University of Tehran PressIranian Journal of Soil and Water Research2008-479X56320250522Assessing the horizontal and vertical distribution of phosphorus in agricultural soil around maize root using a fertigation method in surface drip irrigationAssessing the horizontal and vertical distribution of phosphorus in agricultural soil around maize root using a fertigation method in surface drip irrigation57158810219410.22059/ijswr.2025.385191.669832FAMeisamRezaeiSoil and Water Research Institute, Agricultural Research, Education and Extension Organization, Karaj, Iran0000-0003-3044-4625SomayehDehghaniSalinity Research Department, Bushehr Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization (AREEO), Tehran,, Iran0000-0002-7736-8335KAMBIZBAZARGANSoil and Water Research Institute, Agricultural Research, Education and Extension Organization, Karaj, Iran0000-0001-9569-9667KARIMSHAHBAZISoil and Water Research Institute, Agricultural Research, Education and Extension Organization, Karaj, Iran0000-0001-7994-2559Journal Article20241110The availability and efficient utilization of phosphorus, an essential nutrient in agricultural production, through fertigation systems requires precise determination of application rates and an understanding of phosphorus movement and distribution in the soil layers surrounding crops. This study aimed to evaluate the distribution of soluble phosphorus (SSP) and available phosphorus (SAP) in agricultural soil under maize cultivation and in bare soil during two fertigation cycles over various time periods at the Soil and Water Research Institute (Karaj). After tillage, maize was planted using a strip and single-row method, with row and plant spacings of 60 cm and 15 cm, respectively. Following fertigation in both cycles, using micro auger soil samples were collected from both bare soil and soil under maize at horizontal distances of 5 and 10 cm from the dripper and at depths of 0-5, 5-10, 10-15, 15-20, 20-30, and 30-40 cm at time intervals of 4, 24, 98, and 960 hours, with two plant replications (two sides of each plants). The samples were subsequently transferred to the laboratory for chemical analysis using conventional measurement methods. The results indicated that fertigation, depth, and time significantly affected the distribution of SSP and SAP in both systematic and non-systematic manners. The analysis of variance revealed that the effect of the fertigation cycle treatment on SSP and SAP under maize cultivation at 5 and 10 cm from the fertilizer injection site was significant (at the 1% statistical level), demonstrating a phosphorus movement of approximately 10 cm within this system. As the depth increased, the average SSP and SAP values exhibited a decreasing trend. The maximum average concentration across all treatments was observed 98 hours after fertilizer injection, indicating an optimal time range for easily accessible phosphorus availability. Overall, due to the unique properties of phosphorus in soil—such as low solubility, low mobility, and high stabilization/fixation by the soil matrix—along with its availability for plants, it is preferable to apply phosphorus fertilizers in a soluble form, approximately 5 centimeters away from the crop, and in more frequent applications.The availability and efficient utilization of phosphorus, an essential nutrient in agricultural production, through fertigation systems requires precise determination of application rates and an understanding of phosphorus movement and distribution in the soil layers surrounding crops. This study aimed to evaluate the distribution of soluble phosphorus (SSP) and available phosphorus (SAP) in agricultural soil under maize cultivation and in bare soil during two fertigation cycles over various time periods at the Soil and Water Research Institute (Karaj). After tillage, maize was planted using a strip and single-row method, with row and plant spacings of 60 cm and 15 cm, respectively. Following fertigation in both cycles, using micro auger soil samples were collected from both bare soil and soil under maize at horizontal distances of 5 and 10 cm from the dripper and at depths of 0-5, 5-10, 10-15, 15-20, 20-30, and 30-40 cm at time intervals of 4, 24, 98, and 960 hours, with two plant replications (two sides of each plants). The samples were subsequently transferred to the laboratory for chemical analysis using conventional measurement methods. The results indicated that fertigation, depth, and time significantly affected the distribution of SSP and SAP in both systematic and non-systematic manners. The analysis of variance revealed that the effect of the fertigation cycle treatment on SSP and SAP under maize cultivation at 5 and 10 cm from the fertilizer injection site was significant (at the 1% statistical level), demonstrating a phosphorus movement of approximately 10 cm within this system. As the depth increased, the average SSP and SAP values exhibited a decreasing trend. The maximum average concentration across all treatments was observed 98 hours after fertilizer injection, indicating an optimal time range for easily accessible phosphorus availability. Overall, due to the unique properties of phosphorus in soil—such as low solubility, low mobility, and high stabilization/fixation by the soil matrix—along with its availability for plants, it is preferable to apply phosphorus fertilizers in a soluble form, approximately 5 centimeters away from the crop, and in more frequent applications.https://ijswr.ut.ac.ir/article_102194_a501dfb19ce5c5a4b8eb22a3a92467a2.pdfUniversity of Tehran PressIranian Journal of Soil and Water Research2008-479X56320250522Numerical Modeling of the Effect of Orifices in Stepped Spillways on Flow Energy Dissipation Using the FLOW-3D ModelNumerical Modeling of the Effect of Orifices in Stepped Spillways on Flow Energy Dissipation Using the FLOW-3D Model58960610219510.22059/ijswr.2025.383840.669816FAMehdiDaryaeeDepartment of Water Structures, Faculty of Water and Environmental Engineering, Shahid Chamran University of Ahvaz, Ahvaz, Iran.0000-0003-4304-0240Seyedeh MassomehSharifiDepartment of Water Structures, Faculty of Water and Environmental Engineering, Shahid Chamran University of Ahvaz, Ahvaz, Iran.0009-0003-8023-7146AmirrezaShahriariDepartment of Water Structures, Faculty of Water and Environmental Engineering, Shahid Chamran University of Ahvaz, Ahvaz, Iran.0009-0002-0947-2496SeyedMahmoodKashefipourDepartment of Water Structures, Faculty of Water and Environmental Engineering, Shahid Chamran University of Ahvaz, Ahvaz, Iran.0000-0001-7108-828XMohammadrezaZayeriDepartment of Water Structures, Faculty of Water and Environmental Engineering, Shahid Chamran University of Ahvaz, Ahvaz, Iran.0000-0002-3812-7512Journal Article20241021Stepped spillways, as one of the most efficient hydraulic structures for energy dissipation, play a crucial role in reducing the destructive energy of water discharged from dam reservoirs. These structures, utilizing their geometric features, contribute to the dissipation of turbulent and supercritical flows. In this research, with the aim of increasing the efficiency of stepped spillways in energy dissipation, the effect of creating orifices on the spillway steps has been investigated. The FLOW-3D software was used for numerical simulation, and the model's accuracy was evaluated using statistical indicators. The simulation results indicate that the RNG turbulence model is capable of simulating turbulent flows over stepped spillways with high accuracy (R²=0.96). Creating orifices on the floor of the steps, compared to the walls, generates greater energy dissipation. The outflow from the floor openings of the stepped spillway causes the water jet to collide with the overflow, resulting in greater energy dissipation. In contrast, wall openings, due to their alignment with the overflow direction, lead to less energy loss. Additionally, increasing the number of orifices led to improved spillway performance. Specifically, creating three orifices in the spillway floor was able to increase energy dissipation by 16% compared to the case without orifices (control). Furthermore, creating three orifices in the floor allows a higher discharge to pass through the spillway and increased the initial depth of the