N, P, K, Zn) for Hashemi rice cultivar through two laboratory and open-air pot experiments during 2021 at rice research institute of Iran. The highest increase in seed germination vigor index (2.9 times) ad reduction in germination dynamics or three germination fractions (t 10, t 50, and t 90) compared to control were recorded at nutripriming with zinc sulfate (5g. L^-1) for 12 hours by about 2.28, 2.49, and 2.47 times, respectively. The maximum increase in Zn content of rice seeds (17.5 times) were observed at nutripriming with zinc sulfate (5g.L^-1) for 24 hours compared to the control. Also, the highest positive, significant increase in the length of coleoptile and radicle by seed nutripriming with zinc sulfate (5g.L^-1) for 6 hours compared to the control by about 25.87 and 18.67%, respectively. The maximum significant and positive increase in root wet and dry weight of rice seedlings were found at about 24.36, 20.00, 38.23, and 38% compared to the control through nutripriming of seeds with zinc sulfate (5g.L^-1) for 6 hours in soils with Zn deficiency and sufficiency, respectively. The highest significant and effect on Zn content of shoot and root of rice seedlings were observed about 2.71, 2.91, 2.27, and 2.51 compared to the control through nutripriming of seeds with zinc sulfate (5g.L^-1) for 6 hours in soils with Zn deficiency and sufficiency, respectively. Nutripriming of rice seeds with zinc sulfate (5g.L^-1) solution for 6 hours could be an alternative solution for traditional methods of macro and micronutrients application (soil and foliar) by farmers in seed nursery. https://ijswr.ut.ac.ir/article_92952_b112befbfc2d79f0c6a974bb19d541d9.pdf

University of Tehran Press Iranian Journal of Soil and Water Research 2008-479X 54 6 2023 08 23 Estmiating of Soil Particles Percentage Using Visible-Near Infra-Red (NIR) spectrometry in Semirom area, Isfahan Estmiating of Soil Particles Percentage Using Visible-Near Infra-Red (NIR) spectrometry in Semirom area, Isfahan 915 931 93265 10.22059/ijswr.2023.359898.669505 FA Fateme Rahmati Ph.D. Student, Department of Soil Science, Faculty of Agriculture, Shahid Chamran University of Ahvaz, Ahvaz, Iran,. Saeid Hojati Associate Professor, Department of Soil Science, College of Agriculture, Shahid Chamran University of Ahvaz Kazem Rangzan Professor, Department of Remote Sensing and GIS, Faculty of Earth Science, Shahid Chamran University of Ahvaz, Ahmad Landi Professor, Department of Soil Science, Faculty of Agriculture, Shahid Chamran University of Ahvaz, Ahvaz, Iran, Journal Article 2023 05 26  <br />The present research performed to estimate soil texture using visible near-infrared spectrometry in Semirom, Isfahan. A total number of 200 soil samples (0-10 cm) were collected from the Semirom area (51º 17' - 52º 3' E; 30º 42' - 31º 51' N), Isfahan. The samples were air dried and passed through a 2 mm sieve, and soil particles percentage was determined in the laboratory using hydrometry method. Reflectance spectra of all samples were measured using an ASD field spectrometer. Different pre-processing methods i.e., First Derivatives and Savitzky-Golay Filter, Multiplicative Scatter Correction and Standard Normal Variable were applied and performed on spectral data. The Partial Least Squares Regression, Support Vector Machine Regression and Artificial Neural Network models were used to estimate soil texture. The best result was obtained for Silt estimation, with excellent values of RPD >2, R² =0.98 and RMSE=1.08 using Artificial Neural Network model with MSC pre-processing technique. The results indicated the desirable capability of Artificial Neural Network model with MSC and SNV pre-processing techniques in estimating the Clay (RPD >2, R2=0.94 and RMSE=1.21) and Sand (RPD >2, R²=0.84 and RMSE=6.24) contents of the soils, respectively. In general, based on the results of this study, VNIR spectroscopy was successful in estimating soil particles percentage and showed its potential for substituting laboratory analyses.  <br />The present research performed to estimate soil texture using visible near-infrared spectrometry in Semirom, Isfahan. A total number of 200 soil samples (0-10 cm) were collected from the Semirom area (51º 17' - 52º 3' E; 30º 42' - 31º 51' N), Isfahan. The samples were air dried and passed through a 2 mm sieve, and soil particles percentage was determined in the laboratory using hydrometry method. Reflectance spectra of all samples were measured using an ASD field spectrometer. Different pre-processing methods i.e., First Derivatives and Savitzky-Golay Filter, Multiplicative Scatter Correction and Standard Normal Variable were applied and performed on spectral data. The Partial Least Squares Regression, Support Vector Machine Regression and Artificial Neural Network models were used to estimate soil texture. The best result was obtained for Silt estimation, with excellent values of RPD >2, R² =0.98 and RMSE=1.08 using Artificial Neural Network model with MSC pre-processing technique. The results indicated the desirable capability of Artificial Neural Network model with MSC and SNV pre-processing techniques in estimating the Clay (RPD >2, R2=0.94 and RMSE=1.21) and Sand (RPD >2, R²=0.84 and RMSE=6.24) contents of the soils, respectively. In general, based on the results of this study, VNIR spectroscopy was successful in estimating soil particles percentage and showed its potential for substituting laboratory analyses. https://ijswr.ut.ac.ir/article_93265_e50a486b8da3256bd53fc25c3f147616.pdf

