مجله آب و خاک

Introduction Today, the crisis of water resources is one of the biggest challenges of human societies. Population growth and industrialization have increased the demand for water consumption. The agricultural sector is facing many problems to supply the required water resources. Irrigation management and the use of plastic mulches play a crucial role in raised-bed cultivation of horticultural and medicinal plants, serving various purposes such as enhancing quality and increasing yield. Moreover, given the current water scarcity conditions, improving the quantitative and qualitative yield of medicinal plants relies heavily on effective irrigation management and efficient cultivation practices. Material and Methods In this research, a split-plot experiment was conducted using a randomized complete block design (RCBD). The experimental treatments included: the main factor of irrigation management (IM) with four levels (IM100, IM80, IM60 and IM40) and the sub-factor of plastic mulch (PM) with two levels (black plastic mulch (PM1) and no mulch (PM0)) with 3 replications during the growth season 2022-2023 and was conducted at Sari Agricultural Sciences and Natural Resources University (SANRU), Iran. The dimensions of the experimental plot was arranged as 1.80 × 1.20 meters (length and width). Lemon balm was planted in rows with a spacing of 30 cm between plants and 40 cm between rows. Soil moisture was measured by weight method and irrigation was done manually with a sprinkler. In the end, the data obtained from measuring water productivity (WP), relative water content (RWC), essential oil content, morphological and biochemical characteristics of lemon balm were analyzed using ANOVA of SAS software. The Duncan multiple range post hoc test was employed to compare treatment means. Result Based on the findings, the interaction effect of irrigation management and plastic mulch on water productivity was significant. So, the IM100 conditions and PM1, the highest water productivity was observed with 38.5 kg.m-3 and the lowest amount was related to IM40 and PM0 25 kg m-3. The results showed that the simple effect of IM on the RWC in IM100 was very noticeable and obvious compared to other IMs. The highest (74.3%) RWC was observed in IM100, while the lowest RWC was related to IM40 (40.1%). In PM1, the highest amount of RWC (62.1%) was observed and the lowest amount was related to the PM0 (51.8%). The results showed that vegetative wet and dry weight, leaf area index (LAI) and the number of lateral branches of lemon balm increased under the IMs and PM1 affect compared to the control (PM0). The comparison of averages indicated that the highest wet and dry root weights were 217 kg ha-1 and 140.8 kg ha-1, respectively, observed in the IM100 treatment. Additionally, the highest wet and dry root weights under the plastic mulch treatment (PM1) were 151.1 kg ha-1 and 108.5 kg ha-1, respectively. The results also showed that the highest vegetative wet and dry weights were recorded at 647.2 kg ha-1 and 231 kg ha-1, respectively, in the IM100 treatment. Furthermore, the interaction effect of irrigation management (IM) and plastic mulch (PM) on the leaf area index revealed that the highest LAI value (2.8) was observed in the IM100 and PM1 combination. This was while the lowest value of the LAI was related to IM40 and PM0. The interaction effect of IM and PM on the number of lateral branches indicated that IM100 and PM1, the highest number of lateral branches (12) was generated. Based on the obtained results, the highest amount of phenol and flavonoids content were related to IM40 and PM0 with 13.4 mg.GA g-1 and 14.6 mg.QU g-1, respectively. While their lowest amount was observed under IM100 and PM1 with 10.2 mg.GA g-1 and 11.8 mg.QU g-1, respectively. Also, the results showed that the highest essential oil content was related to IM100 and IM80 conditions with 1.14% and 1.13 %, respectively, and the lowest was observed in IM40 condition with 0.53%. Conclusion The evaluation of the irrigation management and plastic mulch effects on water productivity and quantitative and qualitative yield of lemon balm showed that the use of plastic mulch by maintaining soil moisture and improving cultivation conditions, increased the vegetative growth and some qualitative characteristics. In general, due to the crisis of lack of water resources and the challenge of water scarcity, irrigation under IM80 conditions and the use of black plastic mulch in the rise-bed of lemon balm are suggested.

Introduction The study of soil mean weight diameter (MWD) of wet aggregates that is important for sustainable soil management, has recently received much attention. As the prediction of MWD is challenging, laborious, and time-consuming, there is a crucial need to develop a predictive estimation method to generate helpful information required for the soil health assessment to save time and cost involved in soil analysis. Therefore, it is useful to use different models such as multiple linear regression (MLR) and intelligent models including artificial neural network (ANN) and gene expression programming (GEP) to estimate MWD of wet aggregates through easily accessible and low-cost soil properties. The objectives of this study were (1) to creating MLR, ANN and GEP models for predicting MWD from the easily measurable soil variables in forest, range and cultivated lands of the Fandoghloo region of Ardabil province, (2) to compare the precision of the mentioned models in the prediction of MWD of wet aggregates using the coefficient of determination (R2), root mean square error (RMSE), mean error (ME) and Nash-Sutcliffe coefficient (NS) criteria. Materials and Methods Disturbed and undisturbed soil samples (n= 80) were nearly systematically taken from 0-10 cm depth with nearly 50 m distance in forest (n= 20), range (n= 23) and cultivated (n= 37) lands of the Fandoghloo region of Ardabil province, Iran (lat. 38° 24' 10" to 38° 24' 25" N, long. 48° 32' 45" to 48° 33' 5" E) in summer 2023. The contents of sand, silt, clay, CaCO3, pH, EC, bulk (BD) and particle (PD) density, organic carbon (OC), geometric mean diameter (GMD) of dry aggregates were determined in the laboratory using standard methods. Total porosity (n) was calculated using BD and PD data (n= 1-BD/PD). The mean geometric diameter (dg) and geometric standard deviation (σg) of soil particles were computed by sand, silt and clay percentages. The mean weight diameter (MWD) of wet aggregates was measured in the aggregates smaller than 4.75 mm by wet sieving equipment using sieves with 2, 1, 0.5, 0.25 and 0.106 mm pore diameter. All data were randomly divided into two series as 60 data for training and 20 data for testing of models. The SPSS 22 software with the stepwise method, MATLAB and Gene Xpro Tools 4.0 software were used to derive multiple linear regression (MLR), artificial neural network (ANN) and gene expression programming (GEP) models, respectively. A feed forward three-layer (9, 8, 6 and 6 neurons in the hidden layer) perceptron network and the tangent sigmoid transfer function were used for the ANN modeling. A set of optimal parameters were chosen before developing the best GEP model. The number of chromosomes and genes, head size and linking function were selected by the trial and error method, and they are 30, 3, 8, and +, respectively. The rates of genetic operators were chosen according to literature studies. The precision of MLR, ANN and GEP models in predicting MWD of wet aggregates were evaluated by the coefficient of determination (R2), root mean square error (RMSE), mean error (ME) and Nash-Sutcliffe coefficient (NS) statistics. Results and Discussion The values of sand (13.14 to 64.79 %), silt (21.11 to 74.96 %), clay (3 to 42.18 %), OC (1.01 to 7.17 %), PD (2.00 to 2.67 g cm-3), n (0.39 to 0.87 cm3 cm-3), GMD of dry aggregates (0.8 to 1.33 mm) and MWD of wet aggregates (0.35 to 2.65 mm) showed good variations in the soils of the studied region. The studied soils had clay loam (n= 11), sandy clay loam (n= 6), sandy loam (n= 12), loam (n= 13), silty clay loam (n= 14), silty clay (n= 1) and silt loam (n= 23) textural classes. There were found significant correlations between MWD with OC (r= 0.67**), sand (r= 0.70**), GMD (r= 0.30**) and PD (r= -0.46**). Also, significant and positive correlation was found between OC and sand (r= 0.59**). Due to the multicollinearity of sand with dg (r= 0.87**), we did not use the dg as an input variable to estimate MWD of wet aggregates. Generally, four MLR, ANN and GEP models were constructed to predict MWD of wet aggregates from measured readily available soil variables. The results of MLR, ANN and GEP models indicated that the most suitable variables to estimate MWD of wet aggregates were sand, OC and GMD of dry aggregates. The values of R2, RMSE, ME and NS criteria were obtained equal 0.52, 0.48 mm, 0.13 mm and 0.48, and 0.85, 0.30 mm, 0.03 mm and 0.78, 0.79, 0.35 mm, -0.10 mm, 0.95 for the best MLR, ANN and GEP models in the testing data set, respectively. Many researchers also reported that there is a positive and significant correlation between MWD of wet aggregates and OC. Conclusion The results showed that sand, OC and GMD of dry aggregates were the most important and readily available soil variables to predict the mean weight diameter (MWD) of wet aggregates in the Fandoghloo region of Ardabil province. According to the lowest values of RMSE and the highest values of R2 and NS, the precision of ANN models to predict MWD of wet aggregates was more than MLR and GEP models in this study. Because ANN is more flexible and effectively captures non-linear relationships, it performed better than the other models in predicting MWD.