hydraulic jump downstream of the spillway by 40%. These results demonstrate the effectiveness of using orifices as an efficient method for improving the performance of stepped spillways in managing outflows from dams.Stepped spillways, as one of the most efficient hydraulic structures for energy dissipation, play a crucial role in reducing the destructive energy of water discharged from dam reservoirs. These structures, utilizing their geometric features, contribute to the dissipation of turbulent and supercritical flows. In this research, with the aim of increasing the efficiency of stepped spillways in energy dissipation, the effect of creating orifices on the spillway steps has been investigated. The FLOW-3D software was used for numerical simulation, and the model's accuracy was evaluated using statistical indicators. The simulation results indicate that the RNG turbulence model is capable of simulating turbulent flows over stepped spillways with high accuracy (R²=0.96). Creating orifices on the floor of the steps, compared to the walls, generates greater energy dissipation. The outflow from the floor openings of the stepped spillway causes the water jet to collide with the overflow, resulting in greater energy dissipation. In contrast, wall openings, due to their alignment with the overflow direction, lead to less energy loss. Additionally, increasing the number of orifices led to improved spillway performance. Specifically, creating three orifices in the spillway floor was able to increase energy dissipation by 16% compared to the case without orifices (control). Furthermore, creating three orifices in the floor allows a higher discharge to pass through the spillway and increased the initial depth of the hydraulic jump downstream of the spillway by 40%. These results demonstrate the effectiveness of using orifices as an efficient method for improving the performance of stepped spillways in managing outflows from dams.https://ijswr.ut.ac.ir/article_102195_4701e58dec9094e02e2e677665647320.pdfUniversity of Tehran PressIranian Journal of Soil and Water Research2008-479X56320250522Uncertainty and Spatial mapping of soil salinity and sodicity using machine learning methods in three different management depths in Abyek regionUncertainty and Spatial mapping of soil salinity and sodicity using machine learning methods in three different management depths in Abyek region60762910219610.22059/ijswr.2025.382783.669797FAAzamJafariSoil Science Department, Faculty of Agriculture, Shahid Bahonar University of Kerman, Kerman, Iran0000-0003-0800-2812FereydoonSarmadiansoil science department< faculty of agricultural engineering and technology, university of Tehran0000-0001-9894-2765ZahraRasaeiSoil Science Department, Faculty of Agricultural, University College of Agriculture and Natural Resources, University of Tehran, Karaj, Iran0000-0001-6683-4890Journal Article20240925Soil salinity and sodicity are affecting soils in arid and semi-arid regions, reducing soil fertility and leading to land degradation, posing threats to the sustainable development of resources. Creating maps of these soil variables throughout soil profile is crucial for effective land management. This study aims to investigate the spatial variability of soil salinity and sodicity in a part of the arid and semi-arid region of Abyek. Three critical depths for the cultivation of important agricultural products (0-50, 0-100, and 0-150 cm) were examined. The models were conducted using 281 soil data and environmental covariates. The modeling and prediction of soil electrical conductivity (salinity) and sodium absorption ratio (sodicity) were performed using four machine learning models: Cubist, random forest, artificial neural network, and XGBoost. The final maps were derived from a simple weighted ensemble model. The model uncertainty was assessed using bootstrapping with 50 repetitions. The results indicated high spatial variability of EC and SAR (exceeding 35%), with an increase from north to south of the region and from surface to deeper soil layers. Results showed that topography, climate, and vegetation are primary controlling factors of spatial distribution of soil salinity and alkalinity. R² for the final models predicting both EC and SAR across all three depths ranged from 0.61 to 0.81, demonstrating the models’ high efficiency, increasing with depth. The highest level of model uncertainty was observed in the southern parts of the region with high variability in EC and SAR values in short distances, fewer soil observations, and less topography, which was lower for models predicting sodium content at all depths compared to salinity. More than 65% of the area was non-saline, while non-alkaline areas covered 70% of it. Acquiring these maps represents a significant step towards improving land management practices based on the land’s potential.Soil salinity and sodicity are affecting soils in arid and semi-arid regions, reducing soil fertility and leading to land degradation, posing threats to the sustainable development of resources. Creating maps of these soil variables throughout soil profile is crucial for effective land management. This study aims to investigate the spatial variability of soil salinity and sodicity in a part of the arid and semi-arid region of Abyek. Three critical depths for the cultivation of important agricultural products (0-50, 0-100, and 0-150 cm) were examined. The models were conducted using 281 soil data and environmental covariates. The modeling and prediction of soil electrical conductivity (salinity) and sodium absorption ratio (sodicity) were performed using four machine learning models: Cubist, random forest, artificial neural network, and XGBoost. The final maps were derived from a simple weighted ensemble model. The model uncertainty was assessed using bootstrapping with 50 repetitions. The results indicated high spatial variability of EC and SAR (exceeding 35%), with an increase from north to south of the region and from surface to deeper soil layers. Results showed that topography, climate, and vegetation are primary controlling factors of spatial distribution of soil salinity and alkalinity. R² for the final models predicting both EC and SAR across all three depths ranged from 0.61 to 0.81, demonstrating the models’ high efficiency, increasing with depth. The highest level of model uncertainty was observed in the southern parts of the region with high variability in EC and SAR values in short distances, fewer soil observations, and less topography, which was lower for models predicting sodium content at all depths compared to salinity. More than 65% of the area was non-saline, while non-alkaline areas covered 70% of it. Acquiring these maps represents a significant step towards improving land management practices based on the land’s potential.https://ijswr.ut.ac.ir/article_102196_b4850a9e6467ff104ac6dc27ecd615bd.pdfUniversity of Tehran PressIranian Journal of Soil and Water Research2008-479X56320250522The effect of tillage systems and residue management on the optimal use of phosphorus in safflower cultivation under saline conditionsThe effect of tillage systems and residue management on the optimal use of phosphorus in safflower cultivation under saline conditions63164810219710.22059/ijswr.2025.383497.669813FAAkbarGandomkar1. Department of Soil and Water Research, Isfahan Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education, and Extension Organization (AREEO), Isfahan, Iran, AREEO, Isfahan, Iran.0000-0002-5415-1168FatemehKhayamimDepartment of Soil and Water Research, Isfahan Agricultural and Natural Resources Research and Educational Center, Agricultural Research, Education, and Extension Organization (AREEO), Isfahan, Iran0009-0008-5903-7867Journal Article20241013The present research investigated the effect of plant residues, different tillage techniques, and phosphorus Fertilizer application on safflower crop yield over two years at the Kabutarabad Agricultural Research Station in Esfahan, which has silty clay loam soil. The experiment was conducted as a one-time split plot with a randomized complete block design and three replications. The main treatments included no-tillage, reduced tillage, and conventional tillage. Sub-treatments included four levels