نشریه علوم آب و خاک (علوم و فنون کشاورزی و منابع طبیعی)
سال بیست و نهم شماره 1 (پیاپی 111، بهار 1404)

Soil and water pollution and waste of resources have occurred due to the excessive use of nitrogen fertilizers in paddy fields. Considering that the biofilm of periphyton formed in paddy fields is mainly responsible for the exchange of nutrients, the present research was designed to investigate the effect of periphyton in the nitrification process in paddy fields and performed with 12 treatments. The treatments included powerful and weak nitrifiers isolated from periphyton, periphyton, periphyton enriched with nitrifiers, and their combination with a dicyandiamide chemical inhibitor. The research was carried out in a rice greenhouse cultivation for 30 days. The results showed that the simultaneous application of periphyton enriched with low-power nitrifier and dicyandiamide can increase the amount of total soil nitrogen, soil phosphorus, soil ammonium, total plant nitrogen, plant phosphorus, plant potassium, shoot length, and dry weight of rice plants. While this treatment reduced the conversion of ammonium to nitrate and subsequently reduced the potential of nitrate formation in the soil, with the increase of ammonium accumulation, it increased the utilization of rice plants. Periphyton can be considered a source for the isolation of nitrifiers. Also, the use of periphyton in paddy fields as a biological and healthy solution to inhibit the nitrification process in front of the use of inhibiting chemicals is placed in the path of future research.

In this study, a conceptual model based on dynamic systems was developed to optimize the management of water, land, and agricultural production (tea and rice) in the irrigation zones of the Sefidroud irrigation and drainage network. To understand the behavior of the network and create a simulation model of the system, a dynamic systems modeling approach was employed, and the simulation was conducted using MATLAB/Simulink. Subsequently, the optimization model of the studied system was developed as a multi-objective model using a genetic algorithm. Various management scenarios were implemented through the weighting of the objective functions. The results showed that selecting the best response from multi-objective optimization models depends on the weighted values of the objective functions, and by changing these values, decision-makers can provide various responses to complex optimization problems. The optimization model determines the cultivated area and water allocation in such a way as to minimize water scarcity and maximize crop performance through different weighting combinations. Furthermore, the findings indicate that the canals of the irrigation network play a crucial role in meeting water needs, and equitable water allocation is essential to prevent excessive extraction and negative consequences, such as saline intrusion and land subsidence. The study demonstrates that the best solutions are contingent upon local conditions and decision-makers' policies. To achieve maximum economic benefits and address water needs, it is suggested to use a weighting combination close to (w1=1,w2=2). Ultimately, this model assists managers and decision-makers in minimizing water scarcity in the region by adjusting cropping levels and optimizing the use of available water resources.

Agriculture, as a crucial economic and social sector in Iran, has always been significantly influenced by weather conditions, water availability, and farm management practices. Enhancing productivity and optimizing resource management in crop production are essential to achieving sustainable agricultural development and ensuring food security. This research aimed to investigate how much wheat, barley, and corn production, separately from irrigated and rainfed crops, will be affected by the severity of climatic drought (based on the CMIP6) in Iran. This research was carried out using the amount of wheat, barley, and corn production in all the provinces, which was provided by the Agricultural Jihad Organization during the years 1371 to 1402. Climate data was obtained from the NEX-GDDP database, and the De Martonne aridity index was calculated to investigate changes in aridity under climate scenarios. The results indicated that during the baseline period, the production of rainfed wheat, barley, and corn under semi-arid to very arid climatic conditions was approximately 2,076, 434, and 15 thousand tons per year, respectively. With the intensification of arid conditions across the country, these production levels are projected to increase to 3,333, 693, and 16 thousand tons under the SSP2 scenario and further rise to 3,558, 842, and 16 thousand tons under the SSP5 scenario. Additionally, the production of irrigated wheat, barley, and corn in semi-arid to very arid climatic conditions during the baseline period stands at approximately 6,240, 1,683, and 5,842 thousand tons, respectively. Under the SSP2 climate scenario, the production is expected to reach about 7,126, 1,757, and 6,253 thousand tons, while in the SSP5 scenario, the estimated production is approximately 7,348, 1,780, and 6,324 thousand tons. The findings revealed notable spatial differences in crop production across the country, highlighting that the climatic conditions, particularly in the central, southern, southeastern, and southwestern regions, are becoming increasingly arid. It is crucial to implement smart planning and policies, adopt advanced technologies, and improve the management of water and soil resources to mitigate the adverse impacts of these changes and better adapt to evolving conditions. Addressing these challenges and implementing effective measures are essential steps toward achieving sustainability in the agriculture and natural resources sectors.