Introduction The 21st century is witnessing the increase of climate change as an important challenge due to its destructive environmental and socio-economic effects. Extreme climatic conditions have become frequent and more intense in recent decades as a result of human activities. Iran, as one of the countries in the Middle East with a different climate in each region of the country, has suffered significant adverse effects of climate change. Considering the importance of the climate change, it is important to investigate the changes in climate variables to know the future conditions and make management decisions. In the field of climate research, global climate models are useful tools that are often used to investigate the global climate system, including historical and projected periods. Since the use of the CMIP6 dataset provides improved clarity and accuracy for predicting future climate forecasts, the main objective of the present study is to predict the temperature and precipitation changes in the near, mid, and far future in Sistan-va-Baluchestan province. Materials and Methods The minimum temperature, maximum temperature, and precipitation data of 10 general circulation models (GCMs) of the 6th IPCC report for the baseline (1990-2014) were downloaded from the Global Climate Research Program database (https://esgf-node.llnl.gov). Then GCMs were including ACCESS-CM2, CMCC-ESM2, CNRM-CM6-1-HR, CNRM-ESM2-1, EC-Earth3-CC, EC-Earth3-Veg-LR, INM-CM4-8, INM-CM5-0, MIROC6, and NorESM2-MM. Four statistical indicators including correlation coefficient (R2), RMSE, Nash-Sutcliffe efficiency (NSE), and mean absolute error (MAE) were used to evaluate the performance of 10 GCMs. Based on the results obtained from the these indicators, the models that had higher performance in predicting the temperature and precipitation data were selected as the best models for forecasting in the future. The ensemble of these models under two SSP2-4.5 and SSP5-8.5 scenarios for the near, middle, and far future (2026-2050, 2051-2075, and 2076-2100) were extracted from the World Climate Research Program database. CMhyd (Climate Model data for hydrologic modeling) tool was used to bias correction climate data of the selected models. In order to choose the best bias correction method, the R2, RMSE, NSE, and MAE were estimated. After bias correction, the climate data of selected models were ensembled and then the changes in precipitation and maximum and minimum temperature in three future periods compared to the baseline was estimated. Results and Discussion The results showed that out of 10 GCMs, seven models had good performance (R2 > 0.40, 4.23 < RMSE < 12.02°C, 0.12 < NSE < 0.74, and 3.36 < MAE < 9.59°C) in simulating daily minimum and maximum temperature. However, the performance of all models in simulated daily precipitation was poor (R2 > 0.19, 1.24 < RMSE < 3.70 mm, -7.41 < NSE < -0.57, and 0.23 < MAE < 0.85 mm). Among the different bias correction methods of temperature and precipitation available in CMhyd, the distribution mapping method had the best performance. In all three regions, compared to the baseline, the average annual minimum and maximum temperature under two scenarios will increase in the future periods and precipitation will decrease in most periods and scenarios. These changes will be mainly in the SSP5-8.5 scenario compared to SSP2-4.5 and also in the far future period compared to the middle and near future. Averaged across all locations, annual maximum temperature showed increases in near, middle, and far projected periods of 1.3, 2.1, and 2.8°C under SSP2-4.5 and 1.6, 3.1, and 5.1°C under SSP5-8.5, respectively (Fig. 2), while for minimum temperature, the increases will be of 1.6, 2.6, and 3.4°C for SSP2-4.5 and 1.9, 3.9, and 6.3°C for SSP5-8.5. The range of annual precipitation among all sites was from –58.22 to 49.33% under SSP5-8.5 in the near and far future periods in Zabol and Iranshahr, respectively. The annual increase in the average maximum and minimum temperature will be mainly due to the increase in air temperature in the months of January, February, August, September, October, November and December. The annual decrease in precipitation will mainly result from the decrease in precipitation in January, February, March, November, and December, and the annual increase in precipitation will result from the significant increase in precipitation in May and October compared to the baseline. Conclusion The results showed that under different scenarios of climate change, the maximum and minimum temperatures in the near, middle, and far future periods will face an increase compared to the baseline. However, the precipitation changes in the future time periods are not the same as compared to the baseline, and in some periods the precipitation will decrease and in others it will increase. But in general, the decrease in precipitation will be more than its increase. Therefore, it is very important to formulate and implement appropriate management programs for the needs of each region, in order to properly manage water resources and adapt to extreme temperatures and their consequences.

Introduction Tillage is an important component of soil management that affects the production of crops. Maintaining and improving the quality of the soil is a basic requirement to ensure the sustainability of the ecosystem. This experiment was conducted in order to investigate the effect of different tillage methods and the use of plant residues on the yield, protein and nitrogen percentage of triticale plant and physical and chemical indicators of the soil. Materials and MethodsThe experiment was carried out as split plots based on a randomized complete block design with three replications at Shahid Chamran University of Ahvaz during 2023-2024. The main factor including different methods of tillage at three levels (conventional tillage, reduced tillage and no tillage) and the sub factor also including 5 levels of plant residue application (without residues (control), wheat residues, mung bean, sesame and half of wheat residues + half of residues Mung bean) were considered. The amount of residues used for each plot was approximately 30% of the biological yield of the product, which was considered to be 3, 1.5 and 1 ton.ha-1 for wheat, sesame and mung bean, respectively. At the end of the experiment yield and yield components, seed nitrogen and protein of triticale plant and physical characteristics (bulk density, percentage of porosity) and chemical (pH, EC, organic carbon content, nitrogen) soil properties were measured. All statistical calculations were made using SAS 9.3 statistical software and for the LSD test was used to compare the means at a probability level of 5%. Results and DiscussionThe interaction of tillage treatments and the use of plant residues showed that the highest grain yield was equal to 8.6 ton.ha-1 from the treatment of reduced tillage and the use of Mung bean residues, and the lowest value obtained was related to the effect of the treatment conventional tillage and no residues (control) with 3.5 ton.ha-1. The grain yield in the reduced tillage method was 12.5% and 7.6% higher than the conventional tillage and no tillage methods. The reduced tillage method resulted in a 32.2% increase in seed protein and a 32% increase in seed nitrogen compared to conventional tillage. The results also indicated a significant interaction effect between tillage treatments and residue application on grain yield (p < 0.01). Additionally, the interaction between tillage and residue application had a significant effect on soil bulk density (p < 0.01). The lowest bulk density (1.3 g.cm-3) was observed in the conventional tillage treatment combined with wheat and mung bean residues, with this combination falling within the same statistical group. The highest bulk density (1.75 g.cm-3) was obtained from the no-tillage treatment and the use of NO residues (Control). Based on the obtained results, the interaction effect of tillage treatments and the use of residues on soil organic matter, soil organic carbon and nitrogen soil (p<0.05). The interaction between the effects of tillage and the use of residues showed that the highest soil organic matter (1.53%) was from the treatment of reduced and the use of wheat residues. ConclusionThe results showed that tillage methods and the use of plant residues, in addition to affecting the percentage of nitrogen and protein of triticale seeds, also affected the physical and chemical indicators of the soil. The changes related to the physical and chemical indicators of the soil in the method No tillage are more than the two methods of reduced tillage and conventional tillage, and the improvement of these characteristics has been limited even at this time. Overall, from the point of view of soil protection, the results of this experiment clearly show the superiority of conservation tillage methods compared to conventional tillage methods. Sustainable agriculture aims to achieve optimal yields while preserving environmental structure and minimizing the adverse impacts of agricultural activities. One of the key challenges in sustainable agriculture is the lack of organic matter and its associated consequences. Implementing conservation tillage and managing plant residues-critical elements of agricultural production-can help address this issue. By improving soil quality, these practices contribute to increased productivity in farming. Acknowledgement We would like to thank the Research and Technology Vice-Chancellor of Shahid Chamran University of Ahvaz for funding this research, which is part of the research contract SCU.AA1400.309.

IntroductionAgriculture plays a dual role in the energy sector meaning that it acts both as a source of raw material for bioenergy production and as a major consumer of energy, particularly in the processes of planting, cultivation and harvesting, transportation, processing, and storage of agricultural products. Among the numerous challenges facing the agricultural sector, optimizing energy or input consumption is of paramount importance. These key inputs play a crucial role in ensuring food security and economic stability for the country. One of the most important agricultural development programs in the country should be to increase efficiency of energy consumption in the agricultural sector. In Iran, approximately 9.2 million hectares have been equipped with modern irrigation systems (pressure system) which has increased the water productivity index from 0.87 kg m-3 in 2014 to 0.32 kg m-3 in 2014. Accordingly, it is predicted to reach 0.60 kg m-3 hectares until 2025. The Dehgolan Plain, located in the east of Sanandaj city, has an area of 84,982 square kilometers. Groundwater is the only source of water for agriculture in the region. Due to the annual decrease in the groundwater level, energy consumption for water extraction has increased. Common irrigation systems in the region's farms include fixed-mobile sprinkler classic rain irrigation systems, center pivot, and lateral roll. Thus, it seems necessary to evaluate the energy productivity and efficiency indexes in the mentioned plain. The main objective of this study is to evaluate the energy consumption indexes of wheat in farms under fixed-mobile sprinkler classic and Willet rain irrigation systems. Materials and MethodsThis study was conducted in the farms of Dehgolan plains where the energy consumption trend of input factors in two irrigation systems was investigated. All information related to input factors and working hours of machinery, agricultural equipment, and manpower was recorded at the end of the cropping season 1400-1401 through filling out questionnaires. The studied farms in this research were all under dry wheat cultivation and equipped with two rain irrigation systems, system 1 (fixed-mobile sprinkler classic) and system 2 (Wheel move irrigation). The required input factors for wheat production in each hectare were determined. The amount of different input factors for conversion to energy standard was calculated using energy coefficients and equivalents. As a result, energy productivity, energy use efficiency, specific energy, and net energy indexes were used to investigate the energy consumption trend of wheat in the two mentioned irrigation systems. Results and DiscussionThe results of this study showed that the total input energy for wheat production in systems (1) and (2) was 85943.97 and 69189.04 MJ ha-1, respectively and energy consumption in the Willet rain irrigation system was higher than in the fixed-mobile sprinkler classic rain irrigation system due to the high consumption of electricity and irrigation water. The electricity consumption in both systems accounted for the highest energy consumption. Moreover, the energy productivity and efficiency of the two systems were almost equal as well as the net energy of irrigation system (1) and irrigation system (2) was 41510.96 and 64156.03 MJ ha-1, respectively. ConclusionIn conclusion, this study focuses on evaluating the energy trends in rain irrigation systems used in dry wheat farms in the Dehgolan plains, Kurdistan province, Iran. In this study, the energy indexes of wheat in smallholder farmers' farms in Dehgolan plain, Kurdistan province, were evaluated. The studied farms were categorized into two groups, system (1) (fixed-mobile sprinkler classic rain irrigation system) and irrigation system (2) (Willet rain irrigation system), the energy source of which was electricity for both systems. At the end of the cropping season, the total amount of input and output factors were collected by filling out questionnaires in person, and to validate the amount of electricity consumption, its amount was obtained from the Dehgolan Electricity Company. The results of the research showed that the energy consumption per unit of wheat production in the Willet irrigation system was higher than in the fixed-mobile sprinkler classic irrigation system. This difference was due to the higher consumption of electricity and irrigation water in the Willet irrigation system. The energy productivity and efficiency indexes were almost equal in both systems. Eventually, the net energy of the fixed-mobile sprinkler classic irrigation system was higher than that of the Willet irrigation system.