of zero, 50, 75, and 100 percent of the recommended phosphorus fertilizer based on soil tests for each tillage level. The biological yield, seed yield, phosphorus concentration in both leaves and seeds, and absorbable soil phosphorus were measured. The highest increase in absorbable soil phosphorus was noted in the surface soil of no-tillage and reduced-tillage plots, respectively. The application of triple superphosphate significantly increased the mean absorbable soil phosphorus from 3.5 to 25.3 mg/kg. A significant increase in biological yield (16.3 tons per hectare) and safflower seed yield (1.5 tons per hectare) was observed in the treatment with 75% of the recommended phosphorus fertilizer. The net phosphorus uptake by safflower rose from 17.6 kg/ha in the control treatment to 37.6 kg/ha in the 100% fertilizer recommendation treatment. A notable increase in safflower seed yield and total yield was achieved through the presence of plant residues and the use of reduced-tillage and no-tillage methods in conditions of water and soil salinity, indicating the superiority of these methods compared to conventional tillage. The application of 75% of the recommended phosphorus fertilizer was adequate for safflower planting across all tillage types; this level of phosphorus was sufficient. The application was equivalent to a 100% fertilizer recommendation.The present research investigated the effect of plant residues, different tillage techniques, and phosphorus Fertilizer application on safflower crop yield over two years at the Kabutarabad Agricultural Research Station in Esfahan, which has silty clay loam soil. The experiment was conducted as a one-time split plot with a randomized complete block design and three replications. The main treatments included no-tillage, reduced tillage, and conventional tillage. Sub-treatments included four levels of zero, 50, 75, and 100 percent of the recommended phosphorus fertilizer based on soil tests for each tillage level. The biological yield, seed yield, phosphorus concentration in both leaves and seeds, and absorbable soil phosphorus were measured. The highest increase in absorbable soil phosphorus was noted in the surface soil of no-tillage and reduced-tillage plots, respectively. The application of triple superphosphate significantly increased the mean absorbable soil phosphorus from 3.5 to 25.3 mg/kg. A significant increase in biological yield (16.3 tons per hectare) and safflower seed yield (1.5 tons per hectare) was observed in the treatment with 75% of the recommended phosphorus fertilizer. The net phosphorus uptake by safflower rose from 17.6 kg/ha in the control treatment to 37.6 kg/ha in the 100% fertilizer recommendation treatment. A notable increase in safflower seed yield and total yield was achieved through the presence of plant residues and the use of reduced-tillage and no-tillage methods in conditions of water and soil salinity, indicating the superiority of these methods compared to conventional tillage. The application of 75% of the recommended phosphorus fertilizer was adequate for safflower planting across all tillage types; this level of phosphorus was sufficient. The application was equivalent to a 100% fertilizer recommendation.https://ijswr.ut.ac.ir/article_102197_da93019e8399a5e4b2f263c0089db72e.pdfUniversity of Tehran PressIranian Journal of Soil and Water Research2008-479X56320250522Comparison of the efficiency of the single and double-slope solar stills in dry regions (Case study: Zabul city)Comparison of the efficiency of the single and double-slope solar stills in dry regions (Case study: Zabul city)64966310219810.22059/ijswr.2025.379282.669754FAMansourJahantighCorresponding Author, Department of Soil Conservation and Water Management, Sistan Agriculture and edition Natural Resources Research Center (AREEO) Zabol, Iran.0000-0002-9930-0139MoienJahantighDepartment of Soil Conservation and Water Management, Sistan Agriculture and edition Natural Resources Research Center (AREEO) Zabol, Iran.0000-0002-1115-5353Journal Article20240713The Sistan region is experiencing significant water stress due to an ongoing drought and water scarcity crisis. In response, the utilization of saline water resources through desalination techniques has become crucial for addressing diverse water demands in this area. This study explores the efficiency of single and double slope Solar stills in Zabol City. The dimensions of the basin Solar stills were 60×95 cm, which covered with glass. To increase the absorption capacity and reduce thermal energy waste, the tank color was chosen to be dark. Inside the Solar stills thermometer was placed to measure the temperature. The results showed that the evaporative-distillation process lead to remove the pollutant and improve the improved quality indicators, including water hardness (TDS), salinity (EC), and BOD in the produced freshwater. The findings indicated that evaporative distillation led to the removal of pollutants and improved quality indicators, including total dissolved solids (TDS), electrical conductivity (EC), and biochemical oxygen demand (BOD). A comparison of the internal temperatures of the systems indicated that the highest internal temperature was created in the double-slope basin solar stills, which was significantly higher than that of the single-slope type (p ≤ 0.01). The findings also showed that the double-slope solar still had a higher efficiency (28.6%) than the single-slope type (24.5%), which was statistically significant at the one percent level (p ≤ 0.01). Comparing the performance of double-slope and single-slope solar stills showed that the double-slope system has higher performance in producing fresh water, and the use of solar energy is considered a potential for the development of evaporation-distillation desalination plants in the Sistan.The Sistan region is experiencing significant water stress due to an ongoing drought and water scarcity crisis. In response, the utilization of saline water resources through desalination techniques has become crucial for addressing diverse water demands in this area. This study explores the efficiency of single and double slope Solar stills in Zabol City. The dimensions of the basin Solar stills were 60×95 cm, which covered with glass. To increase the absorption capacity and reduce thermal energy waste, the tank color was chosen to be dark. Inside the Solar stills thermometer was placed to measure the temperature. The results showed that the evaporative-distillation process lead to remove the pollutant and improve the improved quality indicators, including water hardness (TDS), salinity (EC), and BOD in the produced freshwater. The findings indicated that evaporative distillation led to the removal of pollutants and improved quality indicators, including total dissolved solids (TDS), electrical conductivity (EC), and biochemical oxygen demand (BOD). A comparison of the internal temperatures of the systems indicated that the highest internal temperature was created in the double-slope basin solar stills, which was significantly higher than that of the single-slope type (p ≤ 0.01). The findings also showed that the double-slope solar still had a higher efficiency (28.6%) than the single-slope type (24.5%), which was statistically significant at the one percent level (p ≤ 0.01). Comparing the performance of double-slope and single-slope solar stills showed that the double-slope system has higher performance in producing fresh water, and the use of solar energy is considered a potential for the development of evaporation-distillation desalination plants in the Sistan.https://ijswr.ut.ac.ir/article_102198_0308a92d73150061a405a9d618b3788f.pdfUniversity of Tehran PressIranian Journal of Soil and Water Research2008-479X56320250522Impact Analysis of the Southern Oscillation Index (SOI) on Precipitation and Relative Humidity across Various Regions of IranImpact Analysis of the Southern Oscillation Index (SOI) on Precipitation and Relative Humidity across Various Regions of Iran66568410219910.22059/ijswr.2025.385089.669830FAAlirezaSaadatmoghaddasiirrigation & reclamation engrg. dept. university of Tehran, Karaj, iran.0009-0004-4096-1372ZahraAghashariatmadariAssociate Prof.,
Irrigation & Reclamation Engrg. Dept.