University of Tehran Press Iranian Journal of Soil and Water Research 2008-479X 54 6 2023 08 23 Prediction of Wind Erosion Threshold Velocity Using Portable Wind Tunnel Combined with Machine Learning Algorithms Prediction of Wind Erosion Threshold Velocity Using Portable Wind Tunnel Combined with Machine Learning Algorithms 933 947 93337 10.22059/ijswr.2023.354837.669506 FA Monireh Mina Department of Soil Science and Engineering, College of Agriculture, Shiraz University, Shiraz, Iran Abdolmajid Sameni Department of Soil Science and Engineering. College of Agriculture. Shiraz University.Shiraz.Iran Ali Akbar Moosavi Department of Soil Science and Engineering, College of Agriculture, Shiraz University, Shiraz, Iran Yaghoub Ghanbari Department of Computer Science and Information Technology, Faculty of Engineering, Hormozgan University, Bandar abbas, Iran Journal Article 2023 05 27 Wind erosion is a key process in land degradation worldwide, especially in arid and semi-arid regions of Iran. This phenomenon is affected by many soil characteristics. The main objective of this study was to estimate the wind erosion threshold velocity using easily measurable soil characteristics along with data mining methods. For this purpose, wind erosion threshold velocity was measured in 100 areas in Fars province using a portable wind tunnel. Wind erosion threshold velocity was predicted by a support vector regression algorithm using easily measurable soil properties. In this regard, a genetic algorithm was used in order to obtain a set of parameters effective in estimating wind erosion threshold velocity. The results showed that the characteristics of soil moisture (r = 0.77), the size distribution of soil particles including the mean weight diameter of aggregate (r = 0.87) and the wind-erodible fraction of soils (r = -0.81), penetration resistance (r = 0.75), and organic matter (r = 0.33) have a high and significant correlation with wind erosion threshold velocity and play a key role in determining the threshold velocity of wind erosion in the region. According to the evaluation criteria, the combined support vector regression model with the genetic algorithm had the best performance and the most accurate estimate for wind erosion threshold velocity (RMSE = 0.53 and R² = 0.92) and can be a promising method for estimation of wind erosion threshold velocity. Wind erosion is a key process in land degradation worldwide, especially in arid and semi-arid regions of Iran. This phenomenon is affected by many soil characteristics. The main objective of this study was to estimate the wind erosion threshold velocity using easily measurable soil characteristics along with data mining methods. For this purpose, wind erosion threshold velocity was measured in 100 areas in Fars province using a portable wind tunnel. Wind erosion threshold velocity was predicted by a support vector regression algorithm using easily measurable soil properties. In this regard, a genetic algorithm was used in order to obtain a set of parameters effective in estimating wind erosion threshold velocity. The results showed that the characteristics of soil moisture (r = 0.77), the size distribution of soil particles including the mean weight diameter of aggregate (r = 0.87) and the wind-erodible fraction of soils (r = -0.81), penetration resistance (r = 0.75), and organic matter (r = 0.33) have a high and significant correlation with wind erosion threshold velocity and play a key role in determining the threshold velocity of wind erosion in the region. According to the evaluation criteria, the combined support vector regression model with the genetic algorithm had the best performance and the most accurate estimate for wind erosion threshold velocity (RMSE = 0.53 and R² = 0.92) and can be a promising method for estimation of wind erosion threshold velocity. https://ijswr.ut.ac.ir/article_93337_b19ee434b8bed37a4c6584f570022422.pdf