Introduction Selenium (Se) is one of the beneficial elements for plants, which is usually not supplied in the nutrient solutions used in soilless cultures. It is an essential element for both humans and animals. Application of Se at low concentrations has a positive effect on the growth and quality indices of plants. Nitrate accumulation in leafy vegetables poses threaten to human health. Leafy vegetables such as lettuce (Lactuca sativa L.) contain high levels of nitrate. According to the results of some researches, application of Se in the nutrient solutions can decrease nitrate accumulation in vegetables. However, the optimum concentration of Se in the nutrient solution for lettuce production in hydroponic culture is still not clear. This experiment was conducted to elucidate the effect of different levels of Se in the nutrient solution on the growth indices, yield, and nitrate accumulation of red French lettuce (cv. Lolla Rossa) in soilless culture. Materials and Methods A perlite culture experiment, using completely randomized design, was carried out with seven levels of Se in the nutrient solution (0, 0.1, 0.5, 1, 5, 10 and 20 µmol L-1) with four replications in the research greenhouse of Shahrekord University. Lettuce seedlings were grown in 1.7 L plastic pots (one plant per pot) containing perlite with size of 0.5-5 mm and were manually fertigated with the nutrient solutions on a daily basis. Different concentrations of Se were applied as sodium selenate (Na2SeO4.2H2O) in the nutrient solution (Domingues et al., pH= 5.4±0.1, EC=1.36-1.41dS m–1). After four weeks, lettuce plants were harvested and the fresh weights of shoots and roots were measured. Plant growth indices consisting of leaf number, leaf length, leaf width, plant height, plant diameter, leaf chlorophyll index, and leaf total soluble solids were determined. In one bush in each treatment, the leaves were separated as 1st to 10th outer leaves and other inner leaves. The leaves were dried in an oven at 70 °C and were ground. Nitrate concentrations in outer and inner leaves were measured calorimetrically using a spectrophotometer at a wavelength of 410 nm. Shoots Se concentration was determined with ICP-MS after wet digestion of samples with HNO3 and H2O2. Analysis of variance was done using SAS software and means comparison was conducted using the least significant difference test at 0.05 probability level. Results and Discussion The results indicated that application of Se in the nutrient solution had not significant effect on the lettuce growth indices including of leaf length, leaf width and leaf number. Application of 10 µmol L-1 of Se in the nutrient solution led to significant decrease of plant height in comparison with control, but plant diameter increased with application of Se in the nutrient solution. The highest plant diameter was observed in 10 μmol L–1 of Se treatment. The highest and the lowest shoot fresh weight were obtained under 0 and 1 μmol L–1 of Se in the nutrient solution, respectively. Application of 1 μmol L–1 Se increased shoots fresh weight by 22% comparing to the control. Shoot Se concentration was increased with application of Se in the nutrient solution. The highest concentration of Se in shoots (15 mg kg-1 dry matter) was observed at the rate of 20 μmol L–1 of Se in the nutrient solution. The amount of Se accumulated in the plant tissue is important in biofortification programs. The results showed that application of Se in the nutrient solution (with the exception of 1 µmol L-1 of Se) led to significant decrease in the nitrate concentration of roots, outer leaves, inner leaves and all leaves of lettuce. The lowest nitrate concentration in all leaves of lettuce (2095 mg kg-1 fresh weight) was obtained in plants nourished with 0.5 μmol L–1 of Se in the nutrient solution. Compared with control (0 μmol L–1 of Se), nitrate concentration in all leaves for 0.5 μmol L–1 of Se treatment was decreased 28%. Selenium has a positive function on decreasing nitrate accumulation in plants via regulating the transport of nitrate and enhancing activities of nitrogen metabolism enzymes. Conclusion According to our results, application of Se decreased nitrate concentration in lettuce plants. Therefore, application of Se in the nutrient solution at the rate of 0.5 μmol L–1 is suggested for red French lettuce production in hydroponic culture under the conditions of the present study.

IntroductionSugarcane (Saccharum officinarum L.) is a perennial plant belonging to the cereal family. Sugarcane is a major agricultural crop cultivated extensively in tropical and subtropical regions worldwide. Its phenological growth cycles lead to changes in the plant's nutritional requirements. Understanding these changes requires comprehensive knowledge of the plant's growth stages, as well as the decomposition processes of soil and plant leaves throughout these stages. The availability of nutrients required by the plant during the growth stages of the plant is one of the key points of normal plant growth, therefore, plant nutrition management plays a significant role in achieving optimal performance. Considering these changes, the leaf analysis and diagnosis method can prevent the limitations caused by plant nutritional disorders and the optimal use of fertilizers required in sugarcane cultivation. The combined nutrient detection (CND) method is one of the appropriate methods in interpreting the results of plant nutrient analysis, nutrient requirements and nutritional balance status in plants. Performing leaf sample analysis is an effective approach to monitor and assess the nutritional status of sugarcane. Given that sugarcane may have a multi-year cycle, this method provides a reliable indicator for assessing the nutritional needs of the crop during its cultivation period. One of the effective methods for assessing nutritional limitations in sugarcane is through the CND method. This method provides the advantage of quickly delivering up-to-date standards while identifying specific nutrients responsible for nutritional imbalances that may reduce productivity. Additionally, it enables the detection of limitations caused by deficiencies and excesses, indicated by negative and positive indices, respectively. The aim of this study was to determine the order of limitation for nitrogen, phosphorus, potassium, calcium, magnesium, copper, iron, manganese, and zinc using the CND in the commercial sugarcane variety CP69-1062 grown in ratoon farms. In the northern Khuzestan farms, which have the potential for higher sugarcane production, nutritional limitations may still restrict productivity. Materials and MethodsThe present study was conducted in ratoon sugarcane fields in the Shuaibih area of Imam Khomeini sugarcane cultivation and industry. The objective of this study was to examine the impact of fertilization management and assess nutrient balance in the commercial sugarcane variety CP69-1062 grown in ratoon farms. To achieve this, 25 farms were selected during the 2023-2024 crop year. The concentrations of nitrogen, phosphorus, potassium, calcium, magnesium, iron, manganese, zinc, and copper were analyzed in the leaves of the sugarcane plants. After the harvest season, the yield of each field was measured and recorded. The intermediate yield, obtained using the Khayari method, allowed the farms to be divided into two groups based on whether the yield was favorable or unfavorable. Subsequently, CND reference numbers, CND nutrient index and nutrient balance index (r²) were calculated. This index was calculated using the Keith-Nielson method, based on the Chi-square statistical distribution function (K²) in Excel software. Results and DiscussionThe results of the cumulative distribution function of the variance of nutrients, with an intermediate yield of 99 tons per hectare, indicate that 52% of the studied ratoon sugarcane farms were in the high yield group and 48% were in the low yield group. After solving the equations of the cumulative function of the third order of the studied nutrients, the nutrient balance index values were found to fall within the range of (2.62 to 20.58) in the optimal performance group, with an average value of 109.28 tons per hectare. The highest value of this index (r2 = 199.95) was observed in the Raton sugarcane field, with a yield of 73.08 tons per hectare. The CND reference numbers of the evaluated nutrients and remaining compounds were as follows: V*N= 2.87, V*P= 1.04, V*K= 2.64, V*Ca =1.95, V*Mg =1.29, V*Fe = -1.75, V*Mn = -3.35, V*Zn = -4.72, V*Cu = -3. 92, and V*Rd = 4.13. The index of CND nutrients showed that copper and iron had the highest negative index among micronutrients in the group of low-yielding ratoon sugarcane fields. The presence of calcareous conditions in the soil of the studied fields can be one of the reasons for this observation. ConclusionThe CND nutrient balance index (r2) was positive, especially in low-yielding ratoon sugarcane fields, and much higher than its value in high-yielding fields, which indicates nutritional imbalance in these fields. Proper management and balanced use of fertilizers should be considered. It can improve yield and growth cycle of sugarcane.

IntroductionReservoirs are crucial for water supply to human societies, making their proper and planned management essential. Dams serve multiple purposes, including urban water supply, agricultural irrigation, flood control, and hydroelectric power generation. In order to properly manage and monitor the consumption of these important reserves, it is inevitable to know their capacities. Using water stage and the reservoir's initial volume-area-elevation curve, which is prepared with the hydrographic operations, is a common method for estimating the storage capacity of reservoirs at different water levels. Over time, the occurrence of numerous sedimentations, often due to factors such as floods, can alter the initial volume-area-elevation curve of a reservoir, requiring it to be updated. Hydrographic operations, using tools like eco-sounders, are conventional methods for updating this curve; however, these methods are both expensive and time-consuming. In recent years, various studies have focused on remote sensing techniques aimed at estimating the volume of water stored in reservoirs, using water levels to establish the surface area-elevation curve. The basis of these studies is the separation of water-land masks using spectral indices, the calculation of water levels, and the development of reservoir surface area-elevation curves through linear or polynomial relationships. However, the main limitation of these methods is the inaccuracy of linear or polynomial relationships in fitting the surface area-elevation curves at the beginning and end points of the water stage change interval, which correspond to the empty or full states of the reservoir. This inaccuracy arises due to factors such as drought or flood events. In this research, the limitation of linear and polynomial relationships in accurately predicting the points of the reservoir surface area-elevation curves, where observational data are unavailable due to non-occurrence, was addressed by using the Modified Strahler method to draw the hypsometric curve. This method allows for the calculation of the storage capacity of the reservoir between successive water levels and the determination of the final volume of water stored in the reservoir. By comparing the volumes of water stored at the present and initial reservoir capacities, the sedimentation rate and the useful life of the Negarestan Dam reservoir were estimated. Material and MethodsNegarestan Dam (Kabudval) is located on the Qarasu (Zarin Gol) river, 45 km east of Gorgan in the Golestan Province. This dam is used for purposes such as supplying urban water to Aliabad city and supplying water needed for the agricultural irrigation network of Qarasu. In this study, landsat8 satellite images were used to estimate the useful life of the Negarestan reservoir. The required images of the ROI were downloaded through the USGS database and pre-processed in Envi5.3 software. Using visible and infrared spectral bands, water indices NDWIMCFeeters, NDWIGao, MNDWI, AWEISh and TCWet were calculated to separate land-water masks. After evaluating the accuracy of the obtained water level results by comparing it with the initial volume-area-elevation curve of Negarestan reservoir, the MNDWI index was used as the most accurate index to calculate water levels. In this study, the modified Strahler method was used to obtain the hypsometric curve of the surface area-elevation of the reservoir, which has high accuracy in extrapolating the beginning and end points of the curve. By using the hypsometric curve, water levels were extracted for arbitrary water levels, and with the help of the prismoidal method, the volume between consecutive water levels was calculated. The sum of these volumes equaled the current storage capacity of the reservoir. To estimate the sedimentation rate of the Negarestan Dam reservoir, the current storage capacity was compared with the initial storage capacity in 2015. Based on this comparison, the useful life of the reservoir was accurately predicted. Results and DiscussionValidation results for calculating water surface areas using NDWIMCFeeters, NDWIGao, MNDWI, AWEISh and TCWet water indices showed that the MNDWI index with an average water surface areas calculation error equal to 5% is more accurate than other indices. Therefore, the MNDWI index was used in this study. Additionally, the comparison of the volume of water stored in the Negarestan reservoir with its initial storage capacity at the time of operation revealed that, over a period of 9 years, the storage capacity of the reservoir (at a water level of approximately 189.5 meters), which is close to the overflow crest level, had significantly decreased. It has decreased from about 24 to 20 million cubic meters, based on which the average annual sedimentation rate of the reservoir was estimated, to about 1.6%. The results showed that in a period of 9 years, the average level of the bathymetry of Negarestan reservoir has increased by 10 meters due to the accumulation of sediments, and the minimum level of the batymetry has reached from 160 to about 170 meters. According to the statistics of the International Commission on Large Reservoirs (ICOLD), the average annual sedimentation rate of the world's reservoirs is reported to be about 0.95%, and the results show that this amount in the Nagaristan Dam reservoir is almost 2 times the average rate. It is universal. According to the results obtained from this research and assuming constant climatic conditions, the useful life of the Nagarestan dam reservoir was estimated to be about 53 years from the beginning of 2024. ConclusionConsidering the increasing importance of water resources management, including dam reservoirs, this study employed a fast and cost-effective method based on remote sensing to calculate the volume of water stored in dam reservoirs and estimate their useful life. In addition to providing appropriate accuracy, this method was able to overcome the limitations of previous approaches in estimating the volume of accumulated sediment in the deeper parts of the reservoir. As a result, it offers a reliable tool for the effective management of water resources.

