Environmental Earth Sciences最新文献

{"title":"Effect of subsidence on the stability analysis of submarine slopes using the enhanced limit equilibrium method","authors":"Vinícius Oliveira Kühn,&nbsp;Bruno Leite Ramires Saldanha,&nbsp;Isabella Maria Martins De Souza,&nbsp;Ricardo Garske Borges,&nbsp;Manoel Porfírio Cordão-Neto","doi":"10.1007/s12665-025-12296-z","DOIUrl":"10.1007/s12665-025-12296-z","url":null,"abstract":"<div><p>Human activities in the subsea environment, particularly oil and gas extraction, rank among the most important economic activities in the modern world. However, this process can reactivate faults, causing subsidence, and consequently modifying the natural conditions of submarine slopes and their stability. Therefore, this paper aims to evaluate the effect of subsidence on the stability of submarine slopes under drained and undrained conditions. The Enhanced Limit Equilibrium Method (ELEM) was applied to slopes with steep angles and geotechnical parameters representative of subsea environments, considering subsidence with varying shapes and magnitudes. The results indicate that undrained conditions are the most critical due to the increase in pore pressure caused by subsidence and reduction in shear strength. Changes in the slope’s steep angles influence pre-subsidence stability and the evolution of post-subsidence Factor of Safety (FS) under undrained condition. Variations in subsidence levels and steep angles made it possible to determine the critical subsidence leading to slope failure under the initially defined geotechnical conditions. This study contributes to a better understanding of the impact of subsidence on the stability of submarine slopes and can guide future analyses, increasing safety for offshore structures.</p></div>","PeriodicalId":542,"journal":{"name":"Environmental Earth Sciences","volume":"84 12","pages":""},"PeriodicalIF":2.8,"publicationDate":"2025-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144140311","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Digital twin of underground research laboratory as a valuable instrument at early stages of a geological disposal programme","authors":"Valentina Svitelman,&nbsp;Alina Rukavichnikova,&nbsp;Dmitry Lunov,&nbsp;Konstantin Kazakov,&nbsp;Elena Saveleva","doi":"10.1007/s12665-025-12344-8","DOIUrl":"10.1007/s12665-025-12344-8","url":null,"abstract":"<div><p>Numerical simulation tools have been a core part of the safety assessment process for deep geological repositories of high-level radioactive waste from the start, and their crucial role is undeniable. However, the modern landscape of digital technologies is much broader than specialized numerical simulation software, and many such tools could also be of great help in various aspects of information management for geological disposal programmes. One of the most promising trends in the digitalization of high-tech and knowledge-intensive fields is digital twins of complex natural and/or industrial objects at different stages of their lifecycle. The development of digital twins is a complex approach that can employ a multitude of technologies depending on the features of the prototype object, available data, objectives, and technical capacities.</p><p>In this paper, we would like to assess both the opportunities associated with digital twins and the available tools for their development in the context of the digitalization of information management during the construction of the underground research laboratory and the safety assessment process of the future geological disposal repository. From a practical point of view, we aim to establish a reasonable approach for digital twin implementation at the early stages of a geological disposal programme, particularly for the underground research laboratory currently under construction at the Yeniseysky site (Krasnoyarsk region, Russia).</p></div>","PeriodicalId":542,"journal":{"name":"Environmental Earth Sciences","volume":"84 12","pages":""},"PeriodicalIF":2.8,"publicationDate":"2025-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144140315","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Estimation of groundwater recharge by chloride mass balance (CMB) method in some selected wadis, Western Saudi Arabia in (1966–2018)","authors":"Maged El Osta,&nbsp;Milad Masoud,&nbsp;Nassir Al-Amri,&nbsp;Abdulaziz Alqarawy,&nbsp;Riyadh Halawani,&nbsp;Mohamed Rashed","doi":"10.1007/s12665-025-12334-w","DOIUrl":"10.1007/s12665-025-12334-w","url":null,"abstract":"<div><p>Optimal management of groundwater requires conducting numerous studies and measurements to assess its sustainability, especially in arid regions like Kingdom of Saudi Arabia (KSA). The Quaternary aquifer, which serves as a vital source for drinking water, domestic needs, and irrigation in various wadis in Western Saudi Arabia (WSA), represents the most important renewable groundwater resource within the study area. Therefore, estimating the amount of recharging source to groundwater of this coastal aquifer is one of the most important parameters for predicting groundwater availability to support practical approaches for extraction. This research presents an application of the conventional chloride mass balance (CMB) approach for recharging estimation in three representative wadis in WSA, based on hydrological and hydrochemical characteristics. Results revealed that The Quaternary aquifer system exists under an unconfined condition at depth ranging from 1 m to 110 m in wadi Marawani, from 1.2 m to 100 m in wadi Fatimah and from 0.8 m to 21.7 m in wadi Qanunah, respectively. The estimated recharge to quaternary aquifer lies between 0.75% and 4.25% of effective annual rainfall over each basin. Qanunah basin in the south represents the highest recharging rate compared to wadi Marawani and Fatimah basins in the northwestern direction. These findings are in agreement with recharge rates of similar studies observed in different dry and semi-arid regions of the world such as Western United States Great basin.