University of Tehran Press Iranian Journal of Soil and Water Research 2008-479X 54 6 2023 08 23 Determining Water Management Indicators in Olive Production Poles in the Country Determining Water Management Indicators in Olive Production Poles in the Country 949 960 92992 10.22059/ijswr.2023.356374.669480 FA Fariborz Abbasi Agricultural Engineering Research Institute (AERI) 0000-0002-0662-7723 Afshin Yousof Gomrokchi Assistant professor,Ghazvin Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization (AREEO), Ghazvin, Iran Ebrahim Dehghanian Research Instructor,Fars Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization (AREEO), Shiraz, Iran Parisa Shahinrokhsar Agricultural Engineering Research Department, Guilan Agricultural and Natural Resources Research Center, AREEO. Rasht. Iran Hassan Mousavifazl Assistant professor,Semnan Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization (AREEO), Shahrood, Iran Mehdi Taheri Associate professor, Zanjan Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization (AREEO), Zanjan, Iran Alireza Keiani Professor, Golestan Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization (AREEO), Gorgan, Iran 0000-0002-2345-5089 Mohammad Mehdi Nakhjavanimoghaddam کرج - بلوار شهید فهمیده - موسسه تحقیقات فنی و مهندسی کشاورزی - بخش آبیاری تحت فشار Abolfazl Naseri Associate professor,Azarbayejan Sharghi Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization (AREEO), Tabriz, Iran Saloome Sepehri Sadeghian Assistant professor of Irrigation and Drainage Engineering, Agricultural Engineering Research Institute (AERI), Agricultural Research, Education and Extension Organization (AREEO), Karaj, Iran Samira Vahedi Researcher, Zanjan Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization (AREEO), Zanjan, Iran . Samar Behroozinia Researcher, Zanjan Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization (AREEO), Zanjan, Iran Mohammad Abbasi Agricultural and Natural Resources Research Center of Zanjan Province Journal Article 2023 04 09 The purpose of this study was to assess irrigation management and determine water productivity in olive orchards managed by local farmers in the country. To achieve this, the amount of water provided by gardeners and the yield of 102 olive orchards that underwent irrigation using various methods, surface and drip irrigation, were measured across the provinces of Qazvin, Fars, Zanjan, Gilan, Golestan, and Semnan. This data was collected during two consecutive years, 2018 and 2019. Measured values were compared with NETWAT-estimated net irrigation requirements as well as Penman-Monteith-derived values. Based on the results, it can be concluded that the average volume of irrigation water, yield, irrigation water productivity, and applied water productivity in the selected provinces are significantly different at a probability level of 1%. According to the study, the volume of irrigation water used in olive orchards varied from 2848 to 11463 m3/ha, with a weighted average of 6011 m3/ha. The average yield of olives in the production poles of this product has varied from 1500 to 11000 kg/ha over the two-year period, and its weighted average has been 4867 kg/ha. It is also worth mentioning that the water productivity ranged from 0.2 to 2.40 and its weighted average was 0.95 kg/m3. Furthermore, the applied water productivity in the selected provinces ranged from 0.18 to 1.45 and its weighted average was 0.63 kg/m3. Upon evaluating the efficiency of irrigation in the olive orchards, it was observed that the quantity of water delivered was approximately 27% and 17% less in comparison to the irrigation requirement calculated using recent 10-year meteorological data and NETWAT, respectively. In other word, forced deficit irrigation has taken place in the olive orchards The purpose of this study was to assess irrigation management and determine water productivity in olive orchards managed by local farmers in the country. To achieve this, the amount of water provided by gardeners and the yield of 102 olive orchards that underwent irrigation using various methods, surface and drip irrigation, were measured across the provinces of Qazvin, Fars, Zanjan, Gilan, Golestan, and Semnan. This data was collected during two consecutive years, 2018 and 2019. Measured values were compared with NETWAT-estimated net irrigation requirements as well as Penman-Monteith-derived values. Based on the results, it can be concluded that the average volume of irrigation water, yield, irrigation water productivity, and applied water productivity in the selected provinces are significantly different at a probability level of 1%. According to the study, the volume of irrigation water used in olive orchards varied from 2848 to 11463 m3/ha, with a weighted average of 6011 m3/ha. The average yield of olives in the production poles of this product has varied from 1500 to 11000 kg/ha over the two-year period, and its weighted average has been 4867 kg/ha. It is also worth mentioning that the water productivity ranged from 0.2 to 2.40 and its weighted average was 0.95 kg/m3. Furthermore, the applied water productivity in the selected provinces ranged from 0.18 to 1.45 and its weighted average was 0.63 kg/m3. Upon evaluating the efficiency of irrigation in the olive orchards, it was observed that the quantity of water delivered was approximately 27% and 17% less in comparison to the irrigation requirement calculated using recent 10-year meteorological data and NETWAT, respectively. In other word, forced deficit irrigation has taken place in the olive orchards https://ijswr.ut.ac.ir/article_92992_b82f148883f1cbfbbd8ad2c353423872.pdf