University of Tehran
Karaj, Iran.0000-0002-9555-086XJournal Article20241110The climate is the result of interactions between the atmosphere and the oceans, manifesting in phenomena such as landslides, extreme events. This study investigates the effects of the Southern Oscillation Index on two key variables: precipitation and relative humidity, across 21 principal synoptic stations in Iran over a 30-year period. Utilizing factor analysis alongside twelve teleconnection indices, this research aims to elucidate the intricate relationships between these climatic factors. Based on the correlation matrix derived from the factor analysis, the eigenvalue magnitudes and the percentage of variance elucidate the extent to which various teleconnection indices influence the simultaneous assessment of atmospheric components. The analysis revealed that the Southern Oscillation Index (SOI) exerts a more pronounced effect compared to other indices. Data were evaluated as three-month averages during the rainfall season, specifically from October to June. Notably, several stations exhibited no significant correlation with the index. The highest correlation was observed at the Shiraz station, with a correlation coefficient of 58%. The climatic characteristics of this region, particularly in its southern areas, represent another significant finding of this research. Although this region is predominantly influenced by the Indian monsoon and Mediterranean currents, the Southern Oscillation Index—resulting from the pressure differences at sea level between Tahiti and Darwin in the eastern and northern Pacific Ocean—also exerts a substantial impact on the precipitation and relative humidity of the area. It is recommended to consider the importance of climate change and one of its manifestations, global warming, in future researches, are considered.The climate is the result of interactions between the atmosphere and the oceans, manifesting in phenomena such as landslides, extreme events. This study investigates the effects of the Southern Oscillation Index on two key variables: precipitation and relative humidity, across 21 principal synoptic stations in Iran over a 30-year period. Utilizing factor analysis alongside twelve teleconnection indices, this research aims to elucidate the intricate relationships between these climatic factors. Based on the correlation matrix derived from the factor analysis, the eigenvalue magnitudes and the percentage of variance elucidate the extent to which various teleconnection indices influence the simultaneous assessment of atmospheric components. The analysis revealed that the Southern Oscillation Index (SOI) exerts a more pronounced effect compared to other indices. Data were evaluated as three-month averages during the rainfall season, specifically from October to June. Notably, several stations exhibited no significant correlation with the index. The highest correlation was observed at the Shiraz station, with a correlation coefficient of 58%. The climatic characteristics of this region, particularly in its southern areas, represent another significant finding of this research. Although this region is predominantly influenced by the Indian monsoon and Mediterranean currents, the Southern Oscillation Index—resulting from the pressure differences at sea level between Tahiti and Darwin in the eastern and northern Pacific Ocean—also exerts a substantial impact on the precipitation and relative humidity of the area. It is recommended to consider the importance of climate change and one of its manifestations, global warming, in future researches, are considered.https://ijswr.ut.ac.ir/article_102199_5f4c2dede5fc1a802639c02223cb952c.pdfUniversity of Tehran PressIranian Journal of Soil and Water Research2008-479X56320250522Investigation of maize root response to different ionic composition using macroscopic reduction functionsInvestigation of maize root response to different ionic composition using macroscopic reduction functions68570010220010.22059/ijswr.2025.384928.669833FAAbouzarBazrafshanDepartment of Soil Science, Faculty of Agricultural Engineering and Technology, College of Agricultural and Natural Resources, University of Tehran, Karaj, Iran0009-0005-4146-3858Mohammad HoseinMohammadiDepartment of Soil Science, Faculty of Agricultural Engineering and Technology, College of Agricultural and Natural Resources, University of Tehran, Karaj, Iran0000-0003-0596-7539MahdiShorafaDepartment of Soil Science, Faculty of Agricultural Engineering and Technology, College of Agricultural and Natural Resources, University of Tehran, Karaj, Iran0000-0002-0880-4850Ali AsgharZolfaghariDesertification Department, Faculty of Desert Science, University of Semnan, Semnan, Iran0000-0001-7337-9849Journal Article20241110In this study, our aim is to investigate the effect of salinity stress of NaCl+CaCl2 and CaCl2 ionic compositions in maize (Zea Mays L.) root mass. Two parallel greenhouse experiments were conducted in pots in a randomized complete design with 4 replicates. The different salinity levels (0, 61, 126, 252 and 336 kPa) were similarly applied in both ionic compositions. The osmotic potential in pots was kept constant after the treatment initiation. The maize root response was investigated using osmotic potential, ion concentration and electrical conductivity salinity parameters and then were evaluated by linear Maas-Hoffman and non-linear van Genuchten-Hoffman models. The imposed salinity stress significantly affected root mass in both NaCl+CaCl2 and CaCl2 ionic compositions. The results of this study revealed that osmotic potential is a more appropriate parameter than ion concentration and electrical conductivity for maize root response to salinity stress. Based on osmotic potential, the salinity threshold values of NaCl+CaCl2 and CaCl2 ionic compositions were obtained 0 kPa and 2.49 kPa, respectively which implies effect of ion type on sensivity of maize root mass to salinity stress. The estimated root mass values using reduction functions indicated that exponential model of van Genuchten-Hoffman in both NaCl+CaCl2 (nRMSE=4.71) and CaCl2 (nRMSE=5.69) ionic compositions had more accuracy than linear model of Maas-Hoffman. In addition, modeling efficiency of exponential model (EF=0.991) was larger than linear model (EF=0.98).In this study, our aim is to investigate the effect of salinity stress of NaCl+CaCl2 and CaCl2 ionic compositions in maize (Zea Mays L.) root mass. Two parallel greenhouse experiments were conducted in pots in a randomized complete design with 4 replicates. The different salinity levels (0, 61, 126, 252 and 336 kPa) were similarly applied in both ionic compositions. The osmotic potential in pots was kept constant after the treatment initiation. The maize root response was investigated using osmotic potential, ion concentration and electrical conductivity salinity parameters and then were evaluated by linear Maas-Hoffman and non-linear van Genuchten-Hoffman models. The imposed salinity stress significantly affected root mass in both NaCl+CaCl2 and CaCl2 ionic compositions. The results of this study revealed that osmotic potential is a more appropriate parameter than ion concentration and electrical conductivity for maize root response to salinity stress. Based on osmotic potential, the salinity threshold values of NaCl+CaCl2 and CaCl2 ionic compositions were obtained 0 kPa and 2.49 kPa, respectively which implies effect of ion type on sensivity of maize root mass to salinity stress. The estimated root mass values using reduction functions indicated that exponential model of van Genuchten-Hoffman in both NaCl+CaCl2 (nRMSE=4.71) and CaCl2 (nRMSE=5.69) ionic compositions had more accuracy than linear model of Maas-Hoffman. In addition, modeling efficiency of exponential model (EF=0.991) was larger than linear model (EF=0.98).https://ijswr.ut.ac.ir/article_102200_c722c3a0141d8ccebbee6869f18478c9.pdfUniversity of Tehran PressIranian Journal of Soil and Water Research2008-479X56320250522Evaluation of GPR-PSO and KNN-PSO data-mining models for prediction of suspended sediment concentration distributionEvaluation of GPR-PSO and KNN-PSO data-mining models for prediction of suspended sediment concentration distribution70171410220210.22059/ijswr.2025.377078.669846FAMohsenNasrabadiDepartment of Water Science and Engineering, Faculty of Agriculture and Environment, Arak University, Arak, Iran.0000-0001-8061-8836YaserMehriDepratment of Irrigation and Reclamation Engineering, University