JWSS - Journal of Water and Soil Science

The growing concern for environmental protection and increasing demand for green approaches to address environmental problems have prompted researchers to explore a sustainable and reliable method for treating dyeing wastewater. One of the sustainable and reliable methods is the electrocoagulation process. In this study, a batch electrocoagulation reactor was designed to evaluate the efficiency of this process in treating dyeing wastewater. The effects of two parameters, electrode distance and retention time, on pollutant removal efficiency were investigated. Electrode distances of 2, 5, and 7 cm were tested, and retention times of 10, 15, 20, 25, and 30 minutes were examined. Results indicated that the optimal electrode distance was 5 cm and the optimal retention time was 20 minutes. Under these conditions, the removal efficiency of BOD, COD, TSS, color, and turbidity reached 83%, 85%, 98%, 98%, and 93%, respectively. The results of this research demonstrate the significant potential of the electrocoagulation system for treating dyeing wastewater.

Soil loss and extensive degradation caused by gully erosion have always caused serious damage. Because direct field measurement and monitoring of gully erosion are costly and time-consuming, it is very difficult to determine the amount of soil loss caused by gully erosion. The present research was conducted to calculate the volume of soil loss due to gully erosion using machine learning models in the Abgendi watershed of Kohgiluyeh and Boyar Ahmad province based on field studies. Machine learning models include random forest, support vector machine, artificial neural network, and adaptive neural fuzzy inference system. The location of 68 gullies in the area was recorded. Hence, initially, digital layers of factors affecting the expansion of gullies, including topography, pedology, lithology, and hydrology, were prepared as independent variables to model soil loss caused by gullies. Then, representative gullies were selected in the studied watershed, and the volume of soil loss due to gully erosion was directly measured in the field as a dependent variable. The measured gullies were randomly divided into two training and validation groups. The results of the models were evaluated using root mean square error (RMSE) and R2, and the models were compared. According to the results, gully erosion in the Abgendi watershed of Kohgiluyeh and Boyar Ahmad province is increasing every year. Also, the amount of erosion and soil loss will increase when the amount of rainfall and the frequency of intense rainfall (≥5mm) are high. Among the machine learning models used in the present research, the random forest (RF) model was selected as the best model to predict soil loss generated by gully erosion.

By utilizing land surface temperature (LST), valuable insights can be gained regarding the impact of land use on energy balance processes. Therefore, this study aimed to investigate the trend of LST changes due to land use changes in the Gorab rural district. Four land use types, including water bodies, bare land, Agricultural area, and forest, were determined from 2013 to 2024 for the maximum likelihood classification (MLC) and support vector machine (SVM) models. The surveys showed that the area of water in the dry period decreased from 0.9 km2 in 2013 to 0.4 km2 in 2024, a decrease of 0.5 km2. In contrast, the area of forest areas increased from 136.1 km2 in the dry period of 2013 to 147.2 km2 in 2024. The Kappa coefficient values for the SVM and MLC models during the wet season of 2021 were 53.94 and 68.7, respectively. Based on this, it was found that the MLC model has higher accuracy. To match spectral indices with LST values, NDVI, NDSI, and NDWI were calculated. Land use changes during the 2013-2024 period affected land surface temperatures, causing fluctuations from 11.5°C to 21.18°C in the wet season and from 13.81°C to 31.45°C in the dry season. The highest LST values were associated with barren land, while water bodies and vegetation cover had the lowest LST values. Among the spectral indices, the highest positive correlation was observed with NDWI, with a value of 0.64 in 2024. The highest negative correlation, -0.66, was observed with NDVI in the same year. Over the 11 years, the area of forest cover increased by 8.15%, while agricultural land decreased by 33.5%. The most significant change occurred in agricultural lands, which declined in area from 35.5 km² to 23.6 km².

