Water and Soil

Abstract Introduction
Rapseed (Brassica napus L), particularly the low erucic acid and glucosinolate cultivars known as canola, is the third largest oilseed crop in the world after soybean and oil palm. In Iran, canola cultivation covers approximately 173 thousand hectares, making it the largest cultivated area among oilseed crops. Golestan and Khuzestan provinces have the largest cultivated areas. Balanced fertilization is crucial for optimizing canola yield, especially under adverse environmental conditions. Plant tissue analysis serves as a fundamental tool for diagnosing nutrient status and exploits the principle that tissue nutrient concentration reflects soil nutrient availability. Advanced diagnostic methods, such as deviation from optimum percentage (DOP) and nutrient balance index (NBI), provide quantitative measures of nutrient adequacy and imbalance. The DOP method ranks nutrient deficiencies by comparing observed tissue concentrations with those in high-yielding populations. Meanwhile, the NBI integrates multiple nutrient statuses into a single measure (Σ|DOP|) and provides a comprehensive assessment of overall nutrient health.
Materials and Methods
The study was conducted in four provinces: Alborz, Markazi, Golestan, and Ardabil (Moghan region), to reflect the diverse agro-ecological conditions of the country. Thirty farms were randomly selected in each province.
Alborz province (Karaj region) is located at latitudes 35°48'N and 51°10'E. Markazi province (Arak city) is located at latitudes 34°5'30'N and 49°41'30'E. East Golestan Province (Gonbad Kavus region) is located at coordinates 37°16'N and 55°12'E, while Ardabil Province (Parsabad and Moghan regions) is located at coordinates between 39°12'N and 39°42'N and 47°10'E and 48°21'E.
Soil samples were collected from the fields before planting. Plant tissue samples were taken at the biganing of stem elongation stage (two-digit growth code 30), which is a sensitive stage for identifying and eliminating nutrient deficiencies before canola flowering. Plant samples were collected as whole plants from 20 random points per hectare, and 20 plants were sampled from each point. Total nitrogen (N), phosphorus (P), potassium (K), and micro nutrients zinc (Zn), manganese (Mn), iron (Fe), copper (Cu), and boron, were measured in plant tissue. Grain yield was measured at maturity. To assess nutrient status and identify yield-limiting factors, the key diagnostic index, deviation from optimal percentage (DOP), quantifies the deviation in nutrient concentrations from the optimal values observed in high-yielding populations. The NBI index was also used in this study.
Results and Discussion
In terms of soil properties, there was significant variation in pH, salinity, organic carbon, and nutrient availability across the studied provinces.
In Alborz province, the average organic carbon content was low (0.81%) and the frequency of nutrient deficiencies was high, including nitrogen (N, 73%), phosphorus (P, 47%), potassium (K, 20%), sulfur (S, 87%), magnesium (Mg, 37%), iron (Fe, 83%), copper (Cu, 20%), zinc (Zn, 50%), manganese (Mn, 43%), and boron (B, 60%). In Markazi Province, with an average salinity of 1.47 dS/m, severe deficiencies of nitrogen (90%), phosphorus (75%), and potassium (37%) were observed. In Golestan Province, non-saline soils in this region with an average organic carbon percentage of 1.4% showed deficiencies of nitrogen (27%), phosphorus (94%), potassium (32%), magnesium (100%), iron (32%), copper (22%), manganese (31%), and zinc (81%). In Ardabil Province, high clay content (40%) and salinity (2.4 dS/m) led to deficiencies of phosphorus (50%), potassium (1%), sulfur (99%), magnesium (99%), iron (50%), copper (3%), zinc (87%), and manganese (10%).
DOP standards for nutrient concentrations in canola shoots during stem elongation were determined as follows: nitrogen 3.61%, phosphorus 0.46%, potassium 2.8%, sulfur 0.513%, magnesium 44.00%, calcium 1-2%, iron 226 mg/kg, copper 1.8 mg/kg, manganese 78.5 mg/kg, zinc 45.8 mg/kg, and boron 54 mg/kg.
The nutrient balance index (NBI), calculated as the sum of absolute DOP values, was inversely correlated with yield, confirming that greater nutrient imbalances resulted in reduced yield. Statistical analyses confirmed that NBI thresholds between 133 and 146 corresponded to significant yield reductions (p<0.01). based on these thresholds, yield decreased by 12 to 18% for each unit increase in NBI. It is noteworthy that when NBI exceeds a certain threshold (NBI breakpoint) (BPC), yield reduction becomes more evident. Below this threshold, yield is less affected by NBI. Alborz province had the highest BPC (146), followed by Ardabil (139), Markazi (138), and Golestan (133) provinces, respectively. Farmers and advisors can use this range as a guide for fertilizer recommendations.
Conclusion
This study shows that the variability of canola yield in agro-ecological regions of Iran is primarily due to the deficiency of region-specific nutrients, especially phosphorus and zinc, combined with soil alkalinity, low organic carbon, and mineralogical characteristics. By implementing region-specific nutrient management strategies, yield gaps can be closed, and sustainability in semi-arid oilseed systems can be promoted. The Balance Index integrates vital nutrient ratios (such as phosphorus:zinc, magnesium:potassium) to detect imbalances.