University of Tehran Press Iranian Journal of Soil and Water Research 2008-479X 54 6 2023 08 23 Removal of Pb (II) from Aqueous Solution by Nano Organo-Composite Paramagnetic Particles: Study of Kinetic and Isotherm Models Removal of Pb (II) from Aqueous Solution by Nano Organo-Composite Paramagnetic Particles: Study of Kinetic and Isotherm Models 961 979 93401 10.22059/ijswr.2023.360233.669507 FA Mahboobeh Abolhasani Zeraatkar Department of Soil Science, Agriculture Faculty, Shahid Bahonar University of Kerman, Kerman, Iran. Hamidreza Rafiei-Sarbijan Department of Soil Science, Faculty of Agriculture, Shahid Bahonar University of Kerman, Iran Journal Article 2023 06 02 The adsorption of lead on two adsorbents, montmorillonite clay (Mt) and magnetic nano organo-composite, was investigated in this study. The magnetic nano organo-composite has been developed by modifying montmorillonite clay with the organic surfactant Hexa decyltrimethylammonium bromide and adding magnetite nano-particles (MagMt-H). X-ray diffraction, Fourier transform infrared spectroscopy, and scanning electron microscopy were used to identify the nano organo-composite (MagMt-H). Two adsorbents were used to investigate the effect of lead initial concentration on its adsorption from aqueous solution. To comprehend the process of Pb adsorption, two adsorption isothermal models (Langmuir and Freundlich) and kinetic models (Pseudo-first order, pseudo-second order, Elovich, and intraparticle diffusion) were used. Surface adsorption in the nano organo-composite follows the isothermal models of Langmuir, as well as the pseudo-second order kinetic model, according to an examination of isothermal models and adsorption kinetics. The maximum adsorption capacity calculated from the Langmuir model at 30 °C in the nano organo -composite (73.58 mg g-1) was significantly greater than the value obtained in montmorillonite clay (49.54 mg g-1). The initial absorption rate (h) for nano organo-composite adsorbent (MagMt-H) with a value of 18.809 mg g-1min-1 compared to the montmorillonite (Mt) adsorbent with a value of 0.948 mg g-1min-1 indicates a much higher rate of lead (II) adsorption by nano organo-composite (MagMt-H). The results of this research demonstrated that the nano organo-composite (MagMt-H) was easily prepared and that new adsorption sites were created at its interface, making it extremely effective for removing lead from aqueous solutions. The adsorption of lead on two adsorbents, montmorillonite clay (Mt) and magnetic nano organo-composite, was investigated in this study. The magnetic nano organo-composite has been developed by modifying montmorillonite clay with the organic surfactant Hexa decyltrimethylammonium bromide and adding magnetite nano-particles (MagMt-H). X-ray diffraction, Fourier transform infrared spectroscopy, and scanning electron microscopy were used to identify the nano organo-composite (MagMt-H). Two adsorbents were used to investigate the effect of lead initial concentration on its adsorption from aqueous solution. To comprehend the process of Pb adsorption, two adsorption isothermal models (Langmuir and Freundlich) and kinetic models (Pseudo-first order, pseudo-second order, Elovich, and intraparticle diffusion) were used. Surface adsorption in the nano organo-composite follows the isothermal models of Langmuir, as well as the pseudo-second order kinetic model, according to an examination of isothermal models and adsorption kinetics. The maximum adsorption capacity calculated from the Langmuir model at 30 °C in the nano organo -composite (73.58 mg g-1) was significantly greater than the value obtained in montmorillonite clay (49.54 mg g-1). The initial absorption rate (h) for nano organo-composite adsorbent (MagMt-H) with a value of 18.809 mg g-1min-1 compared to the montmorillonite (Mt) adsorbent with a value of 0.948 mg g-1min-1 indicates a much higher rate of lead (II) adsorption by nano organo-composite (MagMt-H). The results of this research demonstrated that the nano organo-composite (MagMt-H) was easily prepared and that new adsorption sites were created at its interface, making it extremely effective for removing lead from aqueous solutions. https://ijswr.ut.ac.ir/article_93401_421c8c107e6ff4c75a5121e0cbaa495b.pdf