One of the most significant hydraulic issues in determining the opening of river bridges is the lack of flow choking due to a reduction in the width of the flood passage. In this paper, determining the required opening for flow passage at a bridge location has been investigated using the concept of specific energy, one-dimensional, and three-dimensional flow modeling. First, the maximum encroachment of the embankments on the sides of the bridge in the river has been determined in such a way that it does not change the flow situation upstream of the bridge, using the concept of specific energy. The dimensions obtained for the bridge opening have been simulated numerically in two one-dimensional and three-dimensional models, and the flow condition at the bridge site and upstream has been evaluated and compared. The results showed that the one-dimensional numerical model predicts, on average, 67 percent higher amount of afflux than the three-dimensional model, while the maximum shear stress obtained from the one-dimensional model is, on average, 33 percent lower than that of the three-dimensional model. The effect of the bridge skewness on the amount of afflux and other hydraulic parameters of the flow, including bed shear stress and maximum velocity, has also been investigated using a three-dimensional model. The afflux was obtained at a 19.2 percent of normal depth at a skew of 40 degrees.

Improvement of soil characteristics is one of the important issues in agricultural and engineering sciences. To investigate the effect of silica nanoparticles on the soil's mechanical and physical properties, a factorial experiment was conducted based on a completely randomized design with three replications. The factors included silica nanoparticles at three levels (0%, 0.5%, and 1% by weight) and two soil types with loam and clay loam textures. The results of the shear strength test showed that the addition of nanosilica increased the internal friction angle and particle adhesion in both loam and clay loam textures, but the liquid limit and plasticity index decreased in both soils. In the consolidation test, the compressibility coefficient in loam decreased from 0.38 to 0.21 and in clay loam from 0.42 to 0.23, while the swelling coefficient in loam decreased from 0.13 to 0.07 and in clay loam from 0.18 to 0.08. Overall, the results showed a significant effect of nanosilica particles on improving soil mechanical strength, especially in clay loam with higher clay content and specific surface area. Therefore, it can be concluded that the use of silica nanoparticles is an effective method for stabilizing problematic soils.
 

This study aimed to evaluate the effectiveness of iron (Fe) aminochelate application methods on Fe chemical speciation in the soil solution, as well as Fe concentration and uptake in sunflower seeds (Helianthus annuus L. cv. Oscar). The experiment was conducted in a randomized complete block design with three replications at the research field of Shahid Chamran University of Ahvaz. Treatments included two application methods (seed priming and fertigation) and three Fe sources: Fe–glycine aminochelate [Fe(Gly)₂], Fe–methionine aminochelate [Fe(Met)₂], and ferrous sulfate (FeSO₄·7H₂O), along with an unfertilized control. Fe speciation was determined using Visual MINTEQ software. Results indicated that Fe aminochelates, [Fe(Met)₂], significantly decreased soil pH and increased DTPA-extractable Fe (by 35.7%), seed Fe concentration (by 13.5%), and seed Fe uptake (by 79.1%) compared with the control (p < 0.01). Application of Fe fertilizers also significantly enhanced the concentrations of dominant Fe species (Fe²⁺ and FeSO₄(aq)) in the soil solution, with the highest Fe²⁺ level (3.1-fold higher than the control) observed under [Fe(Met)₂] seed priming. Strong and significant positive correlations between Fe²⁺ and FeSO₄(aq) concentrations and both DTPA-extractable Fe (r = 0.88** and r = 0.89**, respectively) and seed Fe uptake (r = 0.84** and r = 0.87**, respectively) highlight the pivotal role of these species in improving Fe bioavailability and uptake by plants in calcareous soils.