Abstract Introduction
Cadmium (Cd) and lead (Pb) contamination of calcareous soils can restrict wheat production in arid and semi-arid regions. High pH and calcium carbonate reduce metal solubility but cannot fully prevent root uptake or food-chain entry. Both metals impair nutrient acquisition, damage chloroplasts and membranes, reduce photosynthesis, and promote ROS production, causing oxidative damage and redox imbalance. Thiols mediate plant responses to metal stress. Cysteine supplies sulfur for glutathione synthesis, while glutathione supports redox buffering, antioxidant reactions, metal detoxification, and phytochelatin production. Evidence for simultaneous foliar application of cysteine and glutathione under Cd–Pb stress in wheat grown in calcareous soil remains limited. This study examined individual and combined thiol sprays on wheat growth, oxidative damage, glutathione redox status, and Cd and Pb accumulation under Cd–Pb co-contamination.
Materials and Methods
A pot experiment was conducted in a greenhouse at the Faculty of Agriculture, Ferdowsi University of Mashhad. Calcareous clay loam soil was collected from the 0–30 cm layer of agricultural land near Sabzevar, Iran. Soil pH was 7.89 (1:2.5 soil:water), electrical conductivity 2.53 dS m⁻¹, organic matter 1.03%, and calcium carbonate equivalent 24.55%. DTPA-extractable Cd and Pb were 0.12 and 1.5 mg kg⁻¹, respectively, representing low background levels before contamination.
The experiment used a randomized design with five treatments and three replications (15 pots): control without metals, sprayed with deionized water; HM, with 15 mg Cd kg⁻¹ soil and 300 mg Pb kg⁻¹ soil; HM+Cys, with 0.41 mM L-cysteine foliar spray; HM+GSH, with 2 mM reduced glutathione; and HM+Cys+GSH, receiving 0.41 mM cysteine plus 2 mM glutathione. L-cysteine and reduced glutathione (≥99% purity) were obtained from Sigma–Aldrich.
Cadmium and Pb were added as Cd(NO₃)₂ and Pb(NO₃)₂ to 5 kg soil per pot. Nitrate input was identical among contaminated treatments and considered a common HM component. Soils were mixed and incubated for four weeks near field capacity before planting. Wheat seeds (Triticum aestivum L. cv. Falat) were disinfected in 5% sodium hypochlorite for 10 min, rinsed three times with deionized water, and sown in pots 23 cm in diameter and 21.5 cm high. Eight seeds per pot were thinned to five plants after establishment. Foliar treatments were applied at tillering, stem elongation, and booting; controls received equal volumes of deionized water.
Plants were harvested about 70 days after sowing. Shoot dry biomass was measured after oven drying at 70 °C for 72 h. Total chlorophyll was determined in 80% acetone extracts at 663 and 645 nm following Lichtenthaler (1987). MDA and H₂O₂ were measured at 532 and 390 nm, respectively. GSH and GSSG were assayed in 2% metaphosphoric acid extracts using glutathione reductase, NADPH, DTNB, and 2-vinylpyridine; the GSH/GSSG ratio assessed redox status.
Root and shoot samples were wet-digested with concentrated HNO₃ and H₂O₂, and Cd and Pb concentrations were determined by flame AAS (Analyst 800, PerkinElmer). Oxidative stress index, total thiol pool, tolerance index, chlorophyll protection efficiency, and transfer factor were calculated. Data were analyzed by one-way ANOVA, and means were compared using Duncan’s multiple range test.
Results and Discussion
Combined Cd and Pb stress substantially reduced wheat growth. Shoot dry biomass declined from 12.50 g pot⁻¹ in the control to 7.10 g pot⁻¹ under HM, a 43% reduction. Total chlorophyll decreased from 2.10 to 1.10 mg g⁻¹ fresh weight (47%). All thiol treatments improved both traits. Shoot biomass reached 8.60, 9.60, and 11.00 g pot⁻¹ in HM+Cys, HM+GSH, and HM+Cys+GSH, respectively, while chlorophyll increased to 1.50, 1.70, and 1.90 mg g⁻¹ fresh weight. Tolerance index and chlorophyll protection efficiency showed similar responses. The combined treatment produced the highest values among metal-stressed plants, although neither trait fully reached control values. Oxidative damage increased sharply under HM. MDA increased from 15.00 to 40.00 nmol g⁻¹ fresh weight, while H₂O₂ increased from 4.30 to 12.20 µmol g⁻¹ fresh weight. Cysteine, glutathione, and their combination reduced both indices. MDA concentrations were 32.00, 27.00, and 22.00 nmol g⁻¹ fresh weight in HM+Cys, HM+GSH, and HM+Cys+GSH, respectively; corresponding H₂O₂ values were 9.20, 7.50, and 6.20 µmol g⁻¹ fresh weight. The OSI increased from 0.05 in the control to 0.37 under HM. Cysteine reduced it to 0.17, whereas glutathione alone and the combined treatment both reduced it to 0.10. Therefore, the combined treatment did not exceed glutathione alone for this index, showing that treatment superiority differed among traits.
Cd and Pb strongly affected glutathione redox status. GSH declined from 85.30 to 32.90 nmol mg⁻¹ protein under HM, whereas GSSG increased from 15.20 to 31.00 nmol mg⁻¹ protein. Accordingly, the GSH/GSSG ratio declined from 5.61 to 1.07. Thiol application improved redox status in all treated plants. HM+GSH produced the highest GSH concentration, whereas HM+Cys+GSH produced the highest GSH/GSSG ratio. Under the combined treatment, GSH reached 62.70 nmol mg⁻¹ protein, GSSG decreased to 10.50 nmol mg⁻¹ protein, and the GSH/GSSG ratio reached 6.00. This ratio differed significantly from all stressed treatments but not from the control, indicating near-control redox restoration. Thiols also reduced Cd and Pb accumulation. Under HM, Cd concentrations were 19.0 mg kg⁻¹ in roots and 7.6 mg kg⁻¹ in shoots; under HM+Cys+GSH, they decreased to 10.4 and 4.0 mg kg⁻¹, respectively. Root Pb declined from 25.5 to 12.5 mg kg⁻¹, while shoot Pb declined from 9.8 to 5.5 mg kg⁻¹. Cysteine and glutathione alone also lowered both metals, although differences between HM+GSH and HM+Cys+GSH for shoot Cd and Pb were often not significant.Transfer factors for Cd and Pb remained below 0.5, indicating limited root-to-shoot translocation. Roots retained a substantial proportion of absorbed metals, reducing but not eliminating accumulation in shoots.
Conclusion
Cd–Pb co-contamination reduced wheat shoot biomass and chlorophyll, increased MDA and H₂O₂, and disrupted glutathione redox balance. Foliar cysteine and glutathione alleviated these effects. Their combined application produced the strongest response for most growth, oxidative, redox, and tissue-metal traits, improving biomass and chlorophyll, reducing oxidative damage, restoring GSH/GSSG to a control-comparable value, and lowering Cd and Pb in roots and shoots. Transfer factors remained below 0.5, indicating limited root-to-shoot translocation. Field validation and grain-metal measurements are required before recommending this treatment for food production.

Abstract Introduction: Mycorrhizal symbiosis, particularly arbuscular mycorrhiza, is recognized as one of the most widespread and beneficial interactions between plants and soil microorganisms and has been extensively studied. This symbiosis plays a significant role in improving plant nutritional status, enhancing resistance to both biotic and abiotic stresses, reducing the impact of certain pathogens, and promoting synergistic interactions with other beneficial microbial communities. Ultimately, these effects contribute to improved crop health and productivity. One of the most important benefits of this association is the enhancement of plant nutrition. Mycorrhizal plants acquire nutrients either directly through their roots or indirectly via the hyphal network of symbiotic fungi. The predominance of either pathway depends on a complex set of biochemical and molecular mechanisms within the common symbiosis pathway, as well as phosphorus availability, plant phenotypic traits (especially root characteristics), and environmental conditions. Despite its importance, the degree of mycorrhizal dependency varies among plant species and cultivars. Mycorrhizal dependency is defined as the extent to which a plant relies on mycorrhizal fungi to achieve optimal growth or yield. It is determined by the interaction between plant genotype and phenotype in combination with environmental factors.
Mycorrhizal symbiosis is the result of a complex molecular dialogue between plant and fungus, involving the exchange of signals at cellular, molecular, and genetic levels. In the early stages of symbiosis, plants secrete compounds such as strigolactones from their roots, which stimulate spore germination and hyphal branching. This is followed by fungal signalling molecules, including chito-lipo-oligosaccharides, which act as key signals in the initiation and regulation of arbuscular mycorrhizal symbiosis. Disruption in this shared signalling pathway can lead to failure of symbiosis establishment or reduced mycorrhizal dependency.
Under high nutrient conditions, particularly high phosphorus availability, plant secretion of strigolactones is typically reduced. This illustrates how excess soil phosphorus can interfere with the common symbiosis signalling pathway and thereby decrease mycorrhizal dependency. The synthesis and secretion of strigolactones are regulated by the upregulation of genes such as D27, CCD7, CCD8, and MAX1.
Recent advances in plant molecular biology and genetics have identified a set of genes involved in the common symbiosis pathway that play essential roles in fungal signal recognition, activation of cellular responses, and the formation of fungal structures such as arbuscules. These genes, including SYMRK, CCaMK, and CYCLOPS, will be discussed in detail later. Depending on the upregulation or downregulation of these genes in the plant–fungus symbiotic pathway, a higher or lower degree of mycorrhizal dependency can be expected, respectively.


