Pub Date : 2024-06-03DOI: 10.3389/feart.2024.1403902
Shaopeng Li, Peng Zhou, Baofeng Lan
Shale formations often contain a high proportion of clay minerals, which, upon contact with drilling fluid, undergo hydration expansion. This leads to wellbore instability, a problem that poses significant challenges globally. This study aims to investigate the variation of mechanical properties of shale with respect to hydration time. We employ an empirical model that relates shale strength parameters to the time of drilling through geological formations. Additionally, we consider both shear failure along the wellbore boundary and shear sliding along bedding planes in the analysis. We establish a predictive model for wellbore instability in shale formations. The model quantitatively analyzes the variation of wellbore collapse pressure with drilling time. The research findings indicate that, when the influence of bedding is considered, both the wellbore collapse pressure and the optimal well trajectory undergo significant changes, in addition, for some wellbore trajectories, the collapse pressure can increase by more than 30%. Therefore, it is essential to account for the influence of bedding in wellbore stability analysis in shale formations. As the bedding dip angle changes, both the numerical values and distribution range of wellbore collapse pressure and the optimal well trajectory change noticeably. Changes in bedding dip direction, however, do not affect the numerical values of collapse pressure but do influence the distribution region of the optimal well trajectory. Thus, in wellbore trajectory design within shale formations, it is crucial to determine the orientation of bedding and adjust the well trajectory accordingly to enhance wellbore stability. Furthermore, shale hydration does not impact the optimal well trajectory for a block, but with prolonged hydration, the minimum drilling fluid density required to maintain wellbore stability gradually increases. This suggests that hydration intensifies the weakening effect on bedding plane strength. The research results are helpful to understand the effect of hydration on shale wellbore stability and ensure shale wellbore stability during drilling cycle.
{"title":"Study of wellbore instability in shale formation considering the effect of hydration on strength weakening","authors":"Shaopeng Li, Peng Zhou, Baofeng Lan","doi":"10.3389/feart.2024.1403902","DOIUrl":"https://doi.org/10.3389/feart.2024.1403902","url":null,"abstract":"Shale formations often contain a high proportion of clay minerals, which, upon contact with drilling fluid, undergo hydration expansion. This leads to wellbore instability, a problem that poses significant challenges globally. This study aims to investigate the variation of mechanical properties of shale with respect to hydration time. We employ an empirical model that relates shale strength parameters to the time of drilling through geological formations. Additionally, we consider both shear failure along the wellbore boundary and shear sliding along bedding planes in the analysis. We establish a predictive model for wellbore instability in shale formations. The model quantitatively analyzes the variation of wellbore collapse pressure with drilling time. The research findings indicate that, when the influence of bedding is considered, both the wellbore collapse pressure and the optimal well trajectory undergo significant changes, in addition, for some wellbore trajectories, the collapse pressure can increase by more than 30%. Therefore, it is essential to account for the influence of bedding in wellbore stability analysis in shale formations. As the bedding dip angle changes, both the numerical values and distribution range of wellbore collapse pressure and the optimal well trajectory change noticeably. Changes in bedding dip direction, however, do not affect the numerical values of collapse pressure but do influence the distribution region of the optimal well trajectory. Thus, in wellbore trajectory design within shale formations, it is crucial to determine the orientation of bedding and adjust the well trajectory accordingly to enhance wellbore stability. Furthermore, shale hydration does not impact the optimal well trajectory for a block, but with prolonged hydration, the minimum drilling fluid density required to maintain wellbore stability gradually increases. This suggests that hydration intensifies the weakening effect on bedding plane strength. The research results are helpful to understand the effect of hydration on shale wellbore stability and ensure shale wellbore stability during drilling cycle.","PeriodicalId":12359,"journal":{"name":"Frontiers in Earth Science","volume":null,"pages":null},"PeriodicalIF":2.9,"publicationDate":"2024-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141271065","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Neural networks have become integral to remote sensing data processing. Among neural networks, convolutional neural networks (CNNs) in deep learning offer numerous advanced algorithms for object detection in remote sensing imagery, which is pivotal in military and civilian contexts. CNNs excel in extracting features from training samples. However, traditional CNN models often lack specific signal assumptions tailored to remote sensing data at the feature level. In this paper, we propose a novel approach aimed at effectively representing and correlating information within CNNs for remote sensing object detection. We introduce object tokens and incorporate global information features in embedding layers, facilitating the comprehensive utilization of features across multiple hierarchical levels. Consideration of feature maps from images as two-dimensional signals, matrix image signal processing is employed to correlate features for diverse representations within the CNN framework. Moreover, hierarchical feature signals are effectively represented and associated during end-to-end network training. Experiments on various datasets demonstrate that the CNN model incorporating feature representation and association outperforms CNN models lacking these elements in object detection from remote sensing images. Additionally, integrating image signal processing enhances efficiency in end-to-end network training. Various signal processing approaches increase the process ability of the network, and the methodology could be transferred to other specific and well-defined task.
