JWSS - Journal of Water and Soil Science

Soil erosion and sediment transport are among the key challenges in the management of water and soil resources in Iran. In this study, the Modified PSIAC (MPSIAC) empirical model was applied to estimate sediment yield and evaluate the erosion status in the Plasjan watershed. The model is based on the assessment of nine influencing factors, including geological characteristics, soil properties, climatic conditions, runoff, land slope, vegetation cover, land use, surface erosion, and channel erosion. By assigning scores to each factor and integrating the spatial layers, the sediment yield intensity of each sub-watershed was quantified both qualitatively and quantitatively. The required base data were prepared and analyzed using the Geographic Information System (GIS). Subsequently, the final erosion index for each sub-watershed was calculated, and erosion hazard classes were determined according to the model’s standard tables. The total annual sediment production in the watershed was estimated at 803,301 tons, and the Sediment Delivery Ratio (SDR) was calculated as 14.48%, indicating considerable sediment deposition along the transport paths.  The results showed that most sub-watersheds fall within the “moderate” erosion class, while insufficient vegetation cover, steep slopes, and land-use changes were identified as the main contributing factors to increased sediment yield. Based on these findings, identifying critical areas, implementing erosion control measures, and utilizing remote sensing and sediment monitoring technologies are strongly recommended. This study provides a scientific basis for improving watershed management and mitigating erosion-related risks in similar basins.

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.
 

Soil, as one of the vital natural resources, plays a fundamental role in ecosystem sustainability and global food security; however, degradation caused by unsustainable management, intensive agriculture, and pollution threatens its capacity. The use of organic amendments such as hydrochar is considered an innovative approach to improve soil physicochemical properties and enhance the Soil Quality Index (SQI). This study aimed to investigate the effects of different levels of hydrochar on soil properties and evaluate SQI. The treatments included control and three hydrochar levels (H10, H20, and H50). Soil properties such as pH, porosity, bulk density, electrical conductivity, organic carbon, total nitrogen, and available phosphorus were measured and normalized, and parameter weighting was conducted using entropy and principal component analysis (PCA). Results showed that nitrogen and organic carbon had the greatest importance in soil quality. The H50 treatment recorded the highest SQI (0.815), significantly greater than other treatments, while H20 (0.546) and H10 (0.336) also showed positive effects compared to the control (0.159). Hydrochar application improved organic carbon, nitrogen, and phosphorus and reduced bulk density. Although an increase in electrical conductivity was observed in H50. Overall, hydrochar application had a positive and gradual effect on SQI, with H20 recommended as an optimal level to improve fertility and reduce long-term salinity risks.

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.

One of the key factors in agricultural production is the availability of sufficient and usable nutrients for plant growth, and among these, nitrogen plays a particularly important role. The waste of nitrogen fertilizers due to the low efficiency of using fertilizers has caused environmental problems such as pollution of surface and groundwater by nitrate or ammonium. In this study, the influence of fertigation as a combination of urea, ammonium nitrate, natural zeolite of Semnan (CP), and modified zeolite by surfactant (SMZ) in the reduction of waste and manure fertilizer was evaluated. Two separate experiments with a completely randomized design with three replications were used for loam soil columns. Treatments consisted of four levels of zeolite application (0, 4, 8, and 16 g/Kg) and a fertilization level with a concentration of 60 mg per liter nitrate applied at three fertigations during six irrigations. In the first part of the study, the role of nitrogen fertilizers in fertigation as a combination of urea and ammonium nitrate (UAN) for ordinary soil was examined to reduce the concentration of nitrate and ammonium in the drainage water, and the results were compared with one of the fertigation applications. The results showed that the loss of fertilizer in the form of nitrate was reduced by 40 percent for the UAN treatment during the first period of fertigation. Since the results of the first part of the experiment showed that the concentration of ammonium nitrate does not reduce to the same level as drinking water, in the second part of the experiment, the soil amendments were used. The measured nitrate removal showed that the highest nitrate removal belonged to the soil mixed with 16 g/kg of modified zeolite in the surface layer of soil (SM16) treatment, and it was equivalent to 90 percent. The highest ammonium removal belonged to the soil mixed with 16 g/kg of natural zeolite in the surface layer of soil (CP16) treatment, and it was 85 percent. Therefore, the use of fertigation as a combination of nitrogen fertilizers with soil amendments for conditions where there is a potential for groundwater pollution by nitrate leaching is recommended.