Soils are continuously exposed to large amounts of engineered nanoparticles, particularly silver nanoparticles (AgNPs), which can affect soil microbial activities and nitrogen cycling. The hypotheses of the present study were: (i) vegetation types would differ in their responses to Ag types and concentrations, (ii) these responses would be linked to changes in soil protein and amino acid concentrations, and (iii) combined plant root systems alongside Ag types and concentrations would have offsetting effects on soil protein and amino acid concentrations. A greenhouse experiment was conducted to test these hypotheses using a factorial arrangement of treatments within a randomized block design. Two soil types with loamy sand and sandy loam textures were collected from agricultural fields in Isfahan, specifically from the Badroud (33◦ 44′ 50" N, 51◦ 57′ 55" E) and Femi (33◦ 42′ 17" N, 51◦ 59′58" E) regions. The treatments included: 1) soil types (loamy sand and sandy loam), 2) root systems (non-planted, wheat, and safflower), 3) Ag types (no Ag added, AgNPs, and AgNO3), and 4) Ag concentrations (50 and 100 ppm). The plants were harvested 110 days after sowing, with soil samples collected from both the root zone and non-planted soil, after which the concentrations of protein and amino acids were measured. In the Badroud soil, protein concentration significantly decreased (p < 0.05) with increasing depth. Although depth changes did not show a significant difference in protein concentration in the soil under wheat cultivation, increasing depth resulted in a significant decrease (p < 0.05) in protein concentration in the soil under safflower cultivation. In the Fami soil, the addition of silver nitrate led to a significant (p < 0.05) increase in protein concentration, despite the fact that the addition of silver nanoparticles had no significant (p < 0.05) effect on soil protein concentration. In the Badroud soil, the highest concentration of soil amino acids was observed in the silver nitrate treatment, while the silver nanoparticle treatment did not significantly affect soil amino acid concentrations (p < 0.05). However, applying silver treatments at both tested concentrations resulted in a significant increase (p < 0.05) in soil amino acid levels. Overall, the effects of nanoparticles varied depending on the measured parameters (protein or amino acid), soil texture, and type of cultivation. Further studies are needed to determine the mechanisms by which AgNPs and AgNO3 affect the soil nitrogen cycle in the presence of plants at different soil depths.

Awareness of the impact of water deficit stress on the quantitative and qualitative performance of agricultural products, considering the recent recurrent droughts and reduced precipitation, is essential for water consumption management. This study aimed to evaluate the effects of different irrigation deficit treatments on the yield, yield components, and water use efficiency of autumn wheat in the Shahrekord region. An experiment with three replications was conducted in a completely randomized block design at the Agricultural and Natural Resources Research Center of Chaharmahal Va Bakhtiari Province during 2023-2024. The experimental treatments included four irrigation levels: full irrigation (T100), 80% of full irrigation (T80), 60% of full irrigation (T60), and 40% of full irrigation (T40). The application of the T60 deficit irrigation treatment resulted in a reduction of more than 14% in grain yield, while the T80 treatment caused a more than 31% decrease in grain yield. Additionally, the T60 treatment exhibited the highest water use efficiency at 1.22 kg per cubic meter, while the water use efficiency for the T100, T80, and T40 treatments was 1.06, 1.12, and 1.19 kg per cubic meter, respectively. The results showed that water deficit irrigation significantly affected the grain yield, biomass, and water use efficiency of autumn wheat under the climatic conditions of the Shahrekord region. The results of this study indicated that the T80 deficit irrigation treatment could have a more acceptable performance in terms of water efficiency.

The calcium carbonate equivalent (CCE) in soil is one of the most important soil properties. Predicting the amount of calcium carbonate equivalent in soil is essential for sustainable soil fertility management. The present study aimed to digitally map calcium carbonate equivalent using auxiliary environmental variables, Landsat 8 satellite images, and predictive models and to present the best models in the Badr watershed in the south of Qorveh district. In the first phase, a geomorphologic map was created using a geologic map and based on the ZINC method in a geographic information system environment. In the second phase, the location of 125 survey profiles was determined using the Latin hypercube technique, and the calcium carbonate equivalent of the soil horizons was measured by acid titration. The auxiliary variables included derivatives of the digital elevation model, remote sensing indices from the Landsat 8 satellite, and a geopedological map. The principal component analysis (PCA) method was used to select suitable auxiliary variables. In the third phase, the modeling was carried out, digital maps of the soil classes and properties were created, and the models were evaluated. Two different cases were investigated in this study to estimate the calcium carbonate equivalent of the soil. In the first case, artificial neural network models, decision tree analysis, random forest, and the K-nearest neighbor model were used for prediction. The multiple linear regression model was also used to combine the results of the models. Among the models used to predict the equivalent amount of calcium carbonate using the 10-fold cross-validation method, the multiple linear regression (MLR) model had the highest prediction accuracy with a coefficient of determination of 0.796 and a mean square error of 6.514. In the 5-fold cross-validation method, the K-nearest neighbor (KNN) model had the highest predictive accuracy with a coefficient of determination of 0.9845 and a root mean square error of 2.1258. Due to the spatial nature of the 10-fold cross-validation method, the use of this method is preferable to the 5-fold cross-validation method. In addition, the most important auxiliary variables in order of importance to predict the calcium carbonate equivalent in soil were the carbonate index, slope direction, geomorphology, the base level of the catchment network, and the slope of the catchment.