</p></div>","PeriodicalId":542,"journal":{"name":"Environmental Earth Sciences","volume":"84 12","pages":""},"PeriodicalIF":2.8,"publicationDate":"2025-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144140238","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Probabilistic prediction of rockburst hazard using Monte Carlo simulation and MAIRCA approach","authors":"Zheng Li,&nbsp;Weizhang Liang,&nbsp;Pengpeng Lu","doi":"10.1007/s12665-025-12290-5","DOIUrl":"10.1007/s12665-025-12290-5","url":null,"abstract":"<div><p>The prediction of rockburst hazard is of great significance for the safe exploitation of deep mineral resources. To predict the probability of rockburst hazard reliably, a methodology that integrated the Monte Carlo simulation (MCS) and Multi-Atributive Ideal-Real Comparative Analysis (MAIRCA) approach was proposed in this paper. First, considering the heterogeneity and anisotropy of rock mass, the uniform, normal and triangular distributions were adopted to describe initial indicator information by introducing an uncertainty coefficient. Then, the MCS was used to randomly generate indicator values based on the probability distributions. Subsequently, the maximum deviation method was used to calculate the indicator weights, which can avoid the influence of personal subjectivity. After that, the MAIRCA approach was adopted to determine the rockburst hazard level of each sample, and the probability of rockburst hazard was obtained according to the law of large numbers. Finally, the proposed methodology was applied to predict the rockburst hazard in the Sanshandao gold mine, Laizhou city, Shandong Province, China. In addition, the effectiveness was demonstrated through sensitivity and comparison analyses. Results indicate that the rockburst hazard level is consistent with field conditions, and the proposed methodology is reliable for the probabilistic prediction of rockburst hazard.</p></div>","PeriodicalId":542,"journal":{"name":"Environmental Earth Sciences","volume":"84 12","pages":""},"PeriodicalIF":2.8,"publicationDate":"2025-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144140312","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Landslide susceptibility mapping for western coastal districts of India using geospatial techniques and eXplainable artificial intelligence","authors":"Dikshita A. Shetkar,&nbsp;Bappa Das,&nbsp;Sujeet Desai,&nbsp;Gopal Mahajan,&nbsp;Parveen Kumar","doi":"10.1007/s12665-025-12343-9","DOIUrl":"10.1007/s12665-025-12343-9","url":null,"abstract":"<div><p>The west coast of India is more vulnerable to landslides due to high rainfall and hilly topography. To identify the landslide susceptible areas and the most important landslide triggering factor in the western coastal districts of India a landslide susceptibility mapping (LSM) was carried out using fourteen landslide triggering factors. LSM assists in identifying probable zones for future landslide occurrences within a given location by considering various landslide-triggering factors. For locating landslide-susceptible areas and to identify the best preforming model, a comparison between frequency ratio (FR), logistic regression (LR), machine learning (ML) models was performed. ML models used in this study were random forest (RF), support vector machine (SVM), extreme gradient boosting (XGB) and deep neural network (DNN). Most of the area was covered by very low class, i.e., 60.12% followed by low (13.50%), moderate (10.54%), high (8.04%) and very high (7.79%) classes, respectively. From the variable importance plots, it was found that factors such as slope, TRI, LS-factor, distance to road and rainfall were the most significant landslide-triggering factors. The results of the area under the ROC curve (AUC) revealed that the RF model achieved an excellent accuracy rate of 0.993 surpassing the other models. The ranking based on multiple model evaluation parameters using validation dataset revealed DNN as the best-performing model. The partial dependence plots (PDP) of the DNN model revealed that factors such as TRI, rainfall, slope, elevation and TWI were positively related to the landslide occurrences. It was concluded that the performance of ML models was excellent compared to the statistical model. The results of this study could help to identify landslide-vulnerable areas and adopt suitable preventive measures for mitigating the likely occurrence of future landslide events.