Environmental Earth Sciences最新文献

Groundwater constitutes approximately 30% of the world’s freshwater, making it an essential natural resource for all living beings. However, unplanned usage has resulted in the depletion of groundwater levels, necessitating sustainable management practices. Traditional field mapping of groundwater availability (GWA) is expensive and time-intensive, posing challenges to its effective management. This study proposes a simple methodology to predict the future groundwater availability using remote sensing and Geographical Information Systems (GIS) tools. Ten thematic layers depicting various basin characteristics including annual average rainfall for the year 2012 to 2021 were used to predict groundwater availability zones map for the year 2022 in the Beas river basin. Relative influence of each layer was computed using analytical hierarchy process with consistency ratio below 0.1. The results showed comprehensible dependence of groundwater availability over rainfall, being the prime source of groundwater recharge. The predicted GWA map showed higher groundwater availability in the western part of the basin due to higher rainfall, porous lithology, mild slope, lower drainage density and curvature as compared to the eastern part which consisted of the lower Himalayan region. The results were validated based on actual groundwater data yielding fairly accurate predictions with only 3 out of 35 stations not agreeing to the prediction. The predicted groundwater availability zones map outlines the areas with readily available groundwater in future and recommends the areas for groundwater recharge optimizing water management, aiding in drought preparedness, resource allocation, infrastructure planning, and environmental protection, ensuring sustainable usage and resilience to climate change.

The inverse grading characteristics of granular deposits are commonly observed in landslide dams, influencing the behavior of these deposits. However, the effects of water on this characteristic remain unclear. This study conducted a series of experiments to investigate how water impacts the morphology and particle sorting within granular deposits. Numerical simulations using coupling CFD (Computational Fluid Dynamics) with DEM (Discrete Element Method) were performed to quantitatively analyze the inverse grading characteristics in the deposits and to explore the mechanisms behind these characteristics. The results indicate that the presence of water affects both the morphology and the inverse grading characteristics of the granular deposit due to water-particle interactions. The inverse grading characteristic of the deposit weakens as the water level increases, due to the resistance exerted on the particle motion by the water force. The sliding length of the granular flow also affects the particle sorting by altering the particle velocity upon entering the water, although this effect is less significant than that of the water level. The degree of inverse grading within the deposits can be characterized using the coefficient of variation of particle centroids. This coefficient of variation is mainly affected by the water level, which can decrease from 0.24 to 0.03 as the water level increases from 0 to 23 times the mean particle size. Finally, a model was developed to predict the inverse grading of underwater deposits through multi-parameter regression, considering factors such as water depth, sliding length, and particle size.

The broader region of the Czech Republic in Central Europe experiences moderate seismicity. However, determination of seismic hazard is significant due to its dense population, large cities, and developed industrial infrastructure, including nuclear power plants. A new catalogue of historical earthquakes has been compiled for the Czech Republic and its surrounding areas, covering the period up to the end of 2023. The catalogue was analysed in terms of seismicity variations over the last 164 years (1860–2023). It was shown, that there was a significant increase in seismicity from 1896 to 1910 compared to the present state, in most of the source zones, which are important for the seismic hazard of the region. Significant earthquakes from this period are well documented in historical records, and some also by old seismograms, making it certain that similar strong earthquakes did not occur in later years until now. A strong correlation has been shown with earthquakes in Italy, a highly seismically active area on the margin of the Eurasian tectonic plate, which is more than 200 km away from the study region. However, the physical cause of this variation in seismicity in both regions is unclear. The demonstrated variation in seismicity has essential implications for the methodology of seismic hazard evaluation.

