Search

In this study, the ANSYS 2020R1 software simulation is employed to examine the diffusion process of oil leakage and the underground water solute transport law in the Dashagou Yellow River crossing section of the oil pipeline. The simulation results demonstrate that under identical leakage pressure conditions, diesel fuel leakage in powdery, sandy soil is diminished, the emergency window is extended, and the corresponding leakage risk is reduced. In addition, the leakage rate of crude oil is slower than that of diesel oil. After 850 days of downward migration of approximately 190 m, the pollutant reaches quasi-static equilibrium in the big sand ditch. The results of the surface water oil spill analysis demonstrated that the oil film on the river surface migrated for 100 min after the spill, with a thickness that remained between 0.02 and 0.05 mm and a concentration that approached equilibrium. [ABSTRACT FROM AUTHOR]

Light non-aqueous phase liquids (LNAPLs), which include various petroleum products, are a significant source of groundwater contamination globally. Once introduced into the subsurface, these contaminants tend to accumulate in the vadose zone, causing chronic soil and water pollution. The vadose zone often contains lens-shaped bodies with diverse properties that can significantly influence the migration and distribution of LNAPLs. Understanding the interaction between LNAPLs and these lens-shaped bodies is crucial for developing effective environmental management and remediation strategies. Prior research has primarily focused on LNAPL behavior in homogeneous media, with less emphasis on the impact of heterogeneous conditions introduced by lens-shaped bodies. To investigate the impact of lens-shaped structures on the migration of LNAPLs and to assess the specific effects of different types of lens-shaped structures on the distribution characteristics of LNAPL migration, this study simulates the LNAPL leakage process using an indoor two-dimensional sandbox. Three distinct test groups were conducted: one with no lens-shaped aquifer, one with a low-permeability lens, and one with a high-permeability lens. This study employs a combination of oil front curve mapping and high-density resistivity imaging techniques to systematically evaluate how the presence of lens-shaped structures affects the migration behavior, distribution patterns, and corresponding resistivity anomalies of LNAPLs. The results indicate that the migration rate and distribution characteristics of LNAPLs are influenced by the presence of a lens in the gas band of the envelope. The maximum vertical migration distances of the LNAPL are as follows: high-permeability lens (45 cm), no lens-shaped aquifer (40 cm), and low-permeability lens (35 cm). Horizontally, the maximum migration distances of the LNAPL to the upper part of the lens body decreases in the order of low-permeability lens, high-permeability lens, and no lens-shaped aquifer. The low-permeability lens impedes the vertical migration of the LNAPL, significantly affecting its migration path. It creates a flow around effect, hindering the downward migration of the LNAPL. In contrast, the high-permeability lens has a weaker retention effect and creates preferential flow paths, promoting the downward migration of the LNAPL. Under conditions with no lens-shaped aquifer and a high-permeability lens, the region of positive resistivity change rate is symmetrical around the axis where the injection point is located. Future research should explore the impact of various LNAPL types, lens geometries, and water table fluctuations on migration patterns. Incorporating numerical simulations could provide deeper insights into the mechanisms controlling LNAPL migration in heterogeneous subsurface environments. [ABSTRACT FROM AUTHOR]

Contamination from light nonaqueous phase fluids (LNAPLs) and their derivatives during mining, production, and transportation has become a concern. Scholars have extensively studied LNAPL contamination, but the role of water content variation on its migration process in the unsaturated zone has not been sufficiently researched. The specific issue addressed in this study is the impact of water content on the migration of light nonaqueous phase liquids (LNAPLs) in sandy soils, a critical yet under-researched aspect of subsurface contamination. To tackle this, we employed indoor simulated vertical, one-dimensional, multiphase flow soil column experiments, utilizing the orthogonal experimental method to systematically evaluate the effects of varying water contents on the occurrence state and migration rate of LNAPLs. The experimental results indicate the following: (1) The migration rate of LNAPL exhibits an L-shaped trend during subsurface imbibition and a nonlinear relationship with migration time. The migration rate and migration time of surface infiltration have a linear growth relationship. (2) The residual rate of LNAPL is negatively correlated with water content and positively correlated with oil content in the homogeneous non-saturated state. With the increase in the amount of leaked oil, 40% of the leaked LNAPL is sorbed within the soil. (3) When the water content of the test medium is below 14%, and the oil content is below 11%, LNAPL appears in the unsaturated zone in a solid phase. As the water content increases, the adsorption rate of the oil phase gradually decreases and eventually reaches the oil saturation point. (4) When the water content of the medium exceeds 8%, over time, LNAPL will be subject to oil–water interfacial tension, and the rate of LNAPL movement first decreases and then increases, displaying nonlinear growth. The innovation of this work lies in the comprehensive analysis of LNAPL migration under controlled laboratory conditions, providing results that enhance the understanding of LNAPL behavior in sandy soils. These quantitative insights are crucial for developing targeted remediation strategies for LNAPL-induced pollution in the unsaturated zone. [ABSTRACT FROM AUTHOR]

