JWSS - Journal of Water and Soil Science

The rapid and complex movement of sediments in rivers and coastal areas with highly erosive and unsteady flows presents river engineers with numerous problems in the geomorphology of alluvial rivers. Accurately predicting these complex processes in the water-sediment system (a multiphase, dense, granular flow system) is still a major challenge for mesh-based models. Due to the ability of meshless Lagrangian methods to model large deformations and discontinuities, meshless Lagrangian methods can provide a unique way to deal with this complexity. In the current research, the capabilities of the weakly compressibility moving particle semi-implicit (WC-MPS) model in soil-fluid interaction modeling are developed to enable the modeling of sediment transport and erosion effects behind coastal walls. In this method, granular material is considered a non-Newtonian and viscoplastic fluid. The 𝜇(I) rheological model has been used to predict the non-Newtonian behavior of the granular phase. To verify the application of the present model in simulating the interaction of liquid and solid phases, first, the widely used problem of dam break on an erodible bed was modeled. The NRMSE model was calculated to be approximately 6%, which indicates the efficiency and accuracy of the target model in this problem. At the end, the scouring of coastal walls was simulated by the WC-MPS method using 𝜇(I) rheology model. Investigations show that the processes related to erosion and scouring can be well modeled using the current Lagrangian method. The numerical results show excellent agreement with the laboratory measurements. It should be noted that the mean error of the mentioned model is estimated to be 10%.

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.