</p></div>","PeriodicalId":542,"journal":{"name":"Environmental Earth Sciences","volume":"84 12","pages":""},"PeriodicalIF":2.8,"publicationDate":"2025-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144140313","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Crustal dynamics study of the unstable North Egyptian shelf through satellite gravity data and inverse/forward modeling","authors":"Menna Haggag,&nbsp;Mohamed Sobh,&nbsp;Hosni H. Ghazala","doi":"10.1007/s12665-025-12322-0","DOIUrl":"10.1007/s12665-025-12322-0","url":null,"abstract":"<div><p>The crustal architecture of northern Egypt, characterized by its tectonic complexity, remains poorly understood due to insufficient seismic data, limited coverage, and inaccuracies in prior gravity models. Recent advancements in satellite gravity methods, however, provide new opportunities to resolve crustal thickness variations with greater precision. In this study, we integrate GOCE gravity data, topography, sediment distributions, and seismic receiver functions to construct a high-resolution Moho depth model for the region. Using inverse and forward modeling techniques, we invert Bouguer anomalies from the GOCO06 gravity field and incorporate data from 50 seismic stations to constrain the model. Our results reveal significant variations in Moho depth, ranging from 23 to 38 km, with thinning to 23–29 km along the coastal zone and thickening to 35–38 km eastward toward the Sinai Peninsula and Red Sea. Forward modeling of three 2.5D crustal cross-sections further elucidates key tectonic features, including [specific features, e.g., fault zones, crustal thinning], which provide new constraints on the region’s tectonic evolution. This integrated approach, combining gravity modeling with seismic and geological constraints, offers a robust crustal thickness model that advances our understanding of northern Egypt’s tectonic history and structure. The findings have important implications for seismic hazard assessment and provide a foundation for future seismic data collection in the region.</p></div>","PeriodicalId":542,"journal":{"name":"Environmental Earth Sciences","volume":"84 12","pages":""},"PeriodicalIF":2.8,"publicationDate":"2025-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s12665-025-12322-0.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144140314","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Spatial quantification of biomass and carbon stock for different land use systems of Kallakurichi and Villupuram districts of Tamil Nadu, India","authors":"Kumaraperumal Ramalingam,&nbsp;Preethi Sekar,&nbsp;Nivas Raj Moorthi","doi":"10.1007/s12665-025-12302-4","DOIUrl":"10.1007/s12665-025-12302-4","url":null,"abstract":"&lt;div&gt;&lt;p&gt;The transformations and sudden shift in the land use and land cover systems (LULC) greatly contributes to the human induced greenhouse gas emissions. With the carbon stock and biomass being quantified for each LULC systems, the sequestration potential and its associated parameters can be assessed aiding in the formulation of carbon related policy decisions. Fifteen different LULC classes including the crops cultivated in the study area were delineated by integrating optical (Sentinel 2A), microwave (Sentinel 1A), and its associated vegetation indices (26 Nos.) using several machine learning algorithms (i.e.) Random Forest (RF), Support Vector Machine (SVM), Multinomial Logistic Regression (MLR), Decision Tree (C5.0) and Extreme Gradient Boosting (XGB). The classification resulted with the random forest having the highest overall accuracy of 71.1% and a kappa coefficient of 0.69, which were enhanced through mask-based delineations. For biomass and stock quantification, a total of 105 observation samples have been collected from the agriculture and forest LULC systems randomly for analysing biomass, bulk density and soil organic carbon using standardized laboratory procedure. The vegetation indices (VI) from both the optical and SAR datasets were then used for the biomass modelling using Multiple Linear Regression (MLR). The regression was then performed with different combinations of the vegetation indices framed and their performance being validated using the test datasets partitioned. Though optical datasets had the evident highest correlation with the biomass values, when compared to the SAR datasets, the synergistic combination of both datasets (optical and SAR) increased the overall performance of the model for above ground biomass estimation. The efficiency of the quantifications was assessed based on the R&lt;sup&gt;2&lt;/sup&gt; and RMSE to indicate the explained variance and the nature of the residuals in the derived model combinations. The integrated optical and the SAR dataset combinations resulted with the R&lt;sup&gt;2&lt;/sup&gt; and RMSE highest for the training (0.84; 3.78 t/ha) and test (0.96; 2.38 t/ha) datasets for agricultural ecosystem. Similarly, for the forest ecosystem, the R&lt;sup&gt;2&lt;/sup&gt; and RMSE metrics derived for the training (0.92; 11.25 t/ha) and the test datasets (0.73; 31.01 t/ha) had the highest measure among the combinations derived. The comprehensive results of the study reported that the random forest and MLR algorithm aided through optical and SAR datasets provided optimal classification and regression results, respectively. Further, the modeling framework resulted with sugarcane crop class having the highest total carbon stock values besides the evergreen forest sequestrating the maximum biomass and carbon stock. Thus, each of the agricultural and forest classes indicated their efficiency in accounting the carbon credit, which can be utilized by the policy makers in strategizing the regulations for carbon sequestration, sustai","PeriodicalId":542,"journal":{"name":"Environmental Earth Sciences","volume":"84 12","pages":""},"PeriodicalIF":2.8,"publicationDate":"2025-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144140239","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evolution of force network, contact network, and