Introduction The large temporal and spatial changes of precipitation, especially in mountainous areas, have turned it into a controversial variable in climate models. Measuring precipitation (rain and snow) along with its distribution and changes is very important to improve our understanding of global water cycle and energy, water resources monitoring, hydrological modeling. Lack of reliable data is one of the most important challenges in rainfall analysis. Due to the significant temporal and spatial variability of precipitation in mountainous areas, accurate spatially distributed data is crucial for effective water resource assessment and management. However, many mountainous regions have limited rain gauge stations. Today, satellite products are commonly used to measure precipitation in these areas, but the variability among these products raises concerns about their accuracy in mountainous regions. Additionally, the quality of satellite products differs between various products and across different climatic regions, making it essential to thoroughly evaluate them before use. The purpose of this research was to evaluate the precipitation data of two satellite products (GPM, PERSIAN) and reanalysis data (ECMWF) in the estimation of precipitation in mountainous areas without stations in Lorestan province. Method This study utilized rainfall data from 24 synoptic and rain gauge stations across Lorestan province. Emphasis was placed on stations situated in or near mountainous regions. The selected stations were chosen based on their suitable spatial distribution and record length. The rainfall data spanned the period from 2015 to 2021 and included daily, monthly, and annual measurements. To evaluate satellite rainfall algorithms and estimate rainfall in regions with limited data, data from the GPM and PERSIAN satellites were employed, along with ECMWF reanalysis data. The PERSIAN rainfall algorithm is a remote sensing-based method that utilizes artificial neural networks. It calibrates infrared data with passive microwave estimates and converts longwave infrared images into rainfall estimates using a three-step process. The spatial resolution of this product is 0.25° x 0.25°, and it offers hourly, daily, and monthly temporal resolution. The PERSIAN rainfall algorithm data can be accessed from https://chrsdata.eng.uci.edu. The GPM mission aims to provide continuous observations of Earth's precipitation. It employs the GPM Microwave Imager (GMI) and Dual-frequency Precipitation Radar (DPR) to observe both snow and rain. The final product, called IMERG, is generated through multiple runs of the algorithm for each observation time. Initial estimates are quickly provided, and subsequent estimates improve as more information becomes available. The spatial resolution of the GPM product is 1° x 1°, and it offers hourly, daily, and monthly temporal resolution. IMERG data can be obtained from https://gpm.nasa.gov/data. CMWF reanalysis data is derived from the combination of short-term simulations of numerical weather prediction models with ground-based observational data. These simulations are controlled with observational data, and the resulting reanalysis database provides global coverage from 1979 with a spatial resolution ranging from 0.125° x 0.125° to 3°. The temporal resolution of ECMWF reanalysis data is hourly, daily, and monthly. More information about ECMWF data can be found at https://www.ecmwf.int/ (Azizi, 2019). To evaluate the accuracy of the products, R-squared correlation (R2), root mean square error (RMSE), standard deviation (MAD), correlation coefficient (R), error deviation (MBE) and Nash-Sutcliffe coefficient (NS) were used. Also, the probability of detection (POD), false alarm ratio (FAR), and critical success index (CSI) indices were used to validate the data. Results The results showed that none of the three products are suitable for estimating daily precipitation in mountainous areas. However, on a monthly scale, these products provide reasonable estimates. Among the three, the GPM satellite product demonstrated better accuracy on a monthly scale, based on error levels and the spatial distribution of estimated precipitation. On an annual scale, GPM also performed best, as indicated by both statistical errors and the spatial patterns of average annual precipitation. According to the MBE index, on daily and monthly scales, the ECMWF product tended to overestimate precipitation, while the PERSIANN and GPM products underestimated it. On an annual scale, GPM and ECMWF products overestimated precipitation, whereas PERSIANN underestimated it.

Introduction The most important effect of global warming is the increase in extreme weather events. According to AR5 reports, between 1951 and 2010, the number of warm days and nights increased and the number of cold days and nights has declined globally. In addition, the duration and frequency of hot periods, including thermal waves, have increased since the middle of the twentieth century. The trend analysis of temperature extreme indices is important in estimating the trend of global warming. Temperature Changes are affected by many complex factors. A significant part of these changes is due to the elements of the general circulation of the atmosphere and the sea surface temperature. Given that extreme weather events are one of the most devastating natural hazards and have harmful effects on different parts of society, therefore, many researchers have studied the changes in the past and future of extreme events and the mechanisms that trigger these changes. This research attempts to study the trend of changes in extreme temperature indices in North-West of Iran, and also their relation with general circulation of atmosphere. Materials and Methods At first, diurnal data of minimum and maximum temperature of 20 synoptic stations of the Northwest of Iran, which have long-term and reliable statistics, extracted for the period of 1986-2010 and quality control and data homogeneity of them were investigated. afterwards, 16 Extreme temperature indices introduced by ETCCDMI were applied. In general, these indices are categorized into five categories of absolute indices, based on percentiles, based on thresholds, periodic, and amplitudes that measure the frequency, severity and duration of the temperature. These indices are estimated by RClimDex software and the trend rate of the changes in indices was shown through maps. To measure the changes in the general circulation of atmosphere the annual mean circulation composites extracted for the periods of 1961-1985 and 1986 -2016 based on the reanalysis data of the NCEP / NCAR. Then the difference maps plotted using grads software. Results The regional trend of extreme indices and the percentage of stations with a positive and negative trend were identified and the spatial distribution of the gradient of each of the indices was mapped. The results show that all absolute temperature indices have an increasing trend. On average, the maximum temperature (TXx and TXn) has increased by about 0.04 degrees over the decade. The increase rate of TNx is about 0.03 degrees, while the TNn increased by about 0.1 degrees Celsius per decade during the study period. Therefore, in the north-west of Iran, temperature increase has mainly occurred at night. The values of cold days (TX10) and cold nights (TN10) decreased with a gradient of -0.46 and -0.42 days in the decade. The warm days (TX90) and warm nights (TN90) have an increasing trend in 95% of the stations in the area. Frost days (FD) and icing days (IDs) have a decreasing trend, whereas, summer days (SU25) and tropical nights (TR20) have an increasing trend. The number of frost days with a gradient of -0.95 and the number of icing days with a gradient of -0.63 days in decade are decreasing. While, the number of summer days with a gradient of 0.81 and the number of tropical nights with gradient of 0.31 days in decade are increasing. In the northwest of Iran, all stations have been experiencing the increasing trend in Warm Spell Duration Index (WSDI), but the Cold Spell Duration Index (CSDI) in 70% of the stations in the region has decreased. Growing season length, as an effective index especially in agriculture, is increasing by an average of 1.1 days per decade. Based on the results of research carried out globally and at Iran, the trend of Daily Temperature Range (DTR) is negative, while this index has a positive and increasing trend in 65% of North-West stations in Iran. Except TNx and TNn indices that have positive trend in most stations in the region, Comparison of warm and cold extreme indices indicates that warm indices have a positive and incremental trend, while cold indicators show a decreasing trend. The positive gradient of these indices also corresponds to the decreasing trend of cold day and night indices, which indicates an increase in temperature and a decrease in cold days and nights. The study of large-scale changes in atmospheric circulation shows that the study area has got warmer in the spring and summer and colder in autumn and winter. Conclusion In this study, the trend of temperature extreme indices in North-West of Iran and its relation with the large-scale general circulation of the atmosphere have been investigated. The results show that all absolute temperature indices (TXx, TXn, TNx and TNn) are incremental. The indices of cold days (TX10) and nights (TN10) decreased with a gradient of -0.46 and -0.42 days in the decade and the indices of warm days (TX90) and warm nights (TN90) are increasing in 95% of the stations in the area. Frost days and icing days (IDs) show declining trend and summer days (SU25) and tropical nights (TR20) have an increasing trend. In the north-west of Iran, all stations have experienced an increasing trend in warm spell duration index (WSDI), but the cold spell duration index (CSDI) has been decreasing in 70% of the stations in the area. Growing season length (GSL) is increasing by an average of 1.1 days in every decade. Daily temperature range (DTR) has a positive and increasing trend in 65% of stations in north-west Iran. Comparison of warm and cold extreme indices indicates that warming indices have a positive and incremental trend, while cold indices show a decreasing trend. Study of the general circulation of atmosphere of the region by drawing and analyzing difference maps indicates that the study area has been warmer in spring and summer and colder in autumn and winter.

IntroductionResearch and development in high-potential agricultural areas are of great importance for ensuring the food needs of the population and livestock. Neglecting these regions can lead to increased food prices and food shortages, which can have a negative impact on the economy and public health. Land suitability maps provide essential information for agricultural planning and are vital for reducing land degradation and evaluating sustainable land use. The utilization of modern mapping techniques such as digital soil mapping and machine learning algorithms can significantly improve the accuracy of land suitability assessment and crop performance prediction. These methods have been widely employed as primary tools for mapping and evaluating land suitability in various regions worldwide. Materials and MethodsIn this study, a total of 288 soil profiles were utilized to compute the land suitability index for wheat, barley, and alfalfa crops. Various environmental variables were included, such as topographic factors derived from the digital elevation model and spectral indices obtained from Landsat 8 satellite imagery. Eight key factors, namely slope percentage, climate, texture, gypsum content, equivalent calcium carbonate, electrical conductivity (EC), and sodium absorption ratio (SAR), were identified as influential in the assessment of land suitability. To quantify the degrees of land suitability for the target crops, a parametric approach based on the square root method was employed. Moreover, the random forest machine learning model was utilized for spatial modeling, zoning mapping, and determining the significance of environmental variables in the land suitability evaluation process. By incorporating these comprehensive methodologies, a more detailed and accurate understanding of the land suitability for wheat, barley, and alfalfa cultivation can be achieved, facilitating informed decision-making in agricultural planning and land management strategies. Results and DiscussionThe spatial prediction results demonstrated the effectiveness of the random forest model in classifying land suitability for wheat, barley, and alfalfa. The model achieved high accuracy, with Kappa coefficients of 81%, 84%, and 85% for wheat, barley, and alfalfa, respectively. The overall accuracies were also impressive, reaching 86% for wheat, 88% for barley, and 89% for alfalfa. Analyzing the land suitability assessment results, it was found that barley had the highest land suitability class, covering a significant portion of 40% in class S1. Alfalfa followed closely with 35.5% of the total area, and wheat occupied 32% in the same class. Delving into the predictive environmental variables for barley, Diffuse, SHt, and MrVBF emerged as the most influential factors. These variables played a crucial role in assessing the suitability of land for barley cultivation. Similarly, for wheat, the variables Diffuse, MrVBF, and TWI were identified as significant indicators, contributing to the accurate prediction of wheat performance. Regarding alfalfa, the variables MrVBF, Diffuse, and Valley_depth stood out as the most important variables, providing valuable insights into land suitability for alfalfa cultivation. In general, the limiting factors for irrigated cultivation of these crops were primarily associated with soil properties. In the northern regions, soil texture was identified as a significant limiting factor, impacting the suitability of the land for crop cultivation. On the other hand, in the southern regions, soil characteristics such as the percentage of lime, gypsum, salinity, and alkalinity were recognized as the most influential limiting factors, affecting the suitability of the land for successful crop production. These findings provide valuable information for land planners, farmers, and decision-makers in determining suitable areas for wheat, barley, and alfalfa cultivation. By considering the identified influential factors and addressing the limiting soil properties, agricultural practices can be optimized to maximize crop productivity and ensure sustainable land use. ConclusionThe research aimed to evaluate land suitability for wheat, barley, and alfalfa crops under irrigation. Data selection focused on the most limiting factors for these crops. The model achieved acceptable predictions for wheat, barley, and alfalfa, with Kappa coefficients of 0.81, 0.85, and 0.84, and overall accuracies of 0.86, 0.89, and 0.88, respectively. Barley had the highest percentage of suitable land (40%), followed by alfalfa (39.5%) and wheat (32%). Soil constraints varied across the study area, including texture, stoniness, lime, gypsum, salinity, and alkalinity. The analysis identified 31 soil types, and the random forest model yielded a digital soil map with a Kappa coefficient of 0.76 and overall accuracy of 0.81. The findings support effective land management and agricultural planning.