College of Agriculture and Natural Resources, University of Tehran, Karaj, Iran.0000-0002-1420-3445Ali AbdolrazaqSabbarDepartment of Water Science and Engineering, Faculty of Agriculture and Environment, Arak University, Arak, Iran0009-0001-0872-8034MohammadJavadNahviniaDepartment of Water Science and Engineering, Faculty of Agriculture and Environment, Arak University, Arak, Iran0000-0002-5833-7744Journal Article20241203The vertical distribution of suspended sediment concentration (SSC) is one of the most important parameters in the hydraulics of sediment transport in rivers. This parameter plays an important role in calculating the total sediment discharge in channels and rivers. For this reason, accurate measurement of this parameter has always been one of the goals of researchers. One way to accurately predict this parameter is to use intelligent models. For this purpose, in this study, four data mining models, KNN, KNN-PSO, GPR, and GPR-PSO, have been used to predict the distribution of sediment concentration (C/Ca). All models were coded in the MATLAB software environment. According to the results, it was found that the optimization performed on the KNN and GPR models was effective and increased the performance of these models. By comparing the models, it was shown that the GPR-PSO model has more accuracy than other models. The accuracy of this model in the training phase is equal to RMSE = 0.0297, R2 = 0.9878, and KGE = 0.9776, and in the testing phase equal to RMSE = 0.0226, R2 = 0.9907, and KGE = 0.9715. After GPR-PSO, the KNN-PSO model was ranked with RMSE = 0.0295, R2 = 0.9870, and KGE = 0.9864 in the training phase and RMSE = 0.0374, R2 = 0.9808, and KGE = 0.9569 in the testing phase. After the aforementioned models, GPR and KNN were respectively ranked. Also, by analyzing the results, it was determined that the two parameters y/D and y/a are the most important parameters in determining the most accurate results.The vertical distribution of suspended sediment concentration (SSC) is one of the most important parameters in the hydraulics of sediment transport in rivers. This parameter plays an important role in calculating the total sediment discharge in channels and rivers. For this reason, accurate measurement of this parameter has always been one of the goals of researchers. One way to accurately predict this parameter is to use intelligent models. For this purpose, in this study, four data mining models, KNN, KNN-PSO, GPR, and GPR-PSO, have been used to predict the distribution of sediment concentration (C/Ca). All models were coded in the MATLAB software environment. According to the results, it was found that the optimization performed on the KNN and GPR models was effective and increased the performance of these models. By comparing the models, it was shown that the GPR-PSO model has more accuracy than other models. The accuracy of this model in the training phase is equal to RMSE = 0.0297, R2 = 0.9878, and KGE = 0.9776, and in the testing phase equal to RMSE = 0.0226, R2 = 0.9907, and KGE = 0.9715. After GPR-PSO, the KNN-PSO model was ranked with RMSE = 0.0295, R2 = 0.9870, and KGE = 0.9864 in the training phase and RMSE = 0.0374, R2 = 0.9808, and KGE = 0.9569 in the testing phase. After the aforementioned models, GPR and KNN were respectively ranked. Also, by analyzing the results, it was determined that the two parameters y/D and y/a are the most important parameters in determining the most accurate results.https://ijswr.ut.ac.ir/article_102202_ce76257a7153b75400c7753635bd90b9.pdfUniversity of Tehran PressIranian Journal of Soil and Water Research2008-479X56320250522Evaluation the effect of root morphological characteristics on phosphorus uptake in rice cultivars (Oryza sativa L.)Evaluation the effect of root morphological characteristics on phosphorus uptake in rice cultivars (Oryza sativa L.)71573410220310.22059/ijswr.2025.384338.669819FASogandShirinpourDepartment of Agronomy and Plant Breeding, Faculty of Agricultural Sciences, University of Guilan, Rasht, Iran0009-0002-0756-7782MasoudEsfahaniDepartment of Agronomy and Plant Breeding, Faculty of Agricultural Sciences, University of Guilan, Rasht, Iran0000-0003-2288-7944AlieazaFallah NosratabadDepartment of Soil Biology, Soil and Water Research Institute of Iran, Karaj, Iran0000-0002-4909-6782ShahramMahmoudsoltaniDepartment of Soil and Water, Rice Research Institute of Iran, Rasht, Iran0000-0002-1300-9536AliAalamiDepartment of Agronomy and Plant Breeding, Faculty of Agricultural Sciences, University of Guilan, Rasht, Iran0000-0002-6791-833XJournal Article20241025To investigate the effect of root morphological characteristic on phosphorus uptake in rice cultivars, a factorial experiment was carried out using a completely randomized design in an open field at the Rice Research Institute of Iran, Rasht, during the spring of 2022. The experimental treatments included 10 rice cultivars (four local cultivars; Hashemi, Hassani, Ali-Kazemi and Domsiah and four improved cultivars; Gilaneh, Anam, Shiroudi and Khazar and two control cultivars; Ahlami Tarom and Neda) and two levels of soil phosphorus including four mg.kg-1 and 60 mg.kg-1. Results showed that there was a significant difference between rice cultivars in terms of the measured root morphological characteristics, and Ahlami Tarom and Shiroudi cultivars with extensive root structure in terms of volume and surface had higher phosphorus uptake efficiency. Ahlami Tarom and Shiroudi cultivars exhibited the highest values for root characteristics, while Gilaneh and Khazar cultivars showed the lowest. Significant differences were observed among rice cultivars in terms of shoot dry weight, total shoot phosphorus concentration and uptake, as well as phosphorus uptake and phosphorus use efficiency. the highest amount of total phosphorus concentration and phosphorus uptake and phosphorus use efficiency were 3.2 mg.g-1, 37.9% and 88% respectively and 2.9 mg.g-1, 32.5% and 64% respectively) in Ahlami Tarom and Shiroudi cultivars, respectively. Based on the results of the cluster analysis, rice cultivars were categorized into two groups, each exhibiting similar characteristics. Additionally, factor analysis identified two main factors, including morphological and functional root characteristics, which significantly explained the variations in root-related characteristics. Based on the results of this experiment, Ahlami Tarom and Shiroudi rice cultivars appear to be better adapted to conditions of soil phosphorus deficiency, and their cultivation in areas with such deficiencies may be recommended.To investigate the effect of root morphological characteristic on phosphorus uptake in rice cultivars, a factorial experiment was carried out using a completely randomized design in an open field at the Rice Research Institute of Iran, Rasht, during the spring of 2022. The experimental treatments included 10 rice cultivars (four local cultivars; Hashemi, Hassani, Ali-Kazemi and Domsiah and four improved cultivars; Gilaneh, Anam, Shiroudi and Khazar and two control cultivars; Ahlami Tarom and Neda) and two levels of soil phosphorus including four mg.kg-1 and 60 mg.kg-1. Results showed that there was a significant difference between rice cultivars in terms of the measured root morphological characteristics, and Ahlami Tarom and Shiroudi cultivars with extensive root structure in terms of volume and surface had higher phosphorus uptake efficiency. Ahlami Tarom and Shiroudi cultivars exhibited the highest values for root characteristics, while Gilaneh and Khazar cultivars showed the lowest. Significant differences were observed among rice cultivars in terms of shoot dry weight, total shoot phosphorus concentration and uptake, as well as phosphorus uptake and phosphorus use efficiency. the highest amount of total phosphorus concentration and phosphorus uptake and phosphorus use efficiency were 3.2 mg.g-1, 37.9% and 88% respectively and 2.9 mg.g-1, 32.5% and 64% respectively) in Ahlami Tarom and Shiroudi cultivars, respectively. Based on the results of the cluster analysis, rice cultivars were categorized into two groups, each exhibiting similar characteristics. Additionally, factor analysis identified two main factors, including morphological and functional root characteristics, which significantly explained the variations in root-related characteristics. Based on the results of this experiment, Ahlami Tarom and Shiroudi rice cultivars appear to be better adapted to conditions