Materials and Methods: This analytical review integrates findings from researchers in this field by utilizing up-to-date studies on the intensity of plant–fungus symbiosis and the degree of mycorrhizal dependency from morphological, physiological, biochemical, and especially molecular dimensions. These studies are accessible through major international databases, including Web of Science and Scopus. In addition, Google Scholar provides an open-access platform for identifying recent publications, while specialized resources such as ScienceDirect, SpringerLink, and Taylor & Francis offer valuable journal articles, book chapters, and authoritative reference works related to mycorrhizal dependency and the underlying mechanisms involved, particularly from a molecular perspective.
Results: The results of numerous studies indicate that the establishment of symbiosis between plants and arbuscular mycorrhizal fungi requires a series of complex physiological, biochemical, and molecular interactions. This process is initiated by the secretion of Myc-LCO signalling molecules by the fungus, which are subsequently recognized by specific receptors in plant roots, including SYMRK (DMI2). Following recognition, the common symbiosis signalling pathway is activated, and the release of calcium ions (Ca²⁺) through DMI1 generates rhythmic calcium oscillations within plant cells. These oscillations function as informational codes that are decoded by the calcium and calmodulin-dependent protein kinase (CCaMK). The calcium signals are then translated into molecular responses, leading to the activation of the transcription factor CYCLOPS and the regulation of symbiosis-related gene expression, ultimately resulting in arbuscule formation. Any disruption or interruption in this signalling pathway may prevent arbuscule development, particularly in non-host plants. The degree of plant dependence on mycorrhizal fungi is influenced by a range of factors, including plant, fungal, and environmental characteristics. Among environmental factors, abiotic stresses such as drought play a critical role. Under drought conditions, the influx of Ca²⁺ into the plant cell cytosol decreases, leading to disturbances in cellular ion homeostasis. However, the presence of mycorrhizal fungi enhances the expression of calcium-sensing and signalling genes, including CBLs, CDPKs, and MAPKs, thereby activating Ca²⁺-dependent signalling pathways. This process regulates and reinforces the increase in cytosolic Ca²⁺ concentration, which acts as an important secondary messenger during the establishment and maintenance of mycorrhizal symbiosis. Furthermore, numerous studies have demonstrated a significant relationship between mycorrhizal dependency and root morphological characteristics. In general, plant species possessing a magnolioid root architecture exhibit a greater degree of dependence on arbuscular mycorrhizal fungi than species with non-magnolioid root systems.
Conclusions: Although many plant species can establish symbiosis with mycorrhizal fungi, the degree of dependency and effectiveness of this association varies considerably. These differences are largely determined by the complexity of signalling pathways and the regulation of symbiosis-related genes. A deeper understanding of the underlying molecular and cellular mechanisms is essential for improving mycorrhizal symbiosis, although significant challenges remain in its practical application.

Abstract Introduction: Soil salinity in arid and semi-arid regions is one of the important factors that limits crop production, and affects plant yield through various mechanisms. Chlorophyll destruction and reduction of leaf area due to high sodium concentration leads to a decrease in photosynthesis. The application of humic acid and amino acid with hormonal effects and adjustment of nutrients has been suggested to reduce salinity stress. The experiment aimed to investigate the effect of plant growth biostimulants and salinity levels on the growth indices of two canola cultivars in greenhouse condition.
Materials and Methods: This study was carried out as a factorial study based on a completely randomized design with three replications. The three experimental factors included: 1) salinity factor in three levels (0.571, 4, and 8 dS m-1), 2) canola cultivars in two levels (Hyola 50 and Dalgan), and 3) types of plant growth biostimulants in four levels (amino acid, humic acid, a combination of these two biostimulants, and a control treatment with no biostimulants application). Before the flowering stage (8 weeks after planting), the plants were harvested and some morphological traits including plant dry weight, root dry weight, and the concentration of calcium, sodium, and potassium in the shoot were measured.
Results and Discussion:
Based on the results, the cultivar Hyola 50 (8.35 g plant-1) had a significantly higher shoot dry weight than the cultivar Dalgan (7.58 g plant-1). The reduction in shoot dry weight at a salinity level of 8 dS m-1 was 19.3% compared to the treatment of 0.571 dS m-1. At salinity levels of 0.571 and 4 dS m-1, there was no difference between the effects of biostimulant treatments compared to the control (without biostimulants). But at a salinity level of 8 dS m-1, the shoot dry weight of the humic acid treatment (7.26 g plant-1) was significantly higher than the control treatment (16.6 g plant-1) (17.9% difference). The effect of humic acid application on leaf area (748 cm2 plant-1) was greater than that of amino acid foliar application (670 cm2 plant-1). With an increase in salinity level to 8 dS m-1, the dry weight of roots decreased. The highest dry weight of the root in the Dalgan cultivar at 8 dS m-1 was obtained in the combined treatment (0.607 g plant-1) and for the cultivar Hyola 50 in the combined treatment and amino acid (0.607 g plant-1). There was a significant difference in root dry weight between salinity of 4 dS m-1 (0.703 g plant-1) and 8 dS m-1 (0.543 g plant-1). The root dry weight of the plant was more affected by salinity stress than the shoot dry weight. In both canola cultivars, at a salinity level of 8 dS m-1, the chlorophyll index (SPAD) increased compared to a salinity level of 0.571 dS m-1 (4.6% increase in Dalgan cultivar and 9% in Hyola 50 cultivar). The shoot potassium concentration of the Dalgan cultivar (11.6%) was significantly higher than that of the Hyola 50 cultivar (92.5%), but the amount of uptake was higher in Hyola 50 cultivar (492.0 versus 459.0 g plant-1). At 8 dS m-1 salinity, the furthest potassium to sodium concentration ratio of the Dalgan cultivar was obtained with amino acid and humic acid treatment (4.87) and with the Hyola 50 cultivar with the humic acid treatment (4.21). At 8 dS m-1 salinity, the calcium to sodium concentration ratio of the Dalgan cultivar was obtained from the amino acid and humic acid treatment (12) and for the Hyola 50 cultivar from the humic acid, amino acid, and combined treatment (11). At a salinity level of 8 dS m-1, combined treatment of biostimulant in both Dalgan (1236 meq l-1) and Hyola 50 (250 meq l-1) cultivar had the highest amount of soil-soluble chlorine. This treatment may have reduced the absorption of chlorine ions by the plant. Shoot dry weight had the highest correlation with root dry weight and leaf area (0.58**). Shoot dry weight had the negative correlation with plant sodium concentration (-0.27**). The negative effect of soil-soluble sodium concentration on root dry weight (-0.39**) was greater than on shoot dry weight (-0.27**).
Conclusion: The positive effect of the application of growth biostimulants was observed through improving potassium absorption and improving the ratio of calcium and potassium to sodium concentrations in the shoot. In saline conditions (8 dS/m), the recommended phosphorus fertilizer for Dalgan variety must be 23.6%, and for the Hyola 50 variety, 10% more phosphorus fertilizer than in non-saline conditions. The application of Hyola 50 and humic acid as fertigation in saline conditions is recommended for canola.