The focus of this study is on investigating the available water resources and the existing challenges to mitigate freshwater supply shortages in Gambella Town, Harari Region, and Shinile Woreda by using the principles of Integrated Water Resources Management (IWRM). The study examined water demand, financial constraints, existing infrastructure capacities, and available water resources focusing on rainwater harvesting (RWH) potential analyses using the existing information from literatures. Results reveal heterogeneous water availability among the study areas. Gambella Town exhibits a yearly water demand estimated at approximately 6.32 million cubic metres (MCM), while available resources from surface water, groundwater, and RWH potential are estimated at 7,674.6 MCM, 0.3 MCM, and 2.73 MCM, respectively. Conversely, the Harari Region displays an imbalance, with a total demand of approximately 16.83 MCM, surpassing available water resources. There is no identified surface and groundwater resource in this region. However, the rainwater potential in the area is calculated to be 6.36 MCM. In Shinile Woreda, the overall water demand is approximately 10.6 MCM, with available resources from groundwater, and rainwater harvesting estimated at 0.9 MCM, and 2.22 MCM, respectively. These findings underscore the urgent necessity for implementing comprehensive water management strategies, guided by the IWRM approach, to ensure sustainable resolutions for freshwater challenges in the study areas.

This study conducted a physical experiment and numerical simulations to investigate the evolution of stress, pore pressure and activation characteristics of concealed faults with two-layer confined aquifers underlying coal floor during mining. The physical experimental results show that the increment change rate of pore pressure lags behind the change in stress, and the change degree of stress and pore pressure increments in the shallow fault zone is higher than that of the deep fault zone. The water inrush risk of shallow fault zone is higher than that of the deep fault zone. Numerical simulation results show that the degree of stress disturbance decreases with the increase of depth, and the activation of the deep fault zone lags behind the shallow part. The distribution of pore pressure in various locations indicates varying degrees of activation in the fault zone. Mining disturbance can generate hydraulic connections between shallow and deep aquifers, and concealed faults can facilitate the recharge of shallow confined aquifer through deep confined aquifer. It is crucial to avoid or mitigate disturbance to the deep fault zone. The results can provide theoretical and practical reference for the analysis of concealed faults’ activation characteristics under the condition of multiple confined aquifers underlying coal floor.

The Regional Plan of Mining Activities (PRAE), adopted in December 2022, represents the strategic regulation instrument pursuing the balance between environmental sustainability and economic development produced by mining activity at a regional scale. The paper proposes an overview of the main regional in-force instrument for surface and ground-water planning and management (PAI and PTA) and how these intersect with the introduced PRAE. Besides, the interaction between mining activities and the geomorphological and hydrogeological contexts in which they are located is described, defining the resulting constraints regarding their interaction with extraction areas. A significant portion of the quarries are located in the floodplain, falling both in river bands of medium–high probability of flooding and in areas involving aquifers bodies, hence these extractive sites are heavily restricted both in terms of excavation depths, never exceeding the base of the surface aquifer. The depth of the water table and the base of the aquifer represent the two fundamental parameters on which new restrictions have been defined in the PRAE in terms of the possibility of developing new quarry areas.

Different modes of disasters will occur in the process of tunnel construction in thin-layered rock mass. The key to tunnel safety control is to analyze the main control factors affecting the failure mode of thin-layered rock mass tunnel and predict the potential failure mode. The failure characteristics of thin-layered rock mass were analyzed and classified based on 22 tunnel projects. In addition, the influence factors of different failure modes are quantitatively analyzed. Taking the influencing factors as the prediction index, combined with the actual case, the initial database is constructed. The Fisher-Freeman-Halton exact test method was used to calculate the main control factors of the failure mode. The initial database samples were pretreated by augmentation and CRITIC method weighting, and the failure mode prediction model of thin-layered rock mass tunnel was established by random forest. The evaluation metrics and validation index of the model is tested by practical engineering case, and the results are compared with RF, AdaBoost and SVM algorithms. The findings show that the failure modes of thin-layered rock mass tunnel can be divided into four types, including squeeze bending failure, buckling bending failure, along-layer slip failure, and falling block failure. The angle between the maximum stress and the rock strata and the degree of joint development are the main control factors affecting the failure mode. The accuracy, precision, recall and F1-Score of the CRITIC-RF are 81.8%, 81.7%, 80.2%, 0.809, and higher than AdaBoost and SVM. The Oob-Score of the CRITIC-RF is 0.824 and higher than RF. The reliability of the prediction results of the prediction model is ensured. The research results can provide the basis and reference for the failure mode prediction and active control of thin-layered rock mass tunnel. The research results can provide scientific basis for the prediction and precise control of engineering disasters in thin-layered rock masses.