Utilizing the monthly monitoring data of water quality indexes in the Guohe River Basin from 2005 to 2018 (a total of 168 months),this paper explores the application of wavelet analysis and neural network in the water quality research of the river basin.Wavelet analysis is employed to clarify the multi-scale change rules of water quality indexes in the Guohe River Basin.The main influencing factors of water quality are selected by principal component analysis,and a wavelet neural network model is established to predict the main influencing factors.The results show that each water quality index presents multi-scale oscillation,and there are three main change periods of about 8 months,20 months,and 30 months. At present,the main factor affecting the water quality of the Guohe River Basin is the pollution factor represented by chemical oxygen demand.The curve fitting is good between the chemical oxygen demand predicted by the wavelet neural network and the measured values with the mean relative error (MRE) and root mean square error (RMSE) of 8.4% and 1.5,respectively.This indicates the good stability and high prediction precision of the model.The application of wavelet neural networks provides a new idea for the study of water pollution in river basins.

Evapotranspiration (ET) is a critical component of the hydrological cycle, and it has a decisive impact on the ecosystem balance in arid and semi-arid regions. The Yinchuan Plain, located in the Gobi of Northwest China, has a strong surface ET, which has a significant impact on the regional water resource cycle. However, there is a current lack of high-resolution evapotranspiration datasets and a substantial amount of time is required for long-time series remote sensing evapotranspiration estimation. In order to assess the ET pattern in this region, we obtained the actual ET (ETa) of the Yinchuan Plain between 1987 and 2020 using the Google Earth Engine (GEE) platform. Specifically, we used Landsat TM+/OLI remote sensing imagery and the GEE Surface Energy Balance Model (geeSEBAL) to analyze the spatial distribution pattern of ET over different seasons. We then reproduced the interannual variation in ET from 1987 to 2020, and statistically analyzed the distribution patterns and contributions of ET with regard to different land use types. The results show that (1) the daily ETa of the Yinchuan Plain is the highest in the central lake wetland area in spring, with a maximum value of 4.32 mm day−1; in summer, it is concentrated around the croplands and water bodies, with a maximum value of 6.90 mm day−1; in autumn and winter, it is mainly concentrated around the water bodies and impervious areas, with maximum values of 3.93 and 1.56 mm day−1, respectively. (2) From 1987 to 2020, the ET of the Yinchuan Plain showed an obvious upward and downward trend in some areas with significant land use changes, but the overall ET of the region remained relatively stable without dramatic fluctuations. (3) The ETa values for different land use types in the Yinchuan Plain region are ranked as follows: water body > cultivated land > impervious > grassland > bare land. Our results showed that geeSEBAL is highly applicable in the Yinchuan Plain area. It allows for the accurate and detailed inversion of ET and has great potential for evaluating long-term ET in data-scarce areas due to its low meteorological sensitivity, which facilitates the study of the regional hydrological cycle and water governance. [ABSTRACT FROM AUTHOR]

In the Yinchuan Plain, the main source of water supply for agricultural crops is irrigation infiltration. Therefore, the irrigation process, method, and time are crucial for the rational planning and utilization of water resources in the region. In this study, the effects of different irrigation methods on groundwater recharge were investigated through irrigation quadrat tests combined with numerical simulations. The water content at depths of 10–50 cm had a more significant response to irrigation than that at 80 and 100 cm in the intelligent irrigation quadrat. The water content change at depths of 10–50 cm was smaller than that at 80 and 100 cm in the flood irrigation quadrat. The flood irrigation method had a greater impact on the water content in the deep vadose zone. The water content of intelligent irrigation was concentrated at depths of 30–50 cm, with weak groundwater recharge. The water content of the flood irrigation quadrat was concentrated at depths of 50–80 cm, with a significant impact in the vertical direction. The simulation results indicated that flood irrigation had the best effect on groundwater recharge, with an infiltration recharge coefficient of 0.73, compared to intelligent irrigation, which had an infiltration recharge coefficient of 0.41. When the groundwater depth range was 0.65–3.8 m, the infiltration recharge efficiencies of intelligent and flood irrigation were the highest at groundwater depths of 1.3 and 1.8 m. Our findings provide a scientific basis for methods of rational irrigation, which could help save water resources in the study area. [ABSTRACT FROM AUTHOR]