One of the main factors contributing to water erosion is the inherent characteristic of soil erodibility. Erodibility depends on particle size distribution, organic matter, structure, and soil permeability. This research aimed to investigate changes in the soil erodibility factor across geomorphological facies. The soil erodibility index was estimated by sampling 58 points within the geomorphological facies of the Dorahan watershed, using the Wischmeyer and Smith method. In the laboratory, soil granularity distribution, organic matter, soil structure, the amount of gravel, lime, salinity, acidity, and sodium absorption ratio were measured. Results indicated that soil erodibility across the entire area ranges from 0.0148 to 0.0661 (t.hr/Mj.mm). The soil erodibility index (K) for the hro-p1 and hro-p2 facies is higher than for others and exhibits the widest range of variations compared to the other facies. The lowest range of changes within geomorphological facies is associated with the hrc facies. The erodibility index decreases from the east to the west of the basin due to the presence of exposed rock faces, which protect the soil as a cover layer.

Weirs play a crucial role in flood management and dam safety, accounting for a significant portion of the construction costs of dams. The selection of floods with long return periods for flood design is of utmost importance. However, in some cases, increasing the weir capacity by widening it may be impossible due to topographical limitations. One solution to enhance the flow capacity of weirs is the application of labyrinth weirs. These weirs increase the effective length of the weir crest within a given width, allowing for the passage of higher flow rates while maintaining similar hydraulic conditions. In this study, the hydraulic performance of labyrinth weirs is investigated using the Flow3D numerical model and laboratory data. Since laboratory experiments are time-consuming and costly, employing numerical simulations to achieve more accurate and reliable results for evaluating the hydraulic behavior of labyrinth weirs is prioritized. The results of the simulations indicate that the Flow3D software, utilizing statistical parameters such as R², DC, and RMSE, achieves values of (0.9805, 0.9725, and 0.0142), respectively. This demonstrates its capability to model the flow passing through weirs with high accuracy. The obtained values of the discharge coefficient in Flow3D show a high agreement with the laboratory data from Crookston. The approximate alignment of these results indicates the high accuracy of the numerical model. Additionally, in comparison to different discharges, the relative computational error observed for flow rates of 0.35, 0.6, and 0.44 (cubic meters per second) was approximately 0.5 percent, while for flow rates of 0.3, 0.4, and 0.57, the corresponding errors were 8, 6, and 4 percent, respectively. The results indicate that these tools can be effectively utilized in precise hydraulic analyses and the optimization of weir designs, irrigation systems, and fluid dynamics phenomena.

Water scarcity and adaptation to it are the most significant issues facing Iran's agriculture. Optimizing the cropping pattern is one of the fundamental strategies for addressing water scarcity. This study evaluated the optimization of the cropping pattern in the irrigated lands of Fars province, one of Iran's key agricultural production areas. Linear mathematical programming and the SAWA system (System for Provincial Agricultural Water Balance and Accounting) were employed. The optimal cropping pattern (OCP) was designed to minimize applied irrigation water and was compared with the current cropping pattern (CCP) as well as a proposed cropping pattern from the Agricultural Jahad Organization (CPAJO) for the province for the cropping year 2023-2024. The results indicated that in the OCP, compared to the CCP, the cultivated area for the following crops decreased: wheat by 30%, barley, grain maize, silage maize, alfalfa, sugar beet, potato, cold- season legumes, and cold-season oil crops by 60%, rice by 80%, warm-season fruit trees by 42%, and vegetables by 13%. Conversely, the cultivated area for warm-season legumes and cold-season fruit trees each increased by 60%, while cold-season legumes increased by 150%. To meet the adaptation goals for water scarcity and sustainable agriculture outlined in this study, a 24% reduction in the irrigated cultivation area of the province was deemed necessary. The OCP achieved a 34% reduction in applied irrigation water at the provincial level without decreasing farmers' income. Compared to the CCP, the OCP led to a 32% reduction in the amount of plant production (by weight) at the provincial level. However, prioritizing plants with higher gross economic profit and lower water consumption over those with lower gross economic profit and higher consumption resulted in the gross economic return of the OCP being comparable to that of the CCP and the CPAJO. The comparison of OCP with CPAJO indicated that the CPAJO has not seriously considered adaptability to water scarcity or agricultural sustainability. The CPAJO needs to be reviewed and optimized to address water scarcity and ensure production stability in light of the impacts of excessive water withdrawal in the province.