As Earth science transitions into the era of big data, artificial intelligence (AI) not only holds significant potential for addressing geoscience challenges, but also plays a pivotal role in accelerating our comprehension of the complex, interactive, and multi-scale processes of Earth's behaviors. As geoscience AI models are progressively utilized for significant predictions in crucial situations, geoscience researchers are increasingly demanding their interpretability and versatility. This study proposes an interpretable geoscience artificial intelligence (XGeoS-AI) framework to unravel the mystery of image recognition in the Earth sciences, and its effectiveness and versatility are exemplified through the application to computed tomography (CT) image analysis. To enhance interpretability, the XGeoS-AI framework incorporates a local region threshold generation method (LRT) inspired by human visual mechanisms. Different kinds of artificial intelligence (AI) engines, including support vector regression (SVR), multilayer perceptron (MLP), convolutional neural network (CNN), are integrated within the XGeoS-AI framework to efficiently address geoscience image recognition challenges. Experimental findings affirm the effectiveness, versatility, and heuristics of the XGeoS-AI framework, underscoring its potential to revolutionize geoscience image recognition. Interpretable AI should receive more and more attention in the field of the Earth sciences, which is the key to promoting more rational and wider applications of AI in the field of Earth sciences.

The karst area in general has very specific characteristics, such as a thin layer of soil on the surface and a very uneven distribution, as well as a multitude of interconnected cracks that enable rapid infiltration of water underground. Because of this, groundwater in weathered carbonate rocks requires a very precise approach in management and protection. In the Republic of Croatia, almost half of the country’s territory is built of karstified carbonate rocks, in which there are significant amounts of water supplies. In addition, karst aquifers show a high degree of vulnerability to pollution from any human activity that threatens them. For this reason, it is important to carry out a complex analysis of the natural features of the aquifer system and its reaction to anthropogenic action, in order to determine the level of natural protection that the aquifer has. This is exactly what is shown in detail through the analysis of intrinsic vulnerability, which has become an indispensable tool in the research of karst water resources. Old abandoned industrial waste landfills represent problematic sites of potential hazard for groundwater as well as surface water contamination. There are several such locations in the karst area of the Republic of Croatia, three of them are presented in this paper: location Štrmac, Plomin in Istria peninsula, Plaški in Lika region and Jadral in North Dalmatia. The purpose of this work is to assess the levels of groundwater intrinsic vulnerability with the mobility of certain potentially toxic elements in soils formed at industrial waste disposal sites. By combining geochemical modelling and groundwater vulnerability assessment, an attempt was made to understand the movement of contaminants and their chemical behaviour in different environmental conditions. This helps in predicting whether certain metals might leach into the groundwater and in what form they are likely to be present, which has direct implications for water quality and human health.

This paper investigates the energy evolution and damage mechanical properties of layered rock at medium and high strain rates. Firstly, the dynamic compression experimental results of four types of rock samples were carefully analyzed to reveal the energy evolution mechanism of the layered rock. Then, a damage variable of the layered rock was defined based on the basic principle of energy dissipation. Finally, a damage constitutive model was proposed by combining the damage variable with different stage characteristics. The results show that the energy evolution mechanisms of different layered rocks are almost similar and the corresponding curves can be roughly divided into four stages. As the inclination angle of bedding plane increases, the energy storage limit develops in a “V” shape. The initial damage and the whole damage process of the layered rock can be characterized by the defined damage variable. The proposed damage constitutive model can well describe the nonlinear behaviors of the layered rock in the compaction stage and the post-peak failure process. The relevant parameters have clear physical meanings and are easily obtained from experimental data. This study can provide a theoretical guidance for the safety and stability analysis of underground rock mass engineering under dynamic disturbance.