Abstract Introduction
Drought can be considered one of the most significant hazards for sustainable living in rural areas of Iran, whose many regions are characterized by arid and semi-arid climate. During the last decades, drought occurrence has led to decrease of ecosystems' services provision and negative socio-economic consequences. Moreover, pressure on surface and underground water has been rising, especially in the agriculture-focused Fars province. Despite numerous drought assessment studies performed in Iran, the use of composite indexes that would integrate both social and environmental aspects of drought resilience on the basis of objective and available data is relatively rare. Indeed, earlier studies had used narrow criteria sets or questionnaire-based approaches to estimate social resilience, without developing replicable data-driven approach. However, such a development is needed due to multi-dimensional nature of the concept, which encompasses several factors like land use dynamics, population trends, agriculture diversity, irrigation system, education, and employment age structure. Therefore, development of a composite index to analyze all those factors is required for effective decision making in this area. In this paper, the analysis of social resilience to drought on the basis of LPCIEA composite index will be done in two rural settlements – Mohammadabad and Majdabad – of Marvdasht County, Fars province, over the period of 24 years (2000-2024).
Materials and Methods
LPCIEA composite index includes six criteria: Land use (L), Population (P), Crop diversity (C), Irrigation level (I), Education (E), and Employment age (A). Data on these criteria were collected from various sources: Landsat ETM (2000) and Sentinel-2 (2024) imagery for land use classification and NDVI calculation; census statistics and statistics at village level for Population and Education; field survey for irrigation level and crop diversity. Image pre-processing, including atmospheric and geometric correction was carried out in ENVI 5.6, while maps of land uses were created on the basis of SVM classification with accuracy from 86% to 91% and Kappa index from 0.82 to 0.89. Crop diversity was estimated on the basis of Shannon-Wiener index. All variables were standardized with the help of Min-Max method to 0-1 scale. Weights for each criterion and sub-indicator were objective and were estimated by means of PCA, which accounted for 76.4% of total variance with the help of five principal components. Resilience score (R) for each village was calculated as a linear weighted combination of six standardized criteria. Multiple regression analysis (ENTER method) was used to determine contributions of each criterion to total resilience. Model validation was carried out with the help of Durbin-Watson statistic and test on multicollinearity (VIF and Tolerance), while spatial maps of resilience were made for 2000 and 2024.
Results and Discussion
Over the period of 24 years, 12 states of resilience were identified for the two villages and six criteria. Six of them were red ("very low resilience"), three were yellow ("moderate but declining") and only three states were green ("favorable"), what indicates dominance of critical states and long-term erosive trend. Regression model had excellent goodness-of-fit, with multiple correlation coefficient (R) 0.995 and Adjusted R² 0.98, while Durbin-Watson statistic of 1.892 proves absence of autocorrelation. Out of six criteria, "Crop diversity" (C) had the greatest positive and statistically significant effect on resilience with the beta coefficient of 0.785 (p < 0.01), contributing to 96% of explained variance. On the contrary, "Education" (E) had the lowest effect (β = 0.095, p = 0.63), what indicates that despite the considerable increase in literacy rates, it had little influence on drought resilience in comparison to agriculture diversification and irrigation. Other criteria in order of importance were Population (β = 0.465), Employment age (β = 0.430), Land use (β = 0.380), and Irrigation (β = 0.250). Derived regression equation is as follows: R = 1.450 + 0.090L + 0.220P + 0.185C + 0.110I + 0.040E + 0.145A. According to temporal analysis, Majdabad village showed considerable population growth (resilience score from 46 to 77), Mohammadabad village showed moderate growth (44 to 50), while both villages suffered from severe decrease in crop diversity (from 42 to 7 points) and irrigation level (from 36 to 16 points), which is the consequence of water shortage. On the other hand, education score increased substantially (from 8 to 41-46 points), but didn't lead to the corresponding increase in resilience because of the priority of production-related factors.
Conclusion
It is evident that drought resilience in analyzed villages is mostly determined by crop diversification and availability of water resources, rather than demographic and educational factors. Majdabad village, which has greater population (8,970 people) and greater pressure on resources, needs urgent adaptive measures, followed by Mohammadabad. Dominance of red-status resilience states (6 of 12) indicates critical threshold, and immediate policy measures are needed. Therefore, the following recommendations can be made on the basis of this research. It is necessary to focus the supportive policies on increasing crop diversity, promotion of crops with low demand for water and diversification of agricultural portfolio. Equally important is active participation of local communities in decision making bodies – like strategic planning, priority setting and budget allocation, which will promote social cohesiveness and joint actions. Different villages showed different adaptive capacity under similar climatic conditions, therefore, differentiated rather than general strategy is needed. Index LPCIEA, which provides objective weighting on the basis of PCA and uses replicable satellite and census data, is useful instrument for periodic resilience monitoring. Future research should expand this approach to other regions and incorporate climate projection scenarios into it.
Acknowledgement
This work is derived from part of the results of an independent research subproject entitled "Analysis of Social Resilience to Drought Using a Composite Index (Case Study: Fars Province)", with code 0-66-29-012-010495 and approved by the Soil Conservation and Watershed Management Research Institute. The authors of this article would like to acknowledge the cooperation and support of that research institute and the support of the Fars Agricultural and Natural Resources Research and Education Center.

Abstract Introduction
A large amount of precipitation is lost annually. Therefore, studying the precipitation-runoff process and predicting runoff are essential in water resources studies and plans and water engineering discussions. Therefore, choosing a model that can predict runoff from rainfall with acceptable accuracy using effective factors seems essential. The aim of this research is to estimate the components of unit hydrographs resulting from several precipitation-runoff events in the Samian watershed located in Ardabil province using a nonlinear optimization method along with the application of probability distribution functions.

Materials and Methods
In order to determine the optimal values of the distribution function parameters, the objective function is considered as minimizing the sum of the squares of the deviation between the predicted and actual direct runoff hydrographs. The values of the probability distribution functions parameters are optimized using Mathematica software and nonlinear programming method. Finally, the direct runoff hydrographs are calculated using the effective rainfall hydrographs and the corresponding unit hydrographs and compared with the observed direct runoff hydrographs. The performance criteria of mean square error, mean absolute error and correlation coefficient are used to examine the ability of the functions in the calibration and testing stages. The classical least squares method is also used to extract the unit hydrographs and its efficiency is compared with the results of the nonlinear optimization model.

Results and Discussion
In the calibration period, for the first event, the RMSE and MAE errors of the Gumbel (0.0048 and 0.0042) and Nakagami (0.0134 and 0.0095) functions are higher and their correlation coefficients (0.935 and 0.237, respectively) are also lower than those of the other functions. The lowest errors (0.0021 and 0.0016) and the highest correlation coefficient (0.978) are related to the lognormal distribution. The weakest distribution is the Nakagami distribution with RMSE equal to 0.0134, MAE equal to 0.0095, and CC equal to 0.237. In the case of the second event, the RMSE and MAE errors of the Gumbel (0.0110 and 0.0070) and Nakagami (0.0223 and 0.0293) functions are higher and their correlation coefficients (0.682 and -0.087) are also lower than the other functions. The lowest errors (0.0068 and 0.0056) and the highest correlation coefficient (0.874) are related to the lognormal distribution. The weakest distribution is the Nakagami distribution with RMSE of 0.0223, MAE of 0.0293, and CC of -0.087. In the case of the third event, the performance of all functions is satisfactory due to very low RMSE and MAE values and very high correlation coefficient. However, the errors of the gamma and lognormal functions are slightly higher than the others. Also, Weibull and normal distributions show better performance than other distributions based on the values of performance criteria because these distributions showed high ability in predicting the ascending and descending branches of the unit hydrograph.
In the test period, considering the average values of the performance functions of the distributions in each event, it can be said that the lognormal distributions (with average RMSE and MAE errors of 0.0134 and 0.01115 and average correlation coefficient of 0.823) and the normal distribution (with average RMSE and MAE errors of 0.0142 and 0.01275 and average correlation coefficient of 0.739) have higher potential in estimating the unit hydrographs of the basin, respectively. The errors of Pearson and Nakagami distributions in both events were higher than the other distributions. The least squares method also had better performance criteria values than all distributions in both events.