of soil phosphorus deficiency, and their cultivation in areas with such deficiencies may be recommended.https://ijswr.ut.ac.ir/article_102203_9acadc238d6036baef4b9ea50b8073de.pdfUniversity of Tehran PressIranian Journal of Soil and Water Research2008-479X56320250522Improving Precipitation Accuracy: A Rescaling Method for PERSIANN Using NDVI, LST, and DEM DataImproving Precipitation Accuracy: A Rescaling Method for PERSIANN Using NDVI, LST, and DEM Data73575110220410.22059/ijswr.2025.384891.669827FAZahraShirmohammadi -AliakbarkhaniDepartment of Water Science and Engineering, Faculty of Agriculture and Animal Sciences, University of Torbat-e Jam, Iran0000-0001-6332-8976Journal Article20241105This study is based on the rain gauge data from Torbat-e Jam over a 23-year period (2001–2023). PERSIANN satellite rainfall data with a spatial resolution of 27 kilometers were enhanced to a 1-kilometer resolution using NDVI, land surface temperature (LST), and digital elevation model (DEM) data, aided by the random forest (RF) algorithm. To evaluate the accuracy of satellite rainfall downscaling compared to ground station data, statistical metrics such as correlation coefficient (CC), root mean square error (RMSE), and mean absolute error (MAE) were utilized. Additionally, a residual correction method was implemented to refine model predictions further. Results demonstrated that integrating spatial datasets with the RF algorithm significantly improved rainfall modeling accuracy. Applying the residual correction method led to substantial improvements in forecasting accuracy across all studied stations on both monthly and annual timescales. On the monthly scale, the correlation coefficient increased by 22-29%, while RMSE and MAE decreased by 61-64% and 60-68%, respectively. On an annual scale, the correlation coefficient showed an increase of 7-35%, with RMSE and MAE reductions of 69-74% and 69-76%, respectively. This study underscores the effectiveness of the applied method in enhancing prediction accuracy across various temporal scales within the studied region. Additionally, the practical implications of this research provide valuable insights for hydrological modeling and water resource management, especially in regions with limited ground station data. The findings of this research can significantly aid in better water resource management and climatic planning, particularly in arid and semi-arid areas.This study is based on the rain gauge data from Torbat-e Jam over a 23-year period (2001–2023). PERSIANN satellite rainfall data with a spatial resolution of 27 kilometers were enhanced to a 1-kilometer resolution using NDVI, land surface temperature (LST), and digital elevation model (DEM) data, aided by the random forest (RF) algorithm. To evaluate the accuracy of satellite rainfall downscaling compared to ground station data, statistical metrics such as correlation coefficient (CC), root mean square error (RMSE), and mean absolute error (MAE) were utilized. Additionally, a residual correction method was implemented to refine model predictions further. Results demonstrated that integrating spatial datasets with the RF algorithm significantly improved rainfall modeling accuracy. Applying the residual correction method led to substantial improvements in forecasting accuracy across all studied stations on both monthly and annual timescales. On the monthly scale, the correlation coefficient increased by 22-29%, while RMSE and MAE decreased by 61-64% and 60-68%, respectively. On an annual scale, the correlation coefficient showed an increase of 7-35%, with RMSE and MAE reductions of 69-74% and 69-76%, respectively. This study underscores the effectiveness of the applied method in enhancing prediction accuracy across various temporal scales within the studied region. Additionally, the practical implications of this research provide valuable insights for hydrological modeling and water resource management, especially in regions with limited ground station data. The findings of this research can significantly aid in better water resource management and climatic planning, particularly in arid and semi-arid areas.https://ijswr.ut.ac.ir/article_102204_958cf76990e9ccf502442ead34e224b0.pdfUniversity of Tehran PressIranian Journal of Soil and Water Research2008-479X56320250522Evaluation of drainage systems performance using digital soil salinity mappingEvaluation of drainage systems performance using digital soil salinity mapping75377010220510.22059/ijswr.2025.387219.669857FAFarhadDehghaniFaculty member, National Salinity Research Center (NSRC), Agricultural Research, Education and Extension Organization (AREEO), Yazd, Iran0000-0002-4736-1669YosefHasheminejhadFaculty member, Khorasan Razavi Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization (AREEO), Mashhad, Iran0000-0002-7901-1161AmirParnianFaculty member, National Salinity Research Center (NSRC), Agricultural Research, Education and Extension Organization (AREEO), Yazd, Iran0000-0002-7379-8119NadiaBesharatNational Salinity Research Center (NSRC), Agricultural Research, Education and Extension Organization (AREEO), Yazd, Iran0009-0005-0503-3164Journal Article20241220A Latin hypercube sampling approach was employed to evaluate the drainage system performance in rehabilitated and modernized lands in Tanour-Lahour, Yazd Province. This determined the locations for collecting 147 soil samples, 28 water samples, and 225 electromagnetic conductivity readings. Soil and water salinity and ionic composition used to interpolate and create root zone soil salinity variation maps. The regression results showed that in both cases, only the device measurement in the horizontal position has a significant relationship with the average root zone soil salinity. Accordingly, the assessment of soil salinity based only on traditional sampling and laboratory analysis cannot provide a proper view of the salinity and also an overview of the performance of the drainage system. The land’s soil salinity estimation using apparent electrical conductivity data showed a better relationship between the plant health status and the performance of the land’s drainage system. Accordingly, the soil salinity in the middle lands has been completely controlled in such a way that the ECe has even reached less than the irrigation water EC, while in the marginal lands equipped by the drainage system and where the drainage occurred only by the main drainage ditch, the soil salinity values were higher than middle lands. The time sequence of drainage salinity indicates that the drainage water salinity was almost constant in time. The drainage salinity in the collectors remained constant about 20dS/m and in the main drain ditch about 33 dS/m. These conditions indicate that the drainage system has approached steady or quasi-steady conditions. A Latin hypercube sampling approach was employed to evaluate the drainage system performance in rehabilitated and modernized lands in Tanour-Lahour, Yazd Province. This determined the locations for collecting 147 soil samples, 28 water samples, and 225 electromagnetic conductivity readings. Soil and water salinity and ionic composition used to interpolate and create root zone soil salinity variation maps. The regression results showed that in both cases, only the device measurement in the horizontal position has a significant relationship with the average root zone soil salinity. Accordingly, the assessment of soil salinity based only on traditional sampling and laboratory analysis cannot provide a proper view of the salinity and also an overview of the performance of the drainage system. The land’s soil salinity estimation using apparent electrical conductivity data showed a better relationship between the plant health status and the performance of the land’s drainage system. Accordingly, the soil salinity in the middle lands has been completely controlled in such a way that the ECe has even reached less than the irrigation water EC, while in the marginal lands equipped by the drainage system and where the drainage occurred only by the main drainage ditch, the soil salinity values were higher than middle lands. The time sequence of drainage salinity indicates that the drainage water salinity was almost constant in time. The drainage salinity in the collectors remained constant about 20dS/m and in the main drain ditch about 33 dS/m. These conditions indicate that the drainage system has approached steady or quasi-steady conditions. https://ijswr.ut.ac.ir/article_102205_93100e77ca06add19c1893ec36ff1dd8.pdfUniversity of Tehran PressIranian Journal of Soil and Water Research2008-479X56320250522Identification of high-risk areas and ground fissures caused by land subsidence using the estimation of horizontal displacement components and subsidence gradient maps, case study: Kashan plain subsidenceIdentification of high-risk areas and ground fissures caused by land subsidence using the estimation of horizontal displacement components and subsidence gradient maps, case study: Kashan plain subsidence77178410220610.22059/ijswr.2025.385160.669836FAMasoomeAmighpeyHead of leveling and InSAR office, National cartographic center of Iran, Tehran, Iran.0000-0003-4670-8808SiyavashArabideputy of Land surveying department, National cartographic center of Iran, Tehran, Iran.0009-0005-7218-5459FatemeGhoraiyanLand surveying department, National cartographic center of Iran0009-0008-5424-8868Journal Article20241112