IntroductionOptimum yield production under rainfed cultivation directly depends on the amount of rainfall and moisture storage in the soil. The tillage system directly influences soil moisture retention as well as the soil’s physical and chemical properties. Selecting the appropriate tillage system can significantly impact crop yields. Oilseeds are particularly important among crops, representing the second-largest food reserve in the world after grains. These products are rich in fatty acids. Today, the oil extraction and production industry is one of the most strategic industries in most countries. Iran has vast arable land and favorable conditions for cultivating oilseeds. However, according to available statistics, over 80% of the country's oil needs are met through imports. Given the increasing demand for higher-quality oil products and the challenges posed by climate issues, such as recurring droughts, cultivating and developing crops with lower water requirements and greater resilience appears to be a promising solution. Implementing effective management practices and appropriate fertilizers aligned with conservation agriculture could help increase crop yields while maintaining and improving long-term soil quality. To explore the potential of oilseed cultivation, an experiment was conducted to examine the effects of tillage and fertilization on the yield and yield components of safflower under rainfed conditions. Materials and MethodsThis experiment was carried out as split plots based on random complete blocks design, with three replications under rainfed conditions. The treatments included tillage systems (conventional tillage, reduced tillage, and no-tillage) as the main factor and NPK fertilizer (a mixture of urea, triple superphosphate, and potassium sulfate) at four levels of zero, 33, 66, and 100% as a secondary factor. Potassium and phosphorus fertilization and 50% of nitrogen fertilizer were used at the same time as planting, and the remaining 50% of nitrogen fertilizer was used four months after planting. Each block had three main plots; the distance between each block was 3 meters, and between the main plots was 2 meters. In each main plot, four sub-plots were created, and the distance between the sub-plots was 1 meter. The area of the main plots was 21 × 15 meters, and the area of each sub-plot was 4.5 ×15 meters. The amount of seed used for safflower was 25 kg per hectare. The safflower seeds were sown in 5 rows and planted at a distance of 50 cm and a distance between plants of 10 cm. At all stages of planting, maintenance, and harvesting, agricultural management followed the traditional practices of the study area, as performed by the local farmers. The final sampling, or harvesting, was carried out manually at the physiological maturity stage. Before conducting variance analysis, a normality test was performed on the data. In this research, the LSD test was used to compare the mean at the 5% probability level, Excel software was used to draw graphs, and SAS 9.4 software was used to analyze the data. Results and DiscussionThe research showed that the traits examined, including leaf area index, dry matter content, thousand seed weight, seed yield, and biological yield, were affected by the tillage system, fertilizer, and their interaction effect. The highest safflower seed yield of 195.6 g/m2 was obtained from the fertilizer ratio of 33% and conventional tillage, and the lowest seed yield of 116.2 g/m2 was obtained from no-tillage and no fertilizer use. The results indicated that the conventional tillage system outperformed both reduced tillage and no-tillage systems. In reduced and no-tillage systems, the changes in the leaf area index of the safflower plant were similar, with the 100% fertilizer application under reduced tillage having a more pronounced effect compared to no-tillage. Additionally, in the absence of fertilizer in the no-tillage system, the leaf area index was lower. Fertilizer application increased the plant's biological yield, but its impact was greater under conventional tillage compared to reduced and no-tillage systems. Applying 33% of the required fertilizer in the conventional tillage system resulted in the highest biological yield for safflower, leading to a 94% increase in biological performance compared to the control. ConclusionIn most of the examined traits, the application of 33 and 66% of the fertilizer requirement caused the best results, and the 100% fertilizer ratio left adverse effects, which indicates the lower fertilizer requirement of this cultivar in the studied conditions compared to cultivars in other regions. Since the research was conducted in rainy years, conventional tillage was better than low tillage. It is suggested that this plant's production amount be evaluated under different irrigation conditions and moisture limitations so that tillage systems and management methods can be examined and selected more carefully.

Introduction The rapid growth and development of urban communities, coupled with the increased industrial and economic activities in recent years, have led to the production and release of various pollutants into the environment. These pollutants have adverse effects on human health, living organisms, and the overall environment. With limitations in water resources, insufficient rainfall, the looming risk of water crises in many countries, and the escalating pollution of surface and underground water, there is a pressing need for environmental solutions to mitigate these issues. It is important to acknowledge that wastewater often contains pollutants that may render it unsuitable for certain applications. The utilization of biochar derived from cost-effective materials and innovative technologies such as ultrasonics is one avenue that warrants exploration for enhancing water quality. In this approach, a nitrate solution is exposed to both an adsorbent and ultrasonic waves. This dual treatment induces changes in the physical and chemical properties of water, thereby offering potential improvements in water quality. Materials and Methods This study aimed to explore the impact of utilizing biochar derived from rice straw, which was coated with iron(III) and zinc cations, and subjected to ultrasonication, on the nitrate adsorption process from aqueous solutions. In order to produce biochar, cheap materials of rice straw were used. The chopped straw was placed in the electric furnace and heated for one hour to reach the desired temperature. Then it was kept at that temperature for 2 hours. After that, the obtained biochar was washed three times with distilled water at a ratio of 1:20 and dried in an oven at 70°C for 24 hours. In this study, two temperature levels, 350 °C and 650 °C, were used for biochar production. Based on the results from pre-tests, it was found that biochars produced at 650 °C exhibited higher nitrate removal efficiency. These biochars were then used for the continuation of the experiments. To optimize the adsorbent dose, pre-tests were conducted using doses of 0.1, 0.3, 0.5, 0.8, and 1 gram of the adsorbent with 40 ml of nitrate solution. The concentrations of nitrate solution tested were 20, 45, 80, 100, 150, and 200 mg L-1. The research involved conducting experiments to determine the optimal parameters for each treatment, with three repetitions conducted in the water quality laboratory of Sari agricultural sciences and Natural Resources University during the years 2021 and 2022. The treatments comprised biochar (B), biochar and ultrasonic (BU), biochar with iron(III) coating (BF), biochar with iron(III) coating and ultrasonic (BFU), biochar with zinc coating (BZ), and biochar with zinc coating and ultrasonic (BZU). In this investigation, Langmuir and Freundlich adsorption isotherms were examined. Results and Discussion The results indicated that the BF and BFU treatments exhibited a higher maximum adsorption capacity. The Freundlich isotherm demonstrated higher correlation coefficients for BF, BFU, BZ, and B, suggesting a superior fit of the Freundlich model in these treatments. The better fit of the Freundlich adsorption isotherm indicates the heterogeneity of biochar surface adsorption sites, which means that the adsorption process is not confined to a single constituent layer. Nitrate adsorption on biochar surface is probably influenced by electrostatic adsorption and ion exchange. Conversely, the BZU and BU treatments showed a better fit with the Langmuir model. In the analysis of the Freundlich isotherm, nf values revealed that BF, BFU, and BZ treatments exhibited a favorable adsorption state with a desirable curve shape. The B treatment displayed a normal adsorption state with a linear curve shape, while BU and BZU treatments showed a weak adsorption state with an unfavorable curve shape. The elevated values of adsorption capacity (KF) obtained for BF, BFU, and BZ, namely 1909.414, 1484.22, and 386.63 ((mg g-1)(L mg-1)1/n), respectively, underscore the high nitrate adsorption capacity of these treatments. Also, biochars coated with iron(III) and with iron solution concentration of 10000 mg L-1 had a very good performance in removing nitrate from aqueous solutions. The new ultrasonic technology was able to improve the performance of the tested adsorbents in a period of 5 minutes without the need to stir the mixture of biochar and nitrate solution in the obtained equilibrium times, which were between 60 and 120 minutes. Application of this technology can be effective and useful in increasing the economic benefits of using limited water resources and increasing the efficiency of water consumption. Conclusion The utilization of cost-effective biochars derived from rice straw, along with the application of ultrasonic technology, can substantially decrease nitrate levels in aqueous solutions. In the case of biochar with iron(III) coating, biochar with iron(III) coating combined with ultrasonic treatment, and biochar combined with ultrasonic treatment, there is a notable affinity for nitrate to be adsorbed onto the surface of the adsorbent.