Conclusion
In general, according to the results obtained in the calibration and testing period, it can be concluded that the lognormal distribution is the best distribution for estimating and calculating unit hydrographs (especially in estimating the ascending branch and peak time and discharge) in the Samian basin. Also, the Pearson and Nakagami functions are among the weakest distributions in estimating the hydrographs of that basin. The least squares method, regardless of its shortcomings, is among the appropriate methods in estimating the unit hydrograph.
For future studies, it is suggested to investigate the performance of other statistical distributions such as beta and logistic distributions in extracting the unit hydrograph of the Samian basin. Also, the performance of statistical distributions in determining the unit hydrograph from combined precipitation-runoff events and from precipitation-runoff events related to the warm months of the year in which the basin does not have snow storage should be investigated. Finally, similar research should be conducted in other watersheds of Ardabil province and a suitable model should be proposed for the entire province.

Keywords: Nonlinear optimization, least squares, precipitation-runoff event, Mathematica software, Unit Hydrograph

Abstract Introduction
Dust is one of the most important environmental hazards in arid and semi-arid regions and can affect vegetation health through reducing incoming radiation, depositing particles on leaf surfaces, disrupting photosynthesis, and intensifying environmental stresses. Khuzestan Province is considered one of the major dust-affected regions in Iran due to its geographical location, proximity to domestic and transboundary dust sources, sensitive wetlands, extensive agricultural lands, recurrent droughts, and land-use changes. The reduction of wetland water levels, decline in soil moisture, improper water resource management, and human activities have also increased the vulnerability of this region. Since vegetation plays an important role in soil stabilization and the reduction of wind erosion, investigating the effects of dust events on vegetation conditions is of great importance for environmental and agricultural management. The aim of this study is to analyze the temporal effects of dust events on vegetation health in Khuzestan Province during the period 2001–2023 using remote sensing and atmospheric reanalysis data.
Materials and Methods
In this study, monthly data for the period 2001–2023 were used. To monitor dust intensity, dust aerosol optical depth at 550 nm obtained from the MERRA-2 dataset was employed. In addition, total AOD and the ratio of dust AOD to total AOD were calculated to examine the contribution of dust to the total aerosol burden over the region. Vegetation health was evaluated using two indices, NDVI and EVI, derived from the MODIS MOD13A2 product, version 6.1. NDVI was used as an indicator of vegetation greenness and density, while EVI was applied because of its lower sensitivity to atmospheric effects and vegetation saturation.
The 16-day NDVI and EVI data were converted to a monthly scale and synchronized with the AOD data. Then, monthly anomalies of AOD, NDVI, and EVI were calculated to remove the effect of the seasonal cycle. Severe dust events were identified using percentile-based statistical thresholds; the 75th percentile was calculated as 0.296, and the 90th percentile as 0.360. Months with AOD values equal to or greater than the 90th percentile were selected as severe dust events. Subsequently, the relationship between dust and vegetation indices was examined using Pearson correlation, linear regression, seasonal analysis, month-by-month analysis, lag-correlation analysis, and event-based analysis.
Results and Discussion
The results showed that dust AOD in Khuzestan Province experienced considerable temporal fluctuations during the study period. In total, 70 months were above the 75th percentile and 29 months were above the 90th percentile, indicating the occurrence of relatively severe and severe dust events. The relative synchronization between variations in dust AOD and total AOD showed that dust constitutes an important part of the aerosol burden over the region.
The analysis of NDVI and EVI anomalies indicated that vegetation health changed noticeably during the study period, and both indices showed similar behavior in many periods. In the first step, the relationship between raw AOD and vegetation index anomalies was negative but weak; the correlation coefficient between raw AOD and NDVI anomaly was -0.144, while that between raw AOD and EVI anomaly was -0.132. This weak relationship is probably due to strong seasonal cycles and the simultaneous influence of climatic and agricultural factors.
After removing seasonal effects, the strength of the relationship increased. The correlation coefficients between AOD anomaly and NDVI and EVI anomalies were -0.307 and -0.281, respectively, and both relationships were statistically significant. This result indicates that abnormal increases in dust are generally associated with a relative decline in vegetation health. Seasonal analysis also showed that this relationship was stronger in spring; the correlations between AOD anomaly and NDVI and EVI during this season were -0.388 and -0.346, respectively. This may be related to active plant growth and the greater sensitivity of agricultural crops during this period.
Lag analysis showed that the effect of dust was not limited to the month of occurrence and continued for several months afterward. The strongest negative correlation was observed in the same month as the dust event; however, negative relationships remained at one-month, two-month, and three-month lags. In addition, event-based analysis showed that after severe dust events, the mean anomalies of NDVI and EVI decreased further in the following months. This may indicate the cumulative effect of dust, reduced photosynthetic capacity, decreased surface moisture, or the coincidence of dust events with climatic stresses.
Conclusion
The results of this study showed that there is a negative, significant, and complex relationship between dust events and vegetation health in Khuzestan Province. The use of AOD anomalies provided a more accurate representation of the effect of dust on vegetation compared with raw AOD values. The findings indicate that abnormal increases in dust, particularly in spring and in some sensitive months, are associated with relative decreases in NDVI and EVI. However, vegetation health is not affected by dust alone, and factors such as precipitation, temperature, soil moisture, irrigation, crop type, planting time, and agricultural management also play important roles. Therefore, for a more accurate interpretation of this relationship, the integration of remote sensing data with climatic, hydrological, and field data is recommended.