Earth surface subsidence due to the over-extraction of underground water resources is considered a global crisis, which causes serious economic damage and threatens the safety of the residents of these areas. One of the most important subsidence risks is the formation and development of ground fissures. Identifying areas with surface ruptures can play a significant role in risk management and assessing, strengthening, and improving the structures located in these areas. The ground ruptures in the Kashan Plain are a clear example of surface ruptures caused by excessive extraction of underground water resources and land subsidence. Since horizontal displacements have also occurred in ruptures caused by land subsidence, estimating the horizontal component of subsidence can help locate the places where ruptures are formed. On the other hand, fissures occur in areas with asymmetric subsidence due to the change in the slope of the bedrock. Therefore, determination of the vertical displacement gradient can lead to the identification of places with high changes in the displacement rate and, as a result, the places where cracks are created. In this research, for the first time, the horizontal displacement component and the subsidence gradient map for Kashan Plain, obtained from the radar interferometry measurements. These maps are applied to identify the probable places of ruptures. Field visits have shown that the location of the ruptures is consistent with places with horizontal displacement and high subsidence gradients.
Earth surface subsidence due to the over-extraction of underground water resources is considered a global crisis, which causes serious economic damage and threatens the safety of the residents of these areas. One of the most important subsidence risks is the formation and development of ground fissures. Identifying areas with surface ruptures can play a significant role in risk management and assessing, strengthening, and improving the structures located in these areas. The ground ruptures in the Kashan Plain are a clear example of surface ruptures caused by excessive extraction of underground water resources and land subsidence. Since horizontal displacements have also occurred in ruptures caused by land subsidence, estimating the horizontal component of subsidence can help locate the places where ruptures are formed. On the other hand, fissures occur in areas with asymmetric subsidence due to the change in the slope of the bedrock. Therefore, determination of the vertical displacement gradient can lead to the identification of places with high changes in the displacement rate and, as a result, the places where cracks are created. In this research, for the first time, the horizontal displacement component and the subsidence gradient map for Kashan Plain, obtained from the radar interferometry measurements. These maps are applied to identify the probable places of ruptures. Field visits have shown that the location of the ruptures is consistent with places with horizontal displacement and high subsidence gradients.https://ijswr.ut.ac.ir/article_102206_89a5499ee65c1b2533ab100e11fa2e54.pdfUniversity of Tehran PressIranian Journal of Soil and Water Research2008-479X56320250522Spatio-temporal analysis and future prediction of land use changes using multitemporal remotely sensed data and GIS techniques in Hirmand River BasinSpatio-temporal analysis and future prediction of land use changes using multitemporal remotely sensed data and GIS techniques in Hirmand River Basin78580510220710.22059/ijswr.2025.386623.669848FAMahboubehEbrahimianDepartment of Water Resources Management. Hamoun International Wetland Research Institute, Research Institute of Zabol.0000-0002-0215-5634RoghayehKaramiDepartment of Natural Ecosystem Management, Hamoun International Wetland Research Institute, Research Institute of Zabol0009-0007-3606-5083Journal Article20241207This study aimed to analyze and quantify land use/land cover changes in the transboundary Hirmand River basin over the past 30 years and to predict probable changes for next 20 years. Land cover maps of 1992, 2002, and 2022 were generated using Landsat images of TM and OLI sensors. The Random Forest algorithm was employed for classification and identification of land use classes. The overall accuracy and Kappa index for all classified maps were over 80% and 0.78, respectively. CA-Markov model was used to predict the changes using the land use maps first simulated for 2022, after validation, the future maps of 2030 and 2040 projected. The Kappa index of 0.82 indicated the model's high ability to simulate land use and cover changes in the basin. Water bodies experienced a 97% reduction from 1992 to 2022, with a significant portion of the remaining water body related to the Hamoun Wetland. This trend is expected to reverse slightly, with the water body area increasing from 0.05% in 2022 to 0.36% and 0.37% in 2030 and 2040, respectively. Forests have lost 20% of area, and this decline is likely to continue. Dense rangelands have lost approximately 75% of their areas by 2022, and it is projected that they will decline to 34% by 2040, while poor rangelands have increased by around 2%. Meanwhile, agricultural land has expanded by approximately 115% by 2022, increasing from 2.72% to 5.88%. It is anticipated that agricultural land will experience a further increase of 20–30% by 2040.This study aimed to analyze and quantify land use/land cover changes in the transboundary Hirmand River basin over the past 30 years and to predict probable changes for next 20 years. Land cover maps of 1992, 2002, and 2022 were generated using Landsat images of TM and OLI sensors. The Random Forest algorithm was employed for classification and identification of land use classes. The overall accuracy and Kappa index for all classified maps were over 80% and 0.78, respectively. CA-Markov model was used to predict the changes using the land use maps first simulated for 2022, after validation, the future maps of 2030 and 2040 projected. The Kappa index of 0.82 indicated the model's high ability to simulate land use and cover changes in the basin. Water bodies experienced a 97% reduction from 1992 to 2022, with a significant portion of the remaining water body related to the Hamoun Wetland. This trend is expected to reverse slightly, with the water body area increasing from 0.05% in 2022 to 0.36% and 0.37% in 2030 and 2040, respectively. Forests have lost 20% of area, and this decline is likely to continue. Dense rangelands have lost approximately 75% of their areas by 2022, and it is projected that they will decline to 34% by 2040, while poor rangelands have increased by around 2%. Meanwhile, agricultural land has expanded by approximately 115% by 2022, increasing from 2.72% to 5.88%. It is anticipated that agricultural land will experience a further increase of 20–30% by 2040.https://ijswr.ut.ac.ir/article_102207_21eab4e033c379d31c61a4e64419028c.pdfUniversity of Tehran PressIranian Journal of Soil and Water Research2008-479X56320250522Investigating the effect of biochar and humic acid application on nutrient content and grain yield of chickpeaInvestigating the effect of biochar and humic acid application on nutrient content and grain yield of chickpea80782310220810.22059/ijswr.2025.382702.669796FAHamidNaseri Nejadcrop production, College of Agriculture & Natural Resources Gonbad Kavous University0009-0003-8980-5744MasoumehNaeemicrop production, College of Agriculture & Natural Resources Gonbad Kavous University0000-0001-7676-6289AliNakhzari MoghaddamCrop Ecology