Introduction High-resolution satellite imagery data is widely utilized for Land Use/Land Cover (LULC) mapping. Analyzing the patterns of LULC and the data derived from changes in land use caters to the increasing societal demands, improving convenience, and fostering a deeper comprehension of the interaction between human activities and environmental factors. Although numerous studies have focused on remote sensing for LULC‎ mapping, there is a pressing need to improve the quality of LULC maps to achieve sustainable land management, especially in light of recent advancements made. This study was carried out in an area covering approximately 8000 hectares, characterized by diverse conditions in LULC, geomorphology and pedology. The objective was to investigate the potential for achieving maximum differentiation and accurate mapping of land features related to LULC. Additionally, the study assessed the impact of various spectral indices on enhancing the results from the classification of Landsat 8 imagery, while also evaluating the efficacy of support vector machine (SVM) and maximum likelihood algorithms in producing maps with satisfactory accuracy and precision. Materials and Methods As an initial step, LULC features were identified through fieldwork, and their geographic coordinates were recorded using GPS. These features included various types of LULC, soil surface characteristics, and landform types. Following the fieldwork, 12 types of LULC units were identified. Subsequently, the LULC pattern in the study area was classified using the RGB+NIR+SWIR1 bands of Landsat 8, employing both SVM and maximum likelihood classifiers. To assess the impact of various spectral indices on improving the accuracy of the LULC maps, a set of vegetation indices (NDVI, SAVI, LAI, EVI, and EVI2), bare soil indices (BSI, BSI3, MNDSI, NBLI, DBSI, and MBI), and integrated indices (TLIVI, ATLIVI, and LST), and digital elevation model of study area were successively incorporated into the classification algorithms. Finally, the outcomes from the two classification algorithms were compared, taking into account the influence of the applied indexes. The classification process continued with the selected classifier and indices until reaching the maximum overall accuracy and kappa coefficient. Results and Discussion Field observations revealed that the study area could be categorized into 12 primary LULC units, including irrigated farms, flow farming, dry farming, traditional gardens (with no evident order observed among planted trees), modern gardens (featuring regular rows where soil reflectance is visible between tree rows), grasslands, degraded grasslands, highland pastures (covered by Astragalus spp., dominantly), lowland pastures (covered by halophyte plants), salt domes (with no or very poor vegetation), outwash areas (River channel with many waterways), and resistant areas. The results of image classification indicated that the performance of the SVM algorithm across different band combinations is superior to that of the maximum likelihood method. Using SVM resulted in an increase in overall accuracy and Kappa coefficient by 3-8% and 0.03-0.08, respectively. For the map generated using RGB+NIR+SWIR1 bands and employing SVM, overall accuracy and Kappa coefficient were determined to be 76.6% and 0.72, respectively. Among the vegetation indices used in the SVM algorithm, LAI had the most significant impact, increasing the classification accuracy by 2.64%. Among the soil indices, BSI and MBI indices demonstrated the best performance; with BSI increasing the classification accuracy by 1.95% and MBI by 1.64%. Among the integrated indices, LST and ALTIVI enhanced the classification accuracy by 2.75% and 2.35%, respectively. It should be noted that the inclusion of the digital elevation model did not significantly improve the classification accuracy when using the support vector machine algorithm; in fact, it led to a decrease in accuracy when applied to the maximum likelihood classification. The probable reason for this issue is the different nature of DEM data compared to the other input data, as well as the limitations of parametric statistical approaches to effectively integrating data from diverse sources. Finally, the classification process was executed using the three visible bands, NIR, and SWIR1, in conjunction with selected indices (LAI, BSI, MBI, LST, and ALTIVI). Results indicated that using these spectral indices significantly improved classification accuracy, particularly for the DF, DGL, MG, O, and IF land cover/use classes. The calculated accuracies for these classes increased by 11.62%, 18.57%, 20.06%, 29.39%, and 33.19% respectively. Consequently, the accuracy of the classification and the Kappa coefficient (using support vector machine algorithm) increased to 85.24% and 0.82, respectively. Conclusion In this research, we aimed to accurately map various land use/land covers by utilizing Landsat 8 imagery and incorporating three group of spectral indexes. Despite spectral interferences and overlaps among various phenomena related to LULC, the utilization of different spectral indices resulted in significant differentiation among LULC classes. Finally, considering the limitations of modelling in ENVI software, it is recommended to investigate the effectiveness of other models for classification in more specialized software, such as R.

Introduction Recently, layered double hydroxides (LDHs) have attracted significant attention due to their various applications, particularly as slow-release fertilizers for essential plant nutrients. Several studies have reported the release of nitrate and phosphorus from LDHs. Additionally, micronutrients such as zinc (Zn), copper (Cu), and manganese (Mn) can be structurally incorporated into the metal hydroxide layers. Recent research indicates that LDHs have considerable potential for releasing these micronutrients. However, further studies are needed to enhance our understanding of the mechanisms and reactions of LDHs under different conditions. Currently, there is a lack of information regarding the divalent (M2+) to trivalent cation (M3+) ratios in LDHs and the influence of malic acid on the release of Zn, Mn, and magnesium (Mg) from these compounds. This study aimed to investigate the effects of malic acid and the ratio of M2+/M3+ on the kinetics release of Zn, Mn and Mg from Mg-Zn-Mn-Al-LDH intercalated with nitrate. Materials and MethodsAll chemicals used in this study including malic acid (C4H6O5), KCl, Zn(NO3)2.6H2O, Mn(NO3)2.4H2O, Mg(NO3)2.6H2O and Al(NO3).9H2O were of analytical grades, purchased from Chem-Lab or Merck Chemical Corporations. The solutions were made with the decarbonated ultrapure water (electrical resistivity = 18 MΩcm). The LDHs were synthesized by co-precipitation method at constant pH=9.2-9.6. Two types of LDHs were synthesized with varying the M+2(Zn+Mn+Mg)/M+3(Al) 3:1 and 4:1 in the precursor solution while being stirred vigorously in a nitrogen atmosphere. The pH was kept at 9.2-9.6 by adding volumes of 3 M NaOH. The crystals of LDH were ripened in the mixture for 2 h and after that, the precipitates were centrifuged at 3000 rpm for 20 min and washed several times with distilled water and placed in an oven at 70 °C for 8 h to dry. The chemical composition of the synthesized LDHs was determined by furnace atomic absorption spectrophotometry (SavantAA, GBC) after acid digestion. The physical, chemical, and morphological characteristics of the LDHs were determined using X-ray diffraction analysis (Panalytical x Pert ProX-ray diffractometer), Fe-SEM (Sigma VP), FT-IR (Nicolet iS10 spectrometer), and BET (BELSORP Mini II) techniques. A batch study was done to determine the effect of different ratios of M2+/M3+ in LDHs and the effect of malic acid on release of Zn, Mn, and Mg from LDH (3:1) and LDH (4:1). Briefly, 0.01 g of synthesized LDH were put in a centrifuge tube mixed with 10 ml background electrolyte (KCl 0.01 M) and 1.25 mM malic acid in initial pH=6-7 and constant temperature (25±0.5 °C). Blank samples (without ligand) were also considered. Suspensions were shaken at periods ranging from 5 to 720 min agitation (180 rpm). Then, the supernatant solution was separated using a centrifuge at a speed of 4000 rpm for 20 min. Zn, Mn, and Mg concentrations in supernatants solutions were determined by graphite furnace atomic absorption spectrophotometry. The effect of pH in the range of 5 to 10 on the release of Zn, Mn, and Mg from LDH was also studied. Two equations (pseudo-second-order and Elovich) were used to fit the kinetics data. Results and DiscussionThe results showed that the calculated molar ratio of divalent cation to trivalent cation was similar to their molar ratio in the solution prepared for the synthesis of LDH samples. The X-ray diffraction patterns of LDH (3:1) and LDH (4:1) samples showed the existence of strong and sharp peaks for 003 and 006 plates. Accordingly, the reflections of the 003 and 006 plates revealed the layered structure of the synthesized LDH materials. Two bands of FT-IR spectrums around 3480 and 1620 cm-1 for all synthesized LDH materials designated stretching vibrations of the O-H group of hydroxide layers and the interlayer water molecules. The sharp characteristic band around 1382 cm−1 in LDH (3:1) and band around 1354 cm-1 in LDH (4:1) was attributed to the antisymmetric stretching mode of nitrate anion in LDH. The specific surface area of LDH (3:1) and LDH (4:1) were 5.50 m2g-1 and 16.54 m2g-1 respectively. The average pore diameters in LDH (3:1) and LDH (4:1) were 1.92 nm and 2.55 nm, respectively. Time-dependent cumulative release of Zn, Mn, and Mg from LDH (3:1) and LDH (4:1) in the presence and absence of malic acid was investigated. Time-dependent Zn, Mn, and Mg release from LDH (3:1) and LDH (4:1) was accelerated in the presence of malic acid. The Zn, Mn, and Mg release from the LDHs was likely to be separated into two stages. In the initial stage from 0 to 60 min, the release rate of Zn, Mn, and Mg was rapid, then either remained constant or slightly enhanced during 60–720 min. In this research, among the non-linear models used to determine the release kinetics of Zn, Mn, and Mg, the result with the highest R2 values was chosen. The R2 values were 0.91–0.99, 0.93–0.99, 0.93–0.99, 0.89-0.99, and 0.55–0.86 for pseudo-first-order, pseudo-second-order, Elovich, power function, and parabolic diffusion, respectively. So, pseudo-second-order and Elovich models were used to analyze kinetic data. The amounts of release of Zn, Mn and Mg were higher from LDH (4:1) than from LDH (3:1) because of greater specific surface area, volume, and pore diameter in LDH (4:1). A comparison of metal release versus time profiles exhibited that dissolution was greatly dependent on the pH. ConclusionThe results of this research indicated that the release of Zn, Mn, and Mg from layered double hydroxides (LDHs) was influenced by factors such as time, ligand, solution pH, and the type of LDH. According to the kinetics models fitted to the experimental data, the release rate of Zn, Mn, and Mg from LDH (4:1) was higher than that from LDH (3:1). In both types of LDHs, the presence of malic acid significantly increased both the rate and amount of Zn, Mn, and Mg release compared to the absence of malic acid. While this study demonstrated that varying the ratios of divalent to trivalent cations can influence the amount and rate of Zn and Mn release, further greenhouse studies are required to confirm the effectiveness of LDH as a slow-release fertilizer in calcareous soils.

Introduction Soil contamination with heavy metals significantly threatens both environmental and human health. Anthropogenic activities, including chemical fertilizers and pesticides, industrial processes, wastewater disposal, and mining, contribute to the accumulation of heavy metals in soil. Plants can then taken up these contaminants and enter the food chain, causing various health problems. Soil amendments such as biochar and activated carbon offer a promising strategy for reducing the mobility and bioavailability of heavy metals in soil. This study investigated the effectiveness of biochar and activated carbon derived from organic waste materials (wheat straw, walnut shells, and almond shells) in immobilizing lead (Pb), zinc (Zn), and cadmium (Cd) and promoting corn (Zea mays. L.) growth in a greenhouse setting using contaminated soil. Materials and Methods Three types of organic waste wheat straw, walnut shells and almond shells were pyrolyzed at two temperatures (300 °C and 500 °C) under oxygen-free conditions for two hours to produce six types of biochar. The resulting biochars were then activated with phosphoric acid at their respective production temperatures, yielding six types of activated carbon. These organic waste materials, biochar, and activated carbons were added to soil contaminated with lead, zinc and cadmium at four application rates (0, 2.5, 5, and 10% by weight) in triplicate, 4.5 Kg Pot-1. The pots were incubated for one month under controlled temperature and humidity to achieve a relative equilibrium. Following incubation, the concentration of available heavy metals in the treated and control soils was measured. Corn was then planted in the pots, and at the end of the growth period, plant growth parameters (dry weight of shoots and roots) and heavy metal concentrations in plant tissues were determined. The data were analyzed using a completely randomized factorial design, and treatment means were compared to each other and the control. Results and Discussion Increasing pyrolysis temperature resulted in increased biochar pH, electrical conductivity (EC), and ash content, while the percentage of organic carbon, C/N ratio, and cation exchange capacity (CEC) decreased. Activation with phosphoric acid lowered the pH, ash content, EC, and organic carbon content of the biochars, while increasing their CEC. Amending the soil with biochar significantly increased soil pH and EC, whereas activated carbon amendments decreased these parameters. All amendments (organic waste, biochar, and activated carbon) significantly reduced the concentration of available heavy metals in the soil. Activated carbon had the greatest effect on immobilization, while organic waste had the least. The lowest concentrations of lead, cadmium, and zinc extractable with DTPA were observed with the 500°C activated carbon derived from wheat straw at a 10% application rate, with values of 1.6, 4.5, and 464 mg kg-1 soil, respectively, representing reductions of 99.46%, 83.67%, and 63.96% compared to the control treatment. This treatment also resulted in the lowest heavy metal concentrations in both the aerial parts and roots of the corn plants. Specifically, the lowest concentrations of lead, zinc, and cadmium in the aerial parts were 71.67, 490.67, and 1.67 mg kg-1 dry weight, respectively, while in the roots, they were 206, 1095, and 20 mg kg-1 dry weight, respectively. The highest dry weights of the aerial parts and roots were also observed with this treatment and a 5% application rate, with values of 5.76 and 1.84 grams per pot, respectively. The lowest concentration of heavy metals in corn tissues was observed in treatments with activated carbon produced at 500 °C and applied at a rate of 10%. Conclusion This study demonstrates that activated carbon derived from organic waste materials can be an effective and sustainable method for remediating soil contaminated with heavy metals and promoting plant growth. However, the presence of detectable heavy metals in corn tissues following activated carbon application suggests that this approach may be best suited for soils with low to moderate contamination levels.