Abstract Reference evapotranspiration (ETo) constitutes a fundamental component in water resource management and irrigation scheduling, playing an important role in agricultural planning, hydrological modeling, and climate change impact assessment. Accurate estimation of ETo primarily depends upon the availability of comprehensive meteorological parameters, including maximum and minimum temperature, relative humidity, wind speed, and solar radiation, which are required for the implementation of the FAO-56 Penman-Monteith method, the internationally recognized standard for ETo calculation. However, ground-based meteorological data often encounter significant limitations in many regions due to sparse and heterogeneously distributed station networks, high maintenance costs, and limited accessibility, particularly in developing countries and areas with complex topography. These constraints lead to considerable uncertainty in ETo estimation and consequently create difficulties in sustainable water resource management, irrigation scheduling, and crop water requirement assessment. In response to these challenges, remote sensing technology has emerged as a promising alternative, offering spatially continuous, temporally consistent, and cost-effective data coverage at regional and global scales.
This study was conducted with the primary objective of assessing the feasibility of replacing ground-based meteorological data with remote sensing parameters for daily ETo estimation using the FAO-56 Penman-Monteith method. The research employed data from 15 weather stations in East Azerbaijan Province in northwestern Iran, covering the period from 2000 to 2023. This region was selected due to its semi-arid to cold semi-arid climate, significant topographical heterogeneity ranging from approximately 700 meters to over 1800 meters above sea level, and its agricultural importance, making it an ideal testbed for evaluating the potential of remote sensing data in complex environmental conditions. The ground-based meteorological data, obtained from the Islamic Republic of Iran Meteorological Organization (IRIMO), included daily maximum temperature (Tmax), minimum temperature (Tmin), mean relative humidity (RH), wind speed at 2-meter height (Ws), incoming solar radiation (Rs), and extraterrestrial radiation (Ra). These data were complemented by MODIS satellite products, including land surface temperature (LST) from both daytime and nighttime observations, solar radiation (DSR), albedo, Normalized Difference Vegetation Index (NDVI), and solar zenith angle (SZA), as well as soil moisture data obtained from the GLDAS satellite product, all extracted through the Google Earth Engine platform.
Four machine learning models were developed and evaluated with six distinct input scenarios, ranging from minimal ground-based variables to a full combination of satellite and ground-based data. The models included Gaussian Process Regression (GPR), a Bayesian non-parametric method capable of estimating prediction uncertainty; LightGBM, an efficient gradient boosting decision tree algorithm suitable for large-scale regression problems; Temporal Convolutional Network (TCN), a deep learning architecture based on causal and dilated convolutions with residual connections; and a hybrid TCN-GRU architecture designed to combine the multi-scale feature extraction capabilities of TCN with the long-term dependency modeling strengths of Gated Recurrent Units (GRU). The input scenarios were carefully designed to evaluate the incremental contribution of different data sources: IC1 used only ground-based variables (Tmax, Tmin, RH); IC2 and IC3 employed limited satellite variables; IC4 incorporated complete satellite-derived variables; IC5 combined complete satellite data with Tmax and RH; and IC6 combined satellite data with Tmin and Ws.
The results demonstrated that the TCN-GRU model provided the most accurate performance under the hybrid scenario IC5, which incorporated all satellite-derived variables alongside maximum temperature and relative humidity. This configuration yielded a coefficient of determination (NSE) of 0.975, a mean absolute error (MAE) of 0.29 mm/day, and a normalized root-mean-square error (NRMSE) of 7.6%, indicating excellent agreement between estimated and observed ETo values. In contrast, the exclusively satellite-based scenarios (IC2–IC4) exhibited a substantial decline in estimation accuracy, with the TCN-GRU model achieving NSE values below 0.79 in IC2 and NRMSE values exceeding 10.6% even in the most comprehensive satellite-only scenario (IC4), highlighting the inherent limitations of remote sensing data when used in isolation for ETo estimation.
The Diebold–Mariano test confirmed that the superiority of the TCN-GRU model over GPR and LightGBM was statistically significant across all scenarios at the 0.01 significance level, while its advantage over the standalone TCN was only significant under the IC5 scenario at the 0.05 level. This finding underscores the value of the hybrid architecture in effectively modeling temporal dependencies and spatial patterns in ETo estimation. Pearson correlation analysis further revealed that maximum temperature (r = 0.93) and solar radiation (r = 0.91) showed the strongest positive correlations with ETo, which is consistent with the physical principles of evapotranspiration, where temperature and energy availability are primary driving factors. Conversely, solar zenith angle (r = -0.88) and relative humidity (r = -0.73) showed the strongest negative correlations with ETo, indicating their role as limiting factors through their influence on atmospheric demand and energy receipt at the surface.
Overall, although remote sensing data cannot fully substitute for ground-based meteorological measurements, their integration with a minimal set of ground variables, specifically maximum temperature and relative humidity, can yield acceptable accuracy (NRMSE < 8%) for operational applications. The proposed TCN-GRU model, with its hybrid convolutional-recurrent architecture, effectively captures both short-term and long-term dependencies in meteorological time series and is recommended as an efficient tool for ETo estimation in regions with limited ground-based data availability.

Abstract Phosphorus (P) deficiency is a major limitation in agricultural soils worldwide, particularly in calcareous soils where phosphorus availability is inherently low due to fixation by calcium compounds. Phosphorus is an essential macronutrient for plants, playing critical roles in energy transfer, photosynthesis, and metabolic processes. Insufficient phosphorus not only reduces crop yield but also affects plant quality and overall ecosystem sustainability. Traditional phosphorus fertilizers, such as triple superphosphate (TSP) and monoammonium phosphate (MAP), are often applied in high doses to compensate for low availability, which can lead to environmental concerns, including phosphorus runoff and eutrophication of water bodies. In recent years, biochar-based fertilizers have emerged as a promising approach to improve soil fertility, enhance nutrient retention, and increase crop nutrient use efficiency. Biochars derived from different feedstocks and produced at varying pyrolysis temperatures possess distinct physicochemical properties that influence nutrient adsorption, soil microbial activity, and plant growth. Moreover, enriching biochar with iron oxide can further improve phosphorus availability by reducing phosphorus fixation and providing a slow-release nutrient source. Despite these advances, the combined effect of phosphorus-enriched biochar and iron oxide on crop growth, nutrient use efficiency, and chlorophyll content remains insufficiently studied. Therefore, this study aimed to evaluate the effects of phosphorus-based biochar-iron oxide composites on the growth performance and phosphorus use efficiency in corn (Zea mays L.) under controlled greenhouse conditions.
Materials and Methods
A greenhouse experiment was conducted using a factorial design based on a completely randomized layout with three replications. Treatments included a control (without biochar and iron oxide), two types of biochar produced from wheat straw and walnut shell at two pyrolysis temperatures (350°C and 650°C), a single iron source (Fe(NO3)3), and two phosphorus levels (0 and 20% by weight) applied as TSP or MAP. Corn plants were cultivated under controlled environmental conditions, and soil moisture, temperature, and light were monitored throughout the 21-day incubation period. Plant growth parameters were measured, including fresh and dry biomass of aerial parts, plant height, and leaf area. Chlorophyll content was determined using a SPAD meter. Phosphorus use efficiency was estimated by comparing biomass production relative to the phosphorus applied. Statistical analyses were performed to evaluate the effects of biochar type, pyrolysis temperature, phosphorus source, and iron oxide enrichment on growth parameters. The interactions between these factors were also examined to understand the synergistic effects on corn performance.
Results and Discussion
The results indicated that phosphorus addition significantly enhanced corn growth and chlorophyll content compared to the control treatment without phosphorus. Among biochar treatments, wheat straw biochar produced at 350°C in combination with 20 mg phosphorus (MAP or TSP) resulted in the highest vegetative growth and biomass of aerial parts, while walnut shell biochar at 650°C and the control treatment exhibited the lowest performance. The inclusion of iron oxide in biochar further improved biomass accumulation. For example, wheat straw and walnut shell biochars produced at 350°C increased fresh and dry biomass of aerial parts by 18.6% (2.18%) and 7.9% (9.17%), respectively, relative to the non-biochar control. At 650°C, only wheat straw biochar showed a significant increase in aerial biomass.
These findings suggest that both biochar feedstock and pyrolysis temperature are critical factors influencing the effectiveness of phosphorus-enriched biochar as a slow-release fertilizer. The results also indicated that the type of phosphorus fertilizer (MAP vs. TSP) had no significant effect on growth performance, emphasizing the importance of biochar-mediated phosphorus delivery rather than the source itself. Moreover, the positive impact on chlorophyll content implies that biochar-based phosphorus composites can improve photosynthetic efficiency and overall plant health. These outcomes highlight the potential of using phosphorus-iron oxide biochar composites as a sustainable strategy for enhancing nutrient use efficiency in crops while minimizing environmental impacts.
Conclusion
In summary, this study demonstrates that phosphorus-based biochar-iron oxide composites can serve as effective slow-release fertilizers, improving phosphorus availability, crop growth, and nutrient use efficiency. Wheat straw biochar produced at lower pyrolysis temperatures (350°C) was particularly effective in promoting vegetative growth, whereas the feedstock type and pyrolysis temperature were more influential than the phosphorus source itself. The application of these composites could contribute to sustainable agricultural practices by reducing reliance on conventional phosphorus fertilizers, mitigating environmental risks, and supporting crop productivity in phosphorus-deficient soils. Future studies are recommended to evaluate long-term field applications and interactions with soil microbial communities to further optimize biochar-based phosphorus management strategies.