The soils of the Shahrekord plain, part of the Beheshtabad watershed subbasin in Shahrekord County, Chaharmahal va Bakhtiari province, have been used for crop production and domestic animal feeding for centuries, yet the soil quality of this plain has been overlooked. Therefore, assessing the quality of Shahrekord plain soil is essential. This research aimed to evaluate the physical soil quality of the plain using soil quality indices such as the Integrated Quality Index (IQI) and Nemoro Quality Index (NQI). A randomized compound sampling strategy was employed, and 106 surficial (0-25 cm) soil samples were collected during intensive fieldwork. Following pretreatments of the soil samples, several key soil characteristics were measured using standard methods, which were compiled into a Total Data Set (TDS) and used to calculate IQITDS and NQITDS. The minimum effective data set (MDS) was selected, and weights for the quality indices were determined using TDS and Principal Component Analysis (PCA). The minimum data set included the soil sand percentage, soil organic matter percentage, mean weighted diameter of aggregates, soil moisture at field capacity, bulk density, soil reaction, and electrical conductivity. The soil quality at each sample site was assessed using the indices and data sets, TDS and MDS. Geostatistical techniques and ordinary kriging methods were utilized to map soil quality. Results indicated that the soil quality of rangelands was significantly higher than that of cultivated soils (irrigated and drylands). Additionally, approximately 71% of the soils were classified as very low, low, and medium quality, highlighting the need for monitoring and managing such soils.

Heavy metal pollution is considered a serious risk to the environment and human health due to its toxicity and indestructibility. Measuring and monitoring little concentration (even lower than the detection limit of the device) in the case of dangerous and biostable pollutants such as cadmium in natural water samples is a necessity. Solid-phase extraction using carbon adsorbents is the most efficient and common method of pre-concentration of heavy metals from environmental samples. The carbon adsorbent used in solid phase extraction must have favorable physical and chemical characteristics, along with low cost and biocompatibility. In this research, Aphanocapsa cyanobacterial cells were used as a cheap precursor to make a microscale absorbent using the hydrothermal method. The qualitative and absorption characteristics of this adsorbent were evaluated using instrumental analysis tests and chemical tests based on cadmium. The absorbent is made in the form of relatively spherical particles (with a size of less than 10 micrometers) with a rough surface and a specific surface area of 382.02 square meters per gram. The efficiency of cadmium absorption of absorbent was in a wide range of pH (3 to 8) and more than 90% due to the buffering effect. The absorbent surface was rich in oxygen and nitrogen functional groups, such as hydroxyl, isothiocyanate, and carbonyl. The cadmium absorption isotherm was the best fit with the Freundlich nonlinear model, and the cadmium absorption rate was the best fit with the pseudo-second-order nonlinear model. The calculation variables related to the Freundlich model, including the inverse of the absorption intensity, showed that the adsorbent has a great tendency to absorb low concentrations of cadmium. Cadmium had the most and least competition for absorption on the adsorbent with alkali metal cations and heavy metal cations, respectively. The resistance of the adsorbent against the increase of ionic strength and the concentration of competing cations was equal to 4 and 20 mg/liter, respectively. The washing efficiency of the adsorbent loaded in the adsorbent-to-solution ratio (1:1000), at a normal concentration of 0.3 and a volume of 160 microliters of detergent (nitric acid), reached its maximum value. According to the findings of this research, the carbon adsorbent originating from the cyanobacterium Aphanocapsa can be an efficient adsorbent to use in the solid phase extraction of cadmium to reduce environmental pollution due to its unique properties.

Piano key weirs are a new form of labyrinth weirs and exhibit nonlinear characteristics. Due to their high efficiency regarding flow capacity, it is crucial to investigate local scour and identify solutions to mitigate it. Local scour was examined downstream of a trapezoidal piano key weir type B for the first time in this study. The weir was installed 5.50 m from the start of the channel and has a height of 0.20 m, featuring three cycles (three outlet keys, two inlet keys, and two inlet half keys). Three tailwater depths and three different flow rates were also utilized. The maximum scour depth increases with a higher densimetric Froude number and flow rate while decreasing with tailwater depth. The range of the dimensionless parameter for the densimetric Froude number in this study varies between 1 and 2. Additionally, sand and gravel were employed as two types of bed materials. As the diameter of the bed material increases, the maximum scour depth decreases. The scour index for gravel bed material is significantly lower than that for sand material, indicating that the risk of weir overturning is much lower in gravel bed material.