IntroductionRecently, layered double hydroxides (LDHs) have attracted significant attention due to their variousapplications, particularly as slow release fertilizers for essential plant nutrients. Several studies have reported therelease of nitrate and phosphorus from LDHs. Additionally, micronutrients such as zinc (Zn), copper (Cu), andmanganese (Mn) can be structurally incor porated into the metal hydroxide layers. Recent research indicates thatLDHs have considerable potential for releasing these micronutrients. However, further studies are needed toenhance our understanding of the mechanisms and reactions of LDHs under diff erent conditions. Currently, thereis a lack of information regarding the divalent (M 2+2+) to trivalent cation (M 3+3+) ratios in LDHs and the influence ofmalic acid on the release of Zn, Mn, and magnesium (Mg) from these compounds. This study aimed toinvesti gate the effects of malic acid and the ratio of M 2+2+/M 3+ on the kinetics release of Zn, Mn and Mg from MgZn Mn Al LDH intercalated with nitrate nitrate.Materials and MethodsAll chemicals used in this study including malic acid (C4H6O5), KCl, Zn(NO3)2.6H2O, Mn(NO3)2.4H2O, Mg(NO3)2.6H2O and Al(NO3).9H2O were of analytical grades, purchased from Chem-Lab or Merck Chemical Corporations. The solutions were made with the decarbonated ultrapure water (electrical resistivity = 18 MΩcm). The LDHs were synthesized by co-precipitation method at constant pH=9.2-9.6. Two types of LDHs were synthesized with varying the M+2(Zn+Mn+Mg)/M+3(Al) 3:1 and 4:1 in the precursor solution while being stirred vigorously in a nitrogen atmosphere. The pH was kept at 9.2-9.6 by adding volumes of 3 M NaOH. The crystals of LDH were ripened in the mixture for 2 h and after that, the precipitates were centrifuged at 3000 rpm for 20 min and washed several times with distilled water and placed in an oven at 70 °C for 8 h to dry. The chemical composition of the synthesized LDHs was determined by furnace atomic absorption spectrophotometry (SavantAA, GBC) after acid digestion. The physical, chemical, and morphological characteristics of the LDHs were determined using X-ray diffraction analysis (Panalytical x Pert ProX-ray diffractometer), Fe-SEM (Sigma VP), FT-IR (Nicolet iS10 spectrometer), and BET (BELSORP Mini II) techniques. A batch study was done to determine the effect of different ratios of M2+/M3+ in LDHs and the effect of malic acid on release of Zn, Mn,and Mg from LDH (3:1) and LDH (4:1). Briefly, 0.01 g of synthesized LDH were put in a centrifuge tube mixed with 10 ml background electrolyte (KCl 0.01 M) and 1.25 mM malic acid in initial pH=6-7 and constant temperature (25±0.5 °C). Blank samples (without ligand) were also considered. Suspensions were shaken at periods ranging from 5 to 720 min agitation (180 rpm). Then, the supernatant solution was separated using a centrifuge at a speed of 4000 rpm for 20 min. Zn, Mn, and Mg concentrations in supernatants solutions were determined by graphite furnace atomic absorption spectrophotometry. The effect of pH in the range of 5 to 10 on the release of Zn, Mn, and Mg from LDH was also studied. Two equations (pseudo-second-order and Elovich) were used to fit the kinetics data.Results and DiscussionThe results showed that the calculated molar ratio of divalent cation to trivalent cation was similar to their molar ratio in the solution prepared for the synthesis of LDH samples. The X-ray diffraction patterns of LDH (3:1) and LDH (4:1) samples showed the existence of strong and sharp peaks for 003 and 006 plates. Accordingly, the reflections of the 003 and 006 plates revealed the layered structure of the synthesized LDH materials. Two bands of FT-IR spectrums around 3480 and 1620 cm-1 for all synthesized LDH materials designated stretching vibrations of the O-H group of hydroxide layers and the interlayer water molecules. The sharp characteristic band around 1382 cm−1 in LDH (3:1) and band around 1354 cm-1 in LDH (4:1) was attributed to the antisymmetric stretching mode of nitrate anion in LDH. The specific surface area of LDH (3:1) and LDH (4:1) were 5.50 m2g-1 and 16.54 m2g-1 respectively. The average pore diameters in LDH (3:1) and LDH (4:1) were 1.92 nm and 2.55 nm, respectively. Time-dependent cumulative release of Zn, Mn, and Mg from LDH (3:1) and LDH (4:1) in the presence and absence of malic acid was investigated. Time-dependent Zn, Mn, and Mg release from LDH (3:1) and LDH (4:1) was accelerated in the presence of malic acid. The Zn, Mn, and Mg release from the LDHs was likely to be separated into two stages. In the initial stage from 0 to 60 min, the release rate of Zn, Mn, and Mg was rapid, then either remained constant or slightly enhanced during 60–720 min. In this research, among the non-linear models used to determine the release kinetics of Zn, Mn, and Mg, the result with the highest R2 values was chosen. The R2 values were 0.91–0.99, 0.93–0.99, 0.93–0.99, 0.89-0.99, and 0.55–0.86 for pseudo-first-order, pseudo-second-order, Elovich, power function, and parabolic diffusion, respectively. So, pseudo-second-order and Elovich models were used to analyze kinetic data. The amounts of release of Zn, Mn and Mg were higher from LDH (4:1) than from LDH (3:1) because of greater specific surface area, volume, and pore diameter in LDH (4:1). A comparison of metal release versus time profiles exhibited that dissolution was greatly dependent on the pH.ConclusionTheresults of this research indicated that the release of Zn, Mn, and Mg from layered double hydroxides(LDHs) was influenced by factors such as time, ligand, solution pH, and the type of LDH. According to thekinetics models fitted to the experimental data, the release rate of Zn, Mn, and Mg from LDH (4:1) was higherthan that from LDH (3:1). In both types of LDH s , the presence of malic acid significantly increased both the rateand amount of Zn, Mn, and Mg release compared to the absence of malic acid. While this study demonstratedthat varying the ratios of divalent to trivalent cations can influence the amount and rate of Zn and Mn release,further greenhouse studies are required to confirm the effectiveness of LDH as a slow release fertilizer incalcareous soils.

Introduction The comprehension of the hydrogeological conditions of the aquifer and the determination of its hydraulic characteristics, such as hydraulic conductivity, transmissivity coefficient, and specific storage, are crucial for the management and preservation of groundwater resources. Various conventional methods, including empirical formulas, laboratory techniques (constant and falling head), tracer tests, field tests (Lugeon, Lefranc, slug, flowmeter, and pumping tests), and groundwater inverse modeling, are employed to establish these characteristics, particularly hydraulic conductivity. Empirical formulas are limited to ideal conditions, and in laboratory methods, the sample must be kept undisturbed. Due to the impracticality of measuring large-scale effective factors, the hydraulic conductivity determined through laboratory methods is also the only representative of the hydraulic conductivity at the sampling point. Tracer studies encounter numerous constraints, such as time, cost, porosity determination, and tracer dispersion in multilayered aquifers. It is also difficult to determine the average hydrodynamic properties of the heterogeneous aquifer based on the data obtained from a specific section of the Lefranc and Slug tests. Consequently, pumping tests are commonly selected for hydraulic parameter estimation. Although costly and time-intensive, these tests provide more precise coefficients. Geophysical methods have been greatly developed during the last two decades and have shown a significant correlation with the hydraulic parameters of the aquifer derived from borehole pumping tests or direct laboratory measurements. This approach minimizes uncertainties in numerical model calibration, improves data coverage, and reduces the time and cost of regional hydrogeological investigations. The conventional approach, known as the electrical resistivity method, is still widely used in global and local research projects for evaluating aquifer hydraulic characteristics (Ige et al., 2018; Arétouyap et al., 2019; Youssef, 2020; Ullah et al., 2020; de Almeida et al., 2021; Lekone et al., 2023). Therefore, this study aims to use the integrated approach of the geophysical method and pumping test as a cost-effective and efficient alternative for estimating the hydraulic parameters of the alluvial aquifer in the northeast of Gachsaran city. Material and Methods The research area is an alluvial aquifer located 5 km to the northeast of Gachsaran, between coordinates 50-52 to 51-09 E longitude and 30-15 to 30-28 N latitude. Using 86 vertical electrical soundings, Archie's equations, and the IPI2win software, the hydraulic characteristics of the aquifer under investigation were estimated. Subsequently, these characteristics were then compared to the coefficients derived from the data of two pumping test wells, which were calculated using the Aquifer test software and obtained via the Cooper-Jacob and Neuman methods. Results and discussion The hydrodynamic coefficients of the aquifer were initially determined using the Cooper-Jacob method in this study. The hydraulic conductivity values for wells one and two are 4.9 m/day and 5.7 m/day, respectively. Correspondingly, the storage coefficient values for wells one and two are 0.015 and 0.021, respectively. Based on the Cooper-Jacob approach, it is deduced that if the storage coefficient values exceed 0.001, the aquifer is classified as unconfined. In this study, the storage coefficient values for both pumping wells suggest that the aquifer is unconfined. Since the vertical flow component and the delayed yield phenomenon should also be taken into account in unconfiend aquifers, the Neuman analytical model has been used in the studied aquifer. The values of specific yield (Sy) for pumping wells one and two, which are related to delayed yield, are 0.05 and 0.04, respectively. These values were calculated by analyzing the first segment of the curve derived from the Neuman logarithmic drawdown-time plot. The storage coefficient values for pumping wells one and two, extracted from the second section of the curve, are 0.015 and 0.021, respectively. Furthermore, the transmissivity value for well number 1 was 323 m2/day, while for well number 2, it was 655.5 m2/day. The vertical electrical sounding (VES) data were subsequently initially analyzed and interpreted using the IPI2win software and the equalization curve method (partial curve matching technique). The coefficients denoted as m and n, indicative of the degree of cementation of the sediments, were determined based on the sedimentary composition prevalent in the area. Archie's equations were employed to calculate the formation factor and porosity parameters. The aquifer exhibits a porosity range of approximately 0.15 in the eastern and southeastern parts (near the outlet of the plain) and around 0.41 in the centeral, northern, and northwestern sections of the area (next to the Asmari Formation). The specific yield (Sy) of the aquifer was calculated using the provided formula: The minimum and maximum specific yield were estimated as 0.006 (in the eastern and southeastern regions) and 0.089 (in the western and northwestern regions of the plain), respectively, with an average value of 0.04. The transmissivity coefficients for the entire aquifer were then calculated based on the fitted relationship between hydraulic conductivity (K) and formation factor (F): The range of transmissivity coefficients varies from a minimum of 63 m2/day (in the western and northwestern sections of the plain) to a maximum of 608.9 m2/day (in the eastern and southeastern areas). The average transmissivity coefficient is calculated as 323.7 m2/day. To ensure the precision of the geoelectric method's coefficients, a comparative analysis was conducted with the hydrodynamic coefficients obtained from the two pumping test wells, as presented in the table below: Well No.K(m/d)T(m2/d)SyPT*VES*PTVESPTVES14.93.63232370.050.0525.75.5655.5632.50.040.03*PT: Pumping Test; VES: Vertical Electrical Sounding Conclusion The evaluation and comparison of the hydrodynamic coefficients derived from the aforementioned methods indicate that the geoelectric method coefficients exhibit acceptable agreement with the pumping test coefficients. In other words, the analysis of the pumping test conducted using the Neuman technique in the unconfined aquifer revealed that well number two displayed a greater transmissivity coefficient, while well number one presented a higher specific yield. These findings are confirmed by the geoelectric approach. Consequently, such hybrid approaches, which include simultaneous analysis of geophysical methods (such as VES) and pumping tests will be a great alternative to multiple costly pumping tests for evaluating the hydrodynamic coefficients of an aquifer. Moreover, employing this hybrid technique enables the generation of dense hydrodynamic coefficients in an aquifer for use as inputs in the groundwater model.