Abstract Introduction
The increasing use of fungicides and antibiotics in agricultural systems has raised concerns regarding their unintended effects on soil biological processes. Benomyl, a benzimidazole fungicide, and tetracycline, a broad-spectrum antibiotic, are frequently introduced into soil through plant protection practices and the application of animal manures. Once in soil, these compounds may alter microbial growth, metabolic activity, and enzyme-mediated nutrient cycling, thereby affecting essential soil functions.
Soil microorganisms are central to soil fertility and ecosystem functioning, and parameters such as microbial respiration, microbial biomass, and enzyme activities are widely used as sensitive indicators of soil disturbance. The simultaneous presence of fungicides and antibiotics may result in interactive effects that differ from those observed for individual compounds, potentially intensifying or prolonging biological stress.
Soil organic matter, particularly humic substances, plays a critical role in regulating the fate and bioavailability of organic contaminants. Humic acid can reduce the toxicity of pesticides and antibiotics through adsorption and complexation, while simultaneously improving physicochemical conditions that support microbial activity. Despite this, information on the combined effects of benomyl and tetracycline on soil microbial activity in the presence of humic acid, and their temporal dynamics, remains limited.
The objective of this study was therefore to assess the individual and combined effects of benomyl and tetracycline on soil microbial respiration, enzyme activities, and microbial biomass carbon, with particular emphasis on the moderating role of humic acid and time-dependent microbial responses.
Materials and Methods
A laboratory incubation experiment was conducted using a soil classified as Typic Haplocambids. The experiment followed a completely randomized design with eight treatments: control (C), benomyl (F), tetracycline (T), benomyl + tetracycline (FT), humic acid (H), benomyl + humic acid (FH), tetracycline + humic acid (TH), and benomyl + tetracycline + humic acid (FTH).
Benomyl and tetracycline were applied at rates of 12 and 50 mg kg⁻¹ soil, respectively, and humic acid was added at 500 mg kg⁻¹ soil. Soil moisture content was adjusted to 60% of water-holding capacity, and samples were incubated at 25 °C for 30 days. Destructive sampling was performed after 1, 7, and 30 days of incubation.
Microbial activity was assessed using substrate-induced respiration with glucose and cellulose as carbon substrates. Microbial biomass carbon (MBC) was determined using the fumigation–extraction method. Enzyme activities, including dehydrogenase, acid phosphomonoesterase (ACP), and alkaline phosphomonoesterase (ALP), were measured using standard colorimetric assays. Data were analyzed by analysis of variance (ANOVA), and treatment means were compared using Tukey’s test at a significance level of P < 0.01.
Results and Discussion
Application of benomyl and tetracycline significantly affected soil microbial activity, with the strongest inhibitory effects observed under their combined application (FT). Substrate-induced respiration with glucose was reduced in soils treated with benomyl and tetracycline during the early incubation period, while the FT treatment consistently exhibited the lowest CO₂ production across all sampling times, indicating a pronounced suppressive effect on microbial metabolic activity.
Respiration responses to cellulose were lower than those observed for glucose, suggesting greater resistance of complex carbon decomposition processes to chemical disturbance. Nevertheless, cellulose-induced respiration was persistently reduced in the FT treatment throughout the incubation period, reflecting impaired hydrolytic capacity of the microbial community.
Microbial biomass carbon declined markedly in treatments without humic acid, particularly in the FT treatment, on day 1 of incubation. Although partial recovery of MBC was observed by day 30, biomass levels in the FT treatment remained significantly lower than in the control, indicating incomplete microbial adaptation.
Dehydrogenase activity exhibited a transient increase in some benomyl-treated soils, especially in the presence of humic acid (FH), followed by a gradual decline over time. This pattern reflects an initial stress-induced stimulation followed by metabolic inhibition. In contrast, humic acid–amended soils generally maintained higher and more stable dehydrogenase activity throughout the incubation period.
Alkaline phosphatase activity showed an inducible response, particularly in the FH and TH treatments during the early stages of incubation, likely reflecting increased phosphorus demand under chemical stress. Acid phosphatase activity responded more variably depending on treatment and incubation time. In soils amended with humic acid, temporal fluctuations in enzyme activities were reduced, indicating enhanced functional stability; however, the inhibitory effect of tetracycline remained evident in the TH treatment.
Conclusion
Benomyl and tetracycline, particularly when applied simultaneously, exerted inhibitory effects on soil microbial respiration, biomass, and enzyme activities. The presence of humic acid mitigated these negative effects by enhancing microbial stability and reducing biological stress over time. Although partial microbial adaptation occurred during the incubation period, the combined fungicide–antibiotic treatment caused persistent disturbances in soil microbial functioning. Overall, humic acid contributes to improved biological stability of soil exposed to bioactive contaminants and represents a potential management strategy for mitigating chemical stress.

Abstract Introduction
Conservation agriculture is widely promoted as a strategy for improving soil structure and water-use efficiency in degraded cropping systems. In northern Iran, intensive conventional tillage combined with crop-residue removal has contributed to structural degradation and reduced soil water storage. Assessing how no-tillage and reduced-tillage systems affect the soil water retention curve (SWRC), pore-size distribution (PSD), and soil physical quality can support sustainable soil management. Therefore, this study evaluated the effects of conventional tillage, reduced tillage, and no-tillage on soil water retention, pore-size distribution, functional pore classes, and physical quality in agricultural soils of Bandar-e Gaz County, Golestan Province, Iran.
Materials and Methods
The study was conducted in agricultural lands of Bandar-e Gaz County in northern Iran. Three management systems representing different levels of soil disturbance were evaluated: conventional tillage, reduced tillage (semi-conservation), and no-tillage (conservation agriculture). Soil was sampled at depths of 0–15, 15–30, and 30–45 cm.
The experiment was arranged as a split-plot based on a randomized complete block design with three replications. Tillage management systems were assigned to the main plots and soil depths to the subplots. Disturbed and undisturbed soil samples were collected after crop harvest and analyzed for pH, electrical conductivity (EC), organic matter (OM), bulk density, total porosity, and mean weight diameter of soil aggregates (MWD) using standard procedures.
Soil water retention was determined at absolute matric potentials of 0, 300, 500, 1000, 2000, and 15000 cm of water column. FC and PWP were obtained directly from the measured water contents at 300 and 15000 cm, respectively, and AW was calculated as their difference. The measured retention data were fitted with the van Genuchten model using RETC software. Pore-size distribution was derived from the fitted curves, and pores were classified by size and function. Functional classes included transmission pores (> 50 μm), storage pores (0.5–50 μm), and residual pores (< 0.5 μm). The soil physical quality index (S-index) was calculated from the slope of the fitted retention curve at its inflection point. Statistical analyses were conducted using SAS. Effects were evaluated at the 1% and 5% probability levels, and means were compared using the LSD test at the 5% level.
Results and Discussion
Tillage management significantly affected organic matter content, EC, MWD, FC, AW, pore-size distribution, and functional pore classes. In contrast, soil pH, bulk density, and total porosity were not significantly affected, indicating that changes in pore organization and function were more important than changes in total pore volume.
Reduced tillage produced the highest organic matter content in the upper soil layers and increased MWD relative to conventional tillage. These results suggest that reduced soil disturbance combined with residue retention promoted aggregate formation and structural stability.
The SWRCs clearly differentiated the management systems. At 0–15 and 15–30 cm, reduced tillage generally retained more water across a wide range of matric suctions, whereas conventional tillage showed the lowest retention capacity. At 30–45 cm, no-tillage exhibited the highest water retention. These shifts reflected changes in soil structure and in the proportion of water-retaining pores.
FC and AW followed similar patterns. Their highest values in the upper layers occurred under reduced tillage, reaching 0.1776 and 0.1390 cm³ cm⁻³, respectively, whereas conventional tillage generally produced the lowest values. At 30–45 cm, no-tillage had the greatest FC and AW, indicating improved water storage associated with reduced disturbance and greater pore continuity. PWP was not significantly affected by tillage management, soil depth, or their interaction.
Pore-size distribution differed significantly among management × depth combinations. Conservation-oriented systems increased the proportion of pores within the water-retention domain, particularly medium-sized pores. At 0–15 cm, reduced tillage had the greatest proportion of storage pores, approximately 69%, whereas conventional tillage had the greatest proportion of transmission pores, approximately 57%. The larger storage-pore fraction under reduced tillage was consistent with its higher FC and AW. Overall, the agreement among water-retention characteristics, pore-size distribution, and functional pore classes indicates that management-induced improvements in hydraulic behavior were mainly governed by changes in pore organization and functionality rather than by total porosity.