Soil contamination by metals is a major problem in terrestrial ecosystems, particularly in and around industrial areas, and can pose a threat to human health in various ways. Therefore, in the present study, the bioaccumulation of heavy metals in the earthworm (Eisenia fetida) in soil around the Abik Cement Factory in Alborz Province was evaluated. Sixty soil samples were collected at depths of 0-20 cm at distances of 500, 1000, and 2000, in the directions of north, south, east, and west. Earthworm samples were also randomly collected from these distances and directions. The wet digestion method was employed to determine heavy metal concentrations in soil and earthworms, and Zn, Cu, Pb, Cr, and Ni were measured using an atomic absorption spectrometer. One- way ANOVA and Kruskal- Wallis statistical methods were used to examine the effects of distance and direction. The bioaccumulation factor (BAF) was used to evaluate the ability of earthworms as a biological indicator. According to the results, the average concentrations of heavy metals in the soil around the lands of the Abik Cement Factory for Cr, Pb, Cu, Zn, and Ni were 22. 20, 10. 19, 6. 34, 7. 63, and 135. 75 (mg/kg), respectively. The average concentrations of heavy metals in earthworms in this region for Cr, Pb, Cu, Zn, and Ni were 51.57. 57, 9. 66, 5. 18, 5. 45, and 106. 17 (mg/kg), respectively. The results indicated that the distance effect was significant only for Ni (p< 0. 05), and the direction effect was significant for all heavy metals except Zn (p> 0. 05). A decreasing trend in the concentrations of Cu, Zn, and Pb was observed with increasing distance from the cement factory, indicating the impact of the Abik Cement Factory on heavy metal pollution in the agricultural soil of the surrounding lands. The highest bioaccumulation factor (BAF) was calculated for zinc and was greater than 1, indicating bioaccumulation of Zn in earthworms. It can be concluded that earthworms can be used as a suitable biological indicator species for monitoring soil contamination with heavy metals, especially for Zn.

This study aimed to optimize the site selection of artificial groundwater recharge zones in the Yazd-Ardakan watershed (covering an area of 116,765 hectares) to address challenges such as water scarcity, severe groundwater depletion, and annual rainfall below 100 mm. The research integrated Geographic Information Systems (GIS) and Multi-Criteria Decision-Making (MCDM) methods. Seventeen influential criteria, including elevation, slope, land use, geology, soil type, climate, distance from faults, and isothermal lines were analyzed using ArcGIS 10.5. Criteria weighting was performed using the Best-Worst Method (BWM), and layer integration was achieved through the Weighted Linear Combination (WLC) approach. Results indicated that slope (weight: 0.203), elevation (correlation >0.75), and land use (correlation ≈0.5) had the highest impact on zone suitability, while climate and isothermal lines were less influential. The final suitability map (900×900 m resolution) revealed that central and southern plain areas with slopes <2%, permeable alluvial formations, flat topography, and optimal distance from faults were prioritized for artificial recharge. Sensitivity analysis identified eight key criteria (correlation >0.5), and by eliminating 53% of non-essential parameters, an efficient framework for sustainable water resource management was established. This study not only contributes to raising groundwater levels, improving soil fertility, and preserving local ecosystems but also offers a practical solution for water crisis management in arid regions. 
 

Precipitation use efficiency (PUE) is defined as crop yield per unit of annual precipitation in a region. Proper management of rainfed lands requires investigation of the spatial variation of PUE. In this study, two hundred ninety-eight rainfed lands were investigated in the Khodabandeh region in the south of Zanjan province. PUE was calculated as the ratio of wheat grain yield to precipitation. In addition, climatic characteristics and soil physical properties (particle size distribution and water retention) were measured, along with soil chemical properties (pH, EC, organic matter, calcium carbonate, and macro- and micronutrients) in rainfed soils. Results indicated that the mean PUE in rainfed lands is 4.43 kg mm-1. Higher values were found in the northeast, south, and west regions of the area, although these parts had lower wheat grain yields. Geostatistical analysis showed moderate spatial variation in wheat grain yield and PUE, with patterns associated with climatic variables (precipitation and temperature) and land conditions such as soil properties (particle size distribution, organic matter, and nitrogen). Rainfed lands with fine-textured soils and higher amounts of organic matter and nitrogen had higher PUE. Adjusting tillage direction and using conservation tillage are important strategies to improve organic matter content and soil productivity in rainfed lands.