Introduction Soil texture is one of the most influential characteristics that affects the decomposition and retention of soil organic matter, as it directly or indirectly impacts the soil's physical, chemical, and biological properties. Soil clays play an important role in soil organic matter stability. Organic matter adsorbed on phyllosilicate clays is more resistant to microbial decomposition than organic matter that has not interacted with any mineral. Exchangeable cations through the influence of physical and chemical characteristics of the soil probably cause changes in the absorption and retention of organic matter. In previous studies, the effect of soil texture on organic matter retention has been investigated, but the impact of clay type and exchange cation has not been investigated. This study aimed to examine the effect of different contents of vermiculite and zeolite clays and exchange cations on the mineralization of organic nitrogen. Materials and Methods A factorial experiment was conducted in a completely randomized design with three replications to study the effect of the type and content of clay and the type of exchange cations on organic nitrogen dynamics. Experimental treatments include two types of clay (vermiculite and zeolite), four different levels of clay (0, 15, 30, and 45%), and three types of exchangeable cations (Na+, Ca2+, and Al3+). The experiment included 24 treatments and three replications. There were total of 72 experimental units. Artificial soil of 50 grams was prepared separately according to the amount and type of clay and the type of exchange cation. "Next, alfalfa plant residues were added to all samples at a rate of 5% w/w. After inoculating and air-drying the samples, the moisture content was adjusted to 60% of the field capacity (FC) using distilled water. To prevent excess water from affecting the final moisture readings, the samples were first air-dried, and then sufficient distilled water was added to each sample to achieve 60% of FC. The samples were then kept in the dark for 60 days at a temperature of 23 °C. Distilled water was added and sealed to the bottom of the incubation jars to keep the moisture content of the soil samples constant during incubation. The percentage of mineralized nitrogen, microbial biomass nitrogen, and the activity of acid and alkaline phosphatase and cellulase enzymes were determined in the prepared samples. The data were analyzed using ANOVA, and the means were compared using Duncan's Multiple Range Test (DMRT). Before applying ANOVA, the data's normality and variance homogeneity were checked using Kolmogorov- Smirnov and Levene tests, respectively. The SPSS software (Windows version 25.0, SPSS Inc., Chicago, USA) and SAS software (version 9.4, SAS Institute Inc., Cary, NC) were employed for data analysis. Results and Discussion The results of variance analysis of the data showed that the effect of the type and content of clay and the type of exchangeable cation on the percentage of mineralized nitrogen, microbial biomass nitrogen, and the activity of acid and alkaline phosphatase and cellulase enzymes were significant (p< 0.01). The results revealed that, regardless of the duration of the samples, with the increase in the amount of clay, the percentage of inorganic nitrogen and the activity of enzymes decreased, but the nitrogen of microbial biomass increased. The highest percentage of inorganic nitrogen was obtained 60 days after incubation of the samples and in clays saturated with calcium, and the lowest amount of these attributes was obtained 15 days after incubation of the samples and in clays saturated with aluminum. The results showed that nitrogen mineralization increased with the samples' incubation time. Also, the highest percentage of mineralized nitrogen, microbial biomass nitrogen, and enzyme activity were observed in soils with vermiculite. Conclusion The increase in the incubation duration enhanced the percentage of inorganic nitrogen. The percentage of mineralized nitrogen and microbial biomass nitrogen was higher in soils with vermiculite than in soils with zeolite. Moreover, regardless of the incubation duration of samples, with increasing clay content, the percentage of mineralized nitrogen and enzyme activity decreased, but with increasing clay nitrogen content, microbial biomass increased. The highest and lowest amounts of mineralized nitrogen and nitrogen of microbial biomass were measured in soils with calcium and aluminum, respectively. The results showed the effect of the clay type and content and the exchangeable cation type on organic nitrogen dynamics.

Introduction A subtropical high system that significantly impacts the Iranian climate is the Arabia Anticyclone (Raziei, 2012). This high-pressure system is located southeast of the Red Sea, over the Arabian Peninsula and the Arabian Sea. It is one of the semi-permanent centers in the lower levels of the atmosphere, and its influence leads to notable climate changes and characteristics in the region (Karimi, 2016). This system is a component of atmospheric circulation affecting cold-period precipitation in Iran (Karimi et al., 2021); due to its dynamic structure, it has a great ability to provide humid air, especially in the lower layers (Mohammadi & Lashkari, 2018). So far, some studies have been conducted on subtropic high's effect on the Iranian climate, but its impact on the occurrence of precipitation in Iran, especially during the cold period of the year, has received less attention. Therefore, in this study, we aimed to examine the role of the Arabia Anticyclone (AA) subtropical high in the pervasive extreme precipitation during the cold season in Iran. By analyzing its influence at different atmospheric levels, we sought to gain a clearer understanding of how this system affects precipitation patterns in Iran. The study also explores the changes in the AA at various atmospheric levels and its relationship with other atmospheric circulation systems, as well as how these factors contribute to the occurrence of extreme precipitation events in the region. Materials and Methods Daily precipitation data of Iranian synoptic stations from 1989 to the end of 2020 were extracted from the Meteorological Organization of Iran. Based on the relative index method, the 95th percentile index of extreme precipitation for all days and all the stations were calculated and extracted by MATLAB software. The criterion was as follows: If at least 20% of the synoptic stations in Iran have extreme precipitation (in case of spatial homogeneity), the days with pervasive/extreme precipitation were obtained, which amounted to 450 days in the entire period. The isohyetal map of 450 days of extreme/pervasive precipitation was drawn in Surfer software to identify the spatial homogeneity of days with extreme/pervasive precipitation because days with this kind of precipitation did not necessarily have spatial homogeneity. The 450 days with extreme/pervasive precipitation were arranged in ascending order, and 7 patterns with the highest extreme precipitation and the highest spatial homogeneity during the cold period of the year (October-March) were selected. Upper atmospheric data of the selected days were then specified to plot and analyze the synoptic maps. The required atmospheric data were geopotential altitude (meter), wind speed (m/s), wind direction, specific humidity (g/km), and average sea-level pressure. The data used were ERA5 data extracted from https://www.ecmwf.int. The data were extracted at three levels: lower, middle, and upper. To synoptically analyze the selected patterns using the selected upper atmosphere data, the following maps were plotted in Grads software: A) Combined map of geopotential altitude and winds was plotted at the selected levels to determine the geographical location of the subtropical high, its displacement at different levels of the troposphere, its penetration, and its impact on Iran. B) Combined maps of specific humidity, geopotential altitude, and wind were plotted in order to identify the role of the subtropical high in the transfer of humidity and its transfer to Iran at different levels. Conclusion In selected patterns, the AA with its anticyclonic current and passing through tropical warm waters, leads to the transfer of tropical humidity to subtropical and extratropical regions. At different atmospheric levels, the location and establishment of the Anticyclone central nucleus and its degree of expansion towards the north and west are determined by the tropical penetration of the cut off lows and the western trough. The AA has the most dominance over Iran in the lower level. In fact, in the lower level, Iran is dominated by two patterns of cut off low in the western and northern regions and the AA in the southern and eastern regions. Due to the greater penetration of the southern branch of the westerlies and the orbitalization of the western currents in the middle level, the AA is displaced eastward and southward. The interaction and accompaniment of the AA and the mid-latitude cut off low form an atmospheric river with a tropical origin. The AA plays an important role in transferring the atmospheric river to Iran and its humidity feeding. On the maps, the southerly and easterly displacement of the AA Arabia is an important factor in the lack of formation of an atmospheric river in East Central Africa. By transferring tropical humidity to Iran, the humidity of the extreme pervasive precipitation is supplied. Another major role played by the AA is to strengthen the ITCZ humidity in East Central Africa, where tropical humidity ascends through the cut off low, West trough, and jet streams. The AA takes the Indian Ocean humidity to eastern Central Africa with its anticyclonic movement. At the ground level, the AA diverts humidity from the Arabian Sea and the Persian Gulf to the western and northwestern regions, preventing Turkey low from entering the western and southwestern regions of Iran. Furthermore, by entering the South Red sea, prevents the entry of the Sudan low into the Middle East and prevents the entry of precipitation systems into Iran. However, in supplying humidity to the extreme pervasive precipitation of Iran, it plays a very important role both by creating an atmospheric river in interaction with the mid-latitude cut off low and by transferring humidity through its anticyclonic flow.