tensile force chains in rock-like bonded granular materials under unconfined and confined compression: A DEM study","authors":"Min Zhang,&nbsp;Heinz Konietzky,&nbsp;Zhengyang Song","doi":"10.1007/s12665-025-12288-z","DOIUrl":"10.1007/s12665-025-12288-z","url":null,"abstract":"<div><p>This study numerically investigates contact forces and the contact network in unconfined and confined compression tests on rock-like bonded granular materials using the particle-based discrete element method (DEM). Statistical analysis of contact force magnitudes and polar distributions under varying confining pressures reveals a significant influence of confining pressure on force evolution. Additionally, contact force distribution is closely related to internal structures and external loads. The relationship between contact force and geometrical features of the contact network is analyzed, along with the three-stage evolution of the relationship between force anisotropy and stress ratio, driven by contact network changes. Tensile force chain lengths follow an exponential distribution. Without confinement, tensile force chains remain stable until crack formation, whereas under confinement, they increase in number and length before decreasing due to the occurrence of cracks. Higher confinement results in shorter, fewer tensile force chains. Finally, the number, orientation and force magnitude of new tensile contacts are analyzed to further elucidate tensile contact evolution in bonded granular materials.</p></div>","PeriodicalId":542,"journal":{"name":"Environmental Earth Sciences","volume":"84 12","pages":""},"PeriodicalIF":2.8,"publicationDate":"2025-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s12665-025-12288-z.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144135438","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessment of arsenic contamination in drinking water sources and its effects on human health in rural regions: a study in the Malistan district, Ghazni province of Afghanistan","authors":"Ali Reza Noori,&nbsp;S. K. Singh,&nbsp;Assadullah Rezai","doi":"10.1007/s12665-025-12309-x","DOIUrl":"10.1007/s12665-025-12309-x","url":null,"abstract":"<div><p>Arsenic in drinking water, even in trace levels, can cause cancer, skin conditions, heart disease, and developmental abnormalities in children. The Malistan District in Ghazni Province of Afghanistan heavily relies on groundwater. This study aimed to evaluate the concentration of arsenic, iron, and nitrate in drinking water sources and identify any potential health hazards. Seventy-three water samples, including wells, springs, and surface water, were collected and analyzed for pH, total dissolved solids (TDS), electrical conductivity (EC), temperature, NO₃, Fe, and arsenic levels. Descriptive statistical analysis categorized the data by water source type, comparing results to World Health Organization (WHO) and Afghanistan National Standard Authority (ANSA) guidelines. Arsenic contamination was identified in six wells and four springs, ranging from 5 to 20 µg/L, with iron concentrations up to 4.5 mg/L. Nitrate concentrations, up to 40 mg/L, were observed in most villages. EC and TDS showed a high correlation (R =  + 0.998), while a moderate correlation existed between arsenic and iron (R =  + 0.6205). Rabat village reported 23 cancer deaths from 2000 to 2023, with stomach cancer accounting for about 48% in the 60–80 age group. Health risk assessments revealed hazard quotient (HQ) values exceeding 1 for all samples, indicating potential noncancerous effects, and carcinogenic risk (CR) values greater than 0.0001, suggesting a potential risk of various cancers for children and adults. Urgent measures are needed to address arsenic contamination and associated health risks in the study area. The study suggests several key recommendations, including utilizing alternative water sources, employing arsenic treatment technology, implementing public awareness campaigns, instituting consistent water quality monitoring, advancing healthcare initiatives, and fostering community involvement.</p></div>","PeriodicalId":542,"journal":{"name":"Environmental Earth Sciences","volume":"84 12","pages":""},"PeriodicalIF":2.8,"publicationDate":"2025-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144135460","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comment on “mineralogy, geochemistry and depositional environment of phosphates in the pabdeh formation, khormuj anticline, SW of Iran” by haddad et al. (2023)","authors":"Mohsen Henchiri","doi":"10.1007/s12665-025-12341-x","DOIUrl":"10.1007/s12665-025-12341-x","url":null,"abstract":"<div><p>In a recent paper, Haddad et al. (2023) presented a comprehensive study, including sedimentary, mineralogical and geochemical study of some phosphorite deposits located in the Khormuj anticline, in the southern Folded Zagros Zone, SW of Iran. Despite their excellent dataset and analysis, Haddad et al. (2023) have undervalued important details that would lead to a different interpretation. These gaps concern the measured sections, the influence of basin configuration on the phosphorite composition, the whole rock (phosphorite) sample analysis and organic matter content of the analysed phosphorites.</p></div>","PeriodicalId":542,"journal":{"name":"Environmental Earth Sciences","volume":"84 12","pages":""},"PeriodicalIF":2.8,"publicationDate":"2025-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144135461","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}