Accurate monitoring of water surface dynamics in semi-arid regions poses challenges due to uncertainties regarding the optimal spectral index and sensor selection for effective water resource management. This study assessed the comparative performance of nine spectral water indices across the Landsat-8 and Sentinel-2 platforms to identify the best index-sensor combinations for monitoring semi-arid reservoirs. Utilizing the Google Earth Engine cloud computing platform, 181 satellite images were processed for Golestan Dam in northeastern Iran, comprising 107 Landsat-8 scenes from 2013 to 2023 and 74 Sentinel-2 scenes from 2018 to 2024. After applying atmospheric corrections using the LEDAPS and Sen2Cor algorithms, nine spectral indices (NDWI, MNDWI, ANDWI, AWEI, WI2015, WI1, WI2, LSWI, and NDTI) were calculated and evaluated against the WI2 reference through RMSE, R², and Nash-Sutcliffe efficiency metrics. MNDWI showed superior performance for Sentinel-2 (RMSE=21.42 ha, R²=0.998, NS=0.996), while ANDWI was optimal for Landsat-8 (RMSE=54.54 ha, R²=0.977, NS=0.976). Time-series analysis revealed a 35% reduction in mean annual reservoir area, decreasing from 7.28 km² in 2014 to 4.72 km² in 2021. Consistent seasonal patterns were observed, with spring maxima (9.33 km² in March) and autumn minima (3.35 km² in September) evident across both sensors. A high inter-sensor correlation (r = 0.933) supports the potential for multi-sensor integration in comprehensive monitoring efforts. The LSWI and NDTI indices displayed systematic overestimation due to interference from soil moisture and vegetation, making them unsuitable for quantifying water area. These findings highlight the sensor-dependent nature of optimal index selection, recommending MNDWI-Sentinel-2 pairing for short-term monitoring and ANDWI-Landsat-8 for long-term trend analysis in the management of semi-arid reservoirs.

Biochar, a stable, economical, and environmentally friendly carbonaceous material, has garnered significant attention in the development of advanced adsorbents for the immobilization and removal of environmental pollutants from water and soil. This interest stems from its oxygen-containing functional groups, aromatic structure, notable porosity, high specific surface area, and suitable cation exchange capacity. However, the performance limitations of pristine biochar in pollutant removal underscore the necessity for its modification and engineering. In this regard, the production of biochar composites through the combination with minerals and iron-containing compounds has emerged as an effective strategy to enhance structural and chemical properties, as well as surface reactivity. This review paper examines the primary methods for synthesizing biochar composites, including post-pyrolysis modification and direct mixing with mineral phases. Synergistic and direct loading methods are introduced as novel approaches. Furthermore, the influence of biomass type, pyrolysis conditions, modifier type, and synthesis pathway on the final physicochemical characteristics of the composites is analyzed. Additionally, the governing mechanisms underlying the performance of these materials in immobilizing and removing heavy metals are discussed, encompassing adsorption, precipitation, complexation, ligand exchange, redox reactions, electron transfer, electrostatic interactions, and ion exchange. Study results indicate that the synergy between biochar and mineral/iron-bearing phases can significantly enhance the efficiency of immobilizing pollutants, including both anionic and cationic heavy metals. This review emphasizes the importance of targeted design of biochar composites based on a precise understanding of the relationship between synthesis methods and functional properties. Future challenges and prospects concerning the application of biochar-mineral composites in environmental remediation and the promising commercialization of this technology are also addressed.