Department of Plant Production
College of Agriculture & Natural Resources
Gonbad Kavous University
Golestan, Iran0000-0003-2282-6973MehdiZareiDepartment of Plant Production
College of Agriculture & Natural Resources
Gonbad Kavous University
Golestan, Iran0000-0001-8222-7388Journal Article20240924To investigate the effect of humic acid and biochar application on the quantitative and qualitative characteristics of chickpea (Cicer arietinum L.), a factorial experiment was conducted in a randomized complete block design with three replications at the research farm of Gonbad Kavous University during the 2018-2019 growing season. The factors studied included biochar at two levels (no application and application of 20 tons per hectare) and humic acid at three levels (no application, application with irrigation water at a concentration of 10 kg per hectare, and application with irrigation water along with two foliar applications at a concentration of 250 cc in 100 liters of water). The results showed that the main effects of biochar and humic acid on various traits, including the number of seeds, total plant weight, 100-seed weight, harvest index, grain yield, and levels of nitrogen, protein, potassium, calcium, and magnesium, were significant. Additionally, the interaction effect of these two factors on 100-seed weight, harvest index, and grain yield was significant. The use of humic acid and biochar improved all the traits studied. The highest grain yield (2983 kg.ha-1) was obtained from the treatment of humic acid application once in the soil and twice as foliar spray along with biochar, while the lowest grain yield (1368 kg.ha-1) was related to the treatment without humic acid and biochar application. Moreover, the highest protein and nitrogen content and the concentrations of calcium, potassium, and magnesium were observed in the treatment with humic acid and biochar application. Therefore, for increasing the yield of chickpea, it is recommended to use humic acid once in the soil and twice as foliar spray along with biochar.To investigate the effect of humic acid and biochar application on the quantitative and qualitative characteristics of chickpea (Cicer arietinum L.), a factorial experiment was conducted in a randomized complete block design with three replications at the research farm of Gonbad Kavous University during the 2018-2019 growing season. The factors studied included biochar at two levels (no application and application of 20 tons per hectare) and humic acid at three levels (no application, application with irrigation water at a concentration of 10 kg per hectare, and application with irrigation water along with two foliar applications at a concentration of 250 cc in 100 liters of water). The results showed that the main effects of biochar and humic acid on various traits, including the number of seeds, total plant weight, 100-seed weight, harvest index, grain yield, and levels of nitrogen, protein, potassium, calcium, and magnesium, were significant. Additionally, the interaction effect of these two factors on 100-seed weight, harvest index, and grain yield was significant. The use of humic acid and biochar improved all the traits studied. The highest grain yield (2983 kg.ha-1) was obtained from the treatment of humic acid application once in the soil and twice as foliar spray along with biochar, while the lowest grain yield (1368 kg.ha-1) was related to the treatment without humic acid and biochar application. Moreover, the highest protein and nitrogen content and the concentrations of calcium, potassium, and magnesium were observed in the treatment with humic acid and biochar application. Therefore, for increasing the yield of chickpea, it is recommended to use humic acid once in the soil and twice as foliar spray along with biochar.https://ijswr.ut.ac.ir/article_102208_872b9409d89a588af072c3c414022400.pdfUniversity of Tehran PressIranian Journal of Soil and Water Research2008-479X56320250522Application of the Combination of Remote Sensing and Machine Learning Approaches in Predicting Hydrological Parameters: A Bibliometric AnalysisApplication of the Combination of Remote Sensing and Machine Learning Approaches in Predicting Hydrological Parameters: A Bibliometric Analysis82585010220910.22059/ijswr.2025.386927.669850FAMoeinTosanDepartment of Water Science and Engineering, Faculty of Agriculture, University of Birjand, Birjand, Iran.0009-0006-8718-3445RaziyehShamshirgaranDepartment of Civil Engineering, Faculty of Engineering, University of Birjand, Birjand, Iran.0000-0001-9599-3356MehdiDastouraniDepartment of Water Science and Engineering, Faculty of Agriculture, University of Birjand, Birjand, Iran.0000-0001-7718-9604Journal Article20241212The integration of remote sensing data with machine learning (ML) techniques has emerged as a robust and effective paradigm for predicting key hydrological parameters, including evapotranspiration, soil moisture content, and land surface temperature. This study presents a comprehensive scientometric analysis of research trends and international collaborative networks within this rapidly evolving field. Data pertinent to this investigation were retrieved from the Web of Science Core Collection database and subsequently analyzed using the Bibliometrix R package and VOSviewer software. These analyses facilitated the identification and visualization of complex interrelationships among scholarly publications, contributing authors, topical keywords, and affiliated countries/institutions. The findings reveal a prominent trend toward the application of advanced ML algorithms, such as Artificial Neural Networks (ANNs) and Random Forest (RF), in conjunction with remotely sensed data acquired from platforms like MODIS, Sentinel, and SMAP, particularly in regions characterized by limited in situ observational data. Furthermore, the utilization of multi-source data fusion and sophisticated ML algorithms for enhanced simulation accuracy of hydrological processes and improved predictive capabilities for climate change impacts and drought events has been identified as a key emerging research direction. Notably, the increasing reliance on satellite-derived datasets, including MODIS, SMAP, and the Normalized Difference Vegetation Index (NDVI), for hydrological parameter estimation in data-scarce environments constitutes another significant observation. Beyond identifying prevailing research trends, this study critically examines existing challenges, knowledge gaps, and potential avenues for future research endeavors in this domain.The integration of remote sensing data with machine learning (ML) techniques has emerged as a robust and effective paradigm for predicting key hydrological parameters, including evapotranspiration, soil moisture content, and land surface temperature. This study presents a comprehensive scientometric analysis of research trends and international collaborative networks within this rapidly evolving field. Data pertinent to this investigation were retrieved from the Web of Science Core Collection database and subsequently analyzed using the Bibliometrix R package and VOSviewer software. These analyses facilitated the identification and visualization of complex interrelationships among scholarly publications, contributing authors, topical keywords, and affiliated countries/institutions. The findings reveal a prominent trend toward the application of advanced ML algorithms, such as Artificial Neural Networks (ANNs) and Random Forest (RF), in conjunction with remotely sensed data acquired from platforms like MODIS, Sentinel, and SMAP, particularly in regions characterized by limited in situ observational data. Furthermore, the utilization of multi-source data fusion and sophisticated ML algorithms for enhanced simulation accuracy of hydrological processes and improved predictive capabilities for climate change impacts and drought events has been identified as a key emerging research direction. Notably, the increasing reliance on satellite-derived datasets, including MODIS, SMAP, and the Normalized Difference Vegetation Index (NDVI), for hydrological parameter estimation in data-scarce environments constitutes another significant observation. Beyond identifying prevailing research trends, this study critically examines existing challenges, knowledge gaps, and potential avenues for future research endeavors in this domain.https://ijswr.ut.ac.ir/article_102209_e7d278a2f3c239afeaf9526d7e275401.pdf