A close agreement was observed among soil water retention characteristics, pore-size distribution, and functional pore classes. This consistency suggests that management-induced improvements in soil hydraulic properties were primarily governed by modifications in pore organization and functionality rather than changes in total porosity. The results therefore highlight the importance of evaluating pore quality in addition to pore quantity when assessing soil physical condition.
The S-index ranged from approximately 0.012 to 0.027 and remained below the critical threshold of 0.035 proposed by Dexter (2004) for desirable soil physical quality. The effects of tillage management, soil depth, and their interaction on the S-index were not statistically significant. Thus, the observed numerical trends should not be interpreted as evidence of the superiority of any management system. The persistence of low S-index values suggests that four years of conservation management was insufficient to produce a statistically detectable improvement in this integrated physical-quality indicator, even though several water-retention and pore-function characteristics responded significantly.
Conclusion
Conservation-oriented management improved soil hydraulic behavior primarily by modifying pore organization, pore-size distribution, and water-retention capacity. Reduced tillage provided the most favorable conditions in the surface and subsurface layers by increasing OM, MWD, storage-pore proportion, FC, and AW. At the deepest layer, no-tillage showed greater water retention, FC, and AW, indicating that some benefits of conservation management may become more evident with depth and time.
The results further showed that soil-quality responses were more strongly associated with pore functionality than with total porosity or bulk density. Although several hydraulic properties improved, S-index values remained below the optimum threshold and did not differ significantly among treatments. Longer implementation of conservation agriculture, together with residue retention and strategies that increase organic matter, may therefore be required to achieve measurable improvements in overall soil physical quality and long-term agricultural sustainability.

Abstract Introduction
Lake desiccation is a major environmental concern in arid and semi-arid regions. The exposed lakebeds resulting from this process can become important sources of wind-blown dust and may facilitate the transport of heavy metals (HMs) to surrounding ecosystems. Previous studies have largely focused on determining HM concentrations in soils, sediments, and airborne dust, whereas less attention has been paid to quantifying HM transport by wind erosion from dried lakebeds. Since the amount of HMs transported depends on both their concentrations in sediment and the quantity of sediment mobilized by wind, HM flux provides a more comprehensive measure of their potential transport. Therefore, this study aimed to assess the potential for HM transport from the dried lakebeds of Kaftar, Tashk, and Parishan in Fars Province, southern Iran, by determining HM concentrations, enrichment ratios (ERs), and HM fluxes using a portable wind tunnel.

Materials and Methods
Three dried lakebeds, including Kaftar, Tashk, and Parishan, in Fars Province, southern Iran, were selected as representative dust-source areas. At each lakebed, three independent wind-tunnel experiments were conducted at separate locations on surfaces without crusts to account for spatial heterogeneity. A surface soil sample (0–5 cm) was collected from each experimental location. Some physical and chemical properties of the soil samples, including soil texture, pH, electrical conductivity (EC), and organic carbon content, were determined using standard laboratory procedures.
Wind erosion experiments were performed using a portable wind tunnel at a constant wind velocity of 14 m s⁻¹, measured at a height of 0.25 m above the soil surface, for 10 min. After each experiment, wind-eroded sediments were collected, and the mean weight diameter (MWD) of both lakebed soils and transported sediments was determined. Concentrations of nickel (Ni), lead (Pb), and cadmium (Cd) in the soil and wind-eroded sediment samples were measured by atomic absorption spectrophotometry following aqua regia digestion. Sediment fluxes, HM fluxes, and ERs were then calculated.
Statistical analyses included one-way ANOVA followed by Duncan’s multiple range test to compare variables among lakebeds, paired t-tests for Cd, and Wilcoxon signed-rank tests for Ni and Pb to compare lakebed soils with wind-eroded sediments. Linear regression was used to examine relationships between HM concentrations in lakebed soils and wind-eroded sediments. All analyses were performed using IBM SPSS Statistics 27, with statistical significance set at P < 0.05.

Results and Discussion
The results revealed considerable differences among the three dried lakebeds in terms of wind erosion rate and HM transport potential. Sediment fluxes in Kaftar (1.64 g m⁻² s⁻¹) and Tashk (1.56 g m⁻² s⁻¹) were significantly higher than that in Parishan (0.86 g m⁻² s⁻¹), with no significant difference between Kaftar and Tashk. In both lakebed soils and wind-eroded sediments, HM concentrations followed the order Ni > Pb > Cd. Although the mean weight diameter (MWD) of wind-eroded sediments was lower than that of the corresponding lakebed soils, enrichment ratios (ERs) for all three elements were below unity (ER < 1), indicating lower HM concentrations in wind-eroded sediments than in lakebed soils. The relative patterns of ER values varied among elements and lakebeds. Cadmium consistently exhibited higher ER values than Pb (0.49–0.53 vs. 0.24–0.26), whereas Ni had the highest ER in Kaftar (0.65) and Parishan (0.56). In Tashk, however, where the Ni concentration in lakebed soils was substantially lower than in the other lakebeds, the Ni ER decreased to 0.30, falling below that of Cd (0.53). These patterns suggest that the relative enrichment of HMs in wind-eroded sediments varies among elements and lakebeds and may reflect differences in their geochemical characteristics and interactions with soil particles. Strong positive linear relationships were observed between HM concentrations in lakebed soils and wind-eroded sediments for Ni (R² = 0.98), Pb (R² = 0.94), and Cd (R² = 0.87). High R² values indicate that HM concentrations in lakebed soils largely explained their concentrations in wind-eroded sediments.
Heavy metal fluxes exhibited patterns different from those of sediment fluxes. Ni, Pb, and Cd fluxes ranged from 0.22 to 3.82, 0.07 to 0.23, and 0.05 to 0.11 mg m⁻² min⁻¹, respectively. Although sediment fluxes were statistically similar between Kaftar and Tashk, Ni and Pb fluxes were significantly higher in Kaftar, whereas Cd flux reached its highest value in Tashk. These findings demonstrate that HM transport depends on both the amount of sediment transported and the metal concentrations within the transported sediments, highlighting the importance of considering both factors simultaneously when assessing HM transport.

Conclusion
The dried lakebeds of Parishan, Kaftar, and Tashk can act as potential sources of Ni, Pb, and Cd through wind erosion, although transport patterns differed among elements and lakebeds. The lower MWD of wind-eroded sediments and ER values below unity indicated that sediment transport did not result in relative HM enrichment. HM flux, integrating sediment flux and HM concentration, provided a comprehensive measure of HM transport and can help prioritize lakebeds for dust monitoring. These findings are limited to surfaces without crusts and should be further evaluated under a wider range of wind velocities in future studies.