Excessive groundwater abstraction is a major environmental and economic challenge in Iran’s arid and semi-arid regions. This study examined farmers’ perceptions of groundwater over-abstraction and its perceived socioeconomic consequences in the Siminehroud catchment. Data from 373 questionnaires were analyzed using descriptive statistics, Mann–Whitney U tests, and chi-square tests. Effect sizes were reported, and p-values were adjusted using the Benjamini–Hochberg procedure. Overall, 41.8% of respondents believed that groundwater over-abstraction was occurring in their locality. Respondents with this perception were younger (median 48.5 versus 53 years; p<0.001), and the proportion with this perception was lower among users of piped water conveyance than among users of traditional canals (24.2% versus 45.6%; p=0.001). Both associations remained significant after false-discovery-rate adjustment. The most frequently perceived consequences of groundwater-level decline were declining farm income, loss of irrigated land, changes in cropping patterns, and increased migration. The findings indicate that groundwater management in Siminehroud should incorporate aquifer monitoring, improved water conveyance, and social interventions tailored to users’ characteristics.
 

This study evaluated groundwater-level variations in the Isfahan-Borkhar aquifer and examined their relationship to land subsidence. Representative hydrographs, groundwater-level maps, depth-distribution maps for the wettest and driest months of the study period, and a 20-year groundwater-level variation map were prepared and compared with the land subsidence map within the aquifer area. The results indicated that subsidence zones were mainly located in areas experiencing considerable groundwater-level decline. The occurrence of critical subsidence zones in regions with a high density of pumping wells and agricultural lands further confirmed this relationship. In addition, the alluvial-thickness map of the study area was prepared and compared with the land subsidence map to investigate the relationship between the spatial distribution of subsidence zones and alluvial thickness. The findings indicated that land subsidence is associated not only with groundwater-level decline but also with other factors, including alluvial thickness and soil texture. In other words, even under substantial groundwater-level decline, significant land subsidence is unlikely where alluvial thickness and the proportion of compressible fine-grained sediments are low.

 

Nickel (Ni) is an essential element for living organisms and plays important biological roles in plants; however, its accumulation at high concentrations can cause toxicity and adverse effects. This study aimed to evaluate nickel accumulation using the leaves of Albizia lebbeck, Prosopis cineraria, and Eucalyptus globulus as biological indicators in Ahvaz City during the summer of 2025. A total of 126 leaf samples and 63 soil samples were collected from seven stations across Ahvaz City. Chemical digestion of the leaf and soil samples was performed using the Johnson and EPA 3050 methods, respectively. Nickel concentrations were determined using atomic absorption spectrometry. Significant differences were observed in Ni concentrations among the leaves of Albizia lebbeck, Prosopis cineraria, and Eucalyptus globulus (P < 0.05), whereas no significant difference was observed in Ni concentrations among the soil samples (P > 0.05). The highest and lowest Ni concentrations in the unwashed and washed leaves of Albizia lebbeck were 36.2 and 10.3 mg kg⁻¹, respectively. The highest and lowest Ni concentrations in the soil samples collected from the tree rhizospheres were 57.36 and 44.1 mg kg⁻¹, respectively. The highest Ni transfer factor was observed in Albizia lebbeck leaves (0.446), whereas the lowest was observed in Eucalyptus globulus leaves (0.203). The Ni transfer factors for the leaves of Albizia lebbeck, Prosopis cineraria, and Eucalyptus globulus, together with the linear regression analysis of Ni concentrations in washed and unwashed leaves, indicate that atmospheric deposition may be an important source of Ni accumulation in the leaves. In contrast, the contribution of soil-derived Ni to leaf accumulation appears to be relatively low.