The steel industry plays an important role in the release of toxic pollutants, including heavy metals, into the environment. The present descriptive-applied study was conducted in 2022 to identify the sources of heavy metal emissions in surface soils in the vicinity of a steel industry using positive matrix factor and chemical mass balance models. Soil samples (50 samples) were systematically collected from four areas within the steel plant, and a control area of 15 km was established. Five main sources, including the earth's crust (factor 1), vehicles (factor 2), steel industry (factor 3), biomass (factor 4), and other sources (factor 5), were identified as the main factors of heavy metals in the positive matrix factor model. Cobalt, nickel, and zinc had the highest mean concentrations with values of 14.5, 1.21, and 0.92mg kg-1, respectively. Cadmium and Lead showed the lowest concentrations with values of 0.02 and 0.10 mg kg-1 in samples inside and outside the Khuzestan Steel Company area, respectively. Comparing the contribution of different sources in the release of heavy metals in the identified factors showed that the steel industry, other sources, earth's crust, vehicles, and biomass accounted for 24, 23, 19, 18, and 16 percent in the positive matrix factor model and 23, 22, 20, 18, and 17 percent in the chemical mass balance model, respectively. The positive matrix factor and chemical mass balance models showed that there was a high level of soil contamination with heavy metals in the vicinity of the Khuzestan Steel Company in Ahvaz city.

In many Iranian agricultural farms, center-pivot sprinkler irrigation is widely used as a modern irrigation method. However, improper design, installation, or operation of these systems can reduce their actual irrigation efficiency. Consequently, non-uniform water distribution along the lateral may occur, resulting in localized waterlogging or runoff. These conditions can adversely affect plant growth and alter nitrate distribution and salinity levels in the soil. Two existing center pivot irrigation systems were evaluated at the farm of Qiam Agricultural and Industrial Company in Isfahan. In this evaluation, the average indices of the Christian-Sen uniformity coefficient CU (C), the distribution uniformity coefficient DU, the Hayman and Hein uniformity coefficient CU (H), the potential efficiency of application in the lower quadrant PELQ, and the actual efficiency of application in the lower quadrant AELQ for the two irrigation machines were calculated to be 67%, 57%, 65%, 45%, and 54%, respectively. Comparison of the results with the acceptable ranges for these indices showed that the two systems did not achieve acceptable irrigation efficiency. The results of the study also showed that the volume of water discharged from the different spans varied, with the highest and lowest volumes of discharged water observed in the first and last spans, respectively. Therefore, due to the non-uniform distribution of water across the spans in the studied center-pivot irrigation system, soil samples were collected from beneath different spans to investigate residual soil nitrate concentrations, the salinity of the saturated soil extract, and rapeseed yield. A completely randomized block design was used to compare their means. The results showed that the first span with higher water intake had the highest canola dry weight (1.19 kg/m2), the lowest saturated soil extract salinity (1.67 dS/m), and the lowest residual nitrate in the soil (4.93 mg/kg). The last span with lower water intake had the lowest canola dry weight (0.44 kg/m2), the highest saturated soil extract salinity (3.33 dS/m), and the lowest residual nitrate in the soil (2.203 mg/kg). There was a significant difference at the 1% level between the parameters in different spans. Therefore, it is recommended to use accurate, real-time management tools suited to the crop and climatic conditions of the region to achieve more uniform crop performance across all spans of the center-pivot irrigation system.
 

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

Rainfall erosivity is a key factor in soil erosion models. Although Iran’s climate is predominantly hot and dry, the occurrence of intense and heavy rainfall events, although infrequent, can cause significant damage to soil resources. In the Universal Soil Loss Equation, rainfall erosivity is calculated based on rainfall intensity. In this study, 45 years of hourly rainfall data from the ERA5 reanalysis dataset were used to estimate rainfall erosivity across Iran. The results revealed that the spatial distribution of rainfall events in Iran is highly heterogeneous. Central Iran, with fewer than 20 rainfall events per year, and the Caspian Sea coast, with nearly 450 events per year, represent two contrasting rainfall regimes. Both the Caspian coast and the Zagros highlands receive slightly less than 10 mm of rainfall per event, while the mean duration of rainfall events in these regions is approximately 10 hours. On the Caspian coast, moisture originating from the Caspian Sea, and over the Zagros Mountains, moisture originating from the Arabian Sea, contribute to the observed rainfall duration and amount per event. Rainfall event intensity in the western Zagros and along the entire southern coast of Iran is considerably higher than in other parts of the country. The transport of moisture from the Arabian Sea into Iran contributes to the high intensity of rainfall events in these regions. Rainfall erosivity is very low across most parts of Iran; however, the Zagros Mountains, the Caspian coast, and some mountainous areas exhibit relatively high levels of erosivity. The mean annual rainfall erosivity over Iran is approximately 80  MJ.mm.ha^-1.h^-1.y^-1.