This research was conducted with the aim of site selection and land capability evaluation for the development of pistachio cultivation in Sistan and Baluchestan province by integrating Geographic Information Systems (GIS), the Analytical Hierarchy Process (AHP), and remote sensing data (Landsat 8 satellite imagery within the Google Earth Engine platform). Eight criteria, including distance from water canals, roads, and population centers, land use, slope, elevation, slope aspect, and soil characteristics (salinity, texture, and pH), were weighted based on the opinions of 15 experts (inconsistency ratio = 0.03). The highest weights were assigned to distance from water canals (0.32), soil characteristics (0.25), and distance from roads (0.14). Information layers with a spatial resolution of 30 m were prepared in the GIS environment and integrated using the weighted overlay method. The final map showed that 13.8 percent of the province is in the highly suitable class, 23.0 percent in the moderately suitable class, 33.5 percent in the marginally suitable class, 27.5 percent in the unsuitable class, and 2.2 percent has absolute limitations. The findings indicated that 36.8 percent of the province has significant potential for the development of pistachio cultivation; however, the main limitation is access to water resources. 65.5 percent of the province is located in the unsuitable category in terms of distance from water canals. Therefore, the sustainable development of pistachio cultivation in the province requires precise planning with a focus on suitable areas and the sustainable management of water resources. The novelty of this research lies in applying Boolean masks to eliminate ecological errors and using cloud computing (GEE) for the temporal consistency of data. Furthermore, comparative analysis revealed that crop development in some areas (such as Zahedan) relies more on groundwater extraction than on inherent land potential; the model classifies these areas as "unsuitable," providing a preventive warning regarding long-term sustainability

The Helmand River is the main source of water for the Sistan Plain and underpins the provision of key ecosystem services, including water supply, agricultural production, forage provision, soil protection, and wildlife habitat. The operation of the Kamal Khan Dam and the diversion of river flow toward Goud-e Zereh have reduced downstream water availability and accelerated land degradation in Sistan. This study aimed to assess land-use and land-cover changes associated with Helmand River water availability before and after the operation of the dam. Land-use/land-cover maps for 2019, 2020, 2024, 2025, and 2026 were produced using Landsat imagery, supervised classification, and the Random Forest algorithm, and their accuracy was evaluated using field-based reference samples. The results showed that, after dam operation, the Hamoun-e Hirmand water body completely dried up, whereas the water-covered area around Kamal Khan Dam and in the Goud-e Zereh region increased from 3,039 ha in 2019 to 62,794 ha in 2026. In the Sistan Plain, agricultural land reached its maximum extent of 69,025 ha in 2020 but declined to 5,776 ha in 2025. In addition, the area of saline lands in the Sistan Plain and Hamoun increased from a minimum of 110,414 ha in 2020 to a maximum of 274,708 ha in 2026. These changes were accompanied by a reduction in rangelands, an expansion of barren lands, increased soil salinity, and greater soil susceptibility to wind erosion. The findings indicate that the diversion of water toward Goud-e Zereh, together with associated declines in agricultural land, rangelands, and soil moisture and the expansion of saline and barren lands, has weakened the ecosystem services provided by the Helmand River.
 

Managed Aquifer Recharge (MAR) using treated wastewater is a viable strategy for water-resource sustainability in arid regions; however, the simultaneous assessment of its hydrogeological and economic aspects remains challenging. The objective of this study was to hydro-economically evaluate the implementation of an MAR project in the Qotb-Abad Plain by integrating numerical modeling and cost-benefit analysis (CBA). The quantitative and qualitative responses of the aquifer were simulated using the MODFLOW and MT3DMS models to estimate changes in groundwater levels, nitrate concentrations, and total dissolved solids (TDS). Economic benefits, including pumping energy savings, the value of stored water, and improvements in water quality, were evaluated alongside capital and operational costs under lower- and upper-bound scenarios. Subsequently, economic indicators, including net present value (NPV), benefit-cost ratio (BCR), internal rate of return (IRR), and payback period, were calculated. The results indicated that implementing MAR with an annual treated wastewater volume of 1.898 million m³ resulted in an approximately 4.5 m rise in groundwater level, accompanied by reductions in TDS from 1859 to 1752 mg/L and in nitrate concentration from 22.2 to 15.4 mg/L by the end of the five-year simulation period. Under the upper-bound scenario, the NPV, BCR, and payback period were 43.7 billion Rials, 1.36, and 3.23 years, respectively. In contrast, the lower-bound scenario was not economically justified, as its BCR was less than 1. Overall, integrating numerical modeling with cost-benefit analysis provides a comprehensive framework for supporting groundwater-management decision-making.