{"title":"Frontiers | Remote sensing object detection with feature-associated convolutional neural networks","authors":"Jianghao Rao, Tao Wu, Hongyun Li, Jianlin Zhang, Qiliang Bao, Zhenming Peng","doi":"10.3389/feart.2024.1381192","DOIUrl":"https://doi.org/10.3389/feart.2024.1381192","url":null,"abstract":"Neural networks have become integral to remote sensing data processing. Among neural networks, convolutional neural networks (CNNs) in deep learning offer numerous advanced algorithms for object detection in remote sensing imagery, which is pivotal in military and civilian contexts. CNNs excel in extracting features from training samples. However, traditional CNN models often lack specific signal assumptions tailored to remote sensing data at the feature level. In this paper, we propose a novel approach aimed at effectively representing and correlating information within CNNs for remote sensing object detection. We introduce object tokens and incorporate global information features in embedding layers, facilitating the comprehensive utilization of features across multiple hierarchical levels. Consideration of feature maps from images as two-dimensional signals, matrix image signal processing is employed to correlate features for diverse representations within the CNN framework. Moreover, hierarchical feature signals are effectively represented and associated during end-to-end network training. Experiments on various datasets demonstrate that the CNN model incorporating feature representation and association outperforms CNN models lacking these elements in object detection from remote sensing images. Additionally, integrating image signal processing enhances efficiency in end-to-end network training. Various signal processing approaches increase the process ability of the network, and the methodology could be transferred to other specific and well-defined task.","PeriodicalId":12359,"journal":{"name":"Frontiers in Earth Science","volume":null,"pages":null},"PeriodicalIF":2.9,"publicationDate":"2024-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141572262","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-05-31DOI: 10.3389/feart.2024.1379985
Scott Moyer, Dork Sahagian
Lava flows have presented the greatest hazard to human property during the most recent eruptions of Hawaiian volcanoes, and lava fountains are a source of these lava flows. The height of Hawaiian lava fountains reflects the exsolved gas content of the magma that controls eruption intensity. However, fountain height is not always observed, so we sought a proxy to estimate fountain heights of eruptions that were older or otherwise unobserved. Here, methods are described to empirically derive a relationship between the modal diameter of vesicles within Pele’s tears and spheres and lava fountain height, using samples of Pele’s tears produced during the last eruptions of Kīlauea Iki (1959) and Mauna Ulu (1969). The tears used to develop these relationships were approximately 1 to 4 mm in diameter. Additionally, since lava fountains 50–580 m high were used, the relationships we describe may only describe lava fountains in this height range. The strongest empirical relation follows the trendline Hmax = −2575d + 820, where Hmax is maximum lava fountain height and d is modal vesicle diameter. This empirical relationship may be applied to sub-Strombolian eruptions of tholeiite basalt that were not directly measured or observed to assess long-term shifts in lava fountain heights and thus the exsolved gas contents of a volcanic system. While the same conceptual framework can be applied beyond Hawai’i, the quantitative empirical relation may be slightly different in different systems, depending on total dissolved volatiles, magma chemistry and other factors.
{"title":"Use of Pele’s tears and spheres as an indicator of lava fountain height in Hawaiian volcanoes","authors":"Scott Moyer, Dork Sahagian","doi":"10.3389/feart.2024.1379985","DOIUrl":"https://doi.org/10.3389/feart.2024.1379985","url":null,"abstract":"Lava flows have presented the greatest hazard to human property during the most recent eruptions of Hawaiian volcanoes, and lava fountains are a source of these lava flows. The height of Hawaiian lava fountains reflects the exsolved gas content of the magma that controls eruption intensity. However, fountain height is not always observed, so we sought a proxy to estimate fountain heights of eruptions that were older or otherwise unobserved. Here, methods are described to empirically derive a relationship between the modal diameter of vesicles within Pele’s tears and spheres and lava fountain height, using samples of Pele’s tears produced during the last eruptions of Kīlauea Iki (1959) and Mauna Ulu (1969). The tears used to develop these relationships were approximately 1 to 4 mm in diameter. Additionally, since lava fountains 50–580 m high were used, the relationships we describe may only describe lava fountains in this height range. The strongest empirical relation follows the trendline H<jats:sub>max</jats:sub> = −2575d + 820, where H<jats:sub>max</jats:sub> is maximum lava fountain height and d is modal vesicle diameter. This empirical relationship may be applied to sub-Strombolian eruptions of tholeiite basalt that were not directly measured or observed to assess long-term shifts in lava fountain heights and thus the exsolved gas contents of a volcanic system. While the same conceptual framework can be applied beyond Hawai’i, the quantitative empirical relation may be slightly different in different systems, depending on total dissolved volatiles, magma chemistry and other factors.","PeriodicalId":12359,"journal":{"name":"Frontiers in Earth Science","volume":null,"pages":null},"PeriodicalIF":2.9,"publicationDate":"2024-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141188457","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-05-31DOI: 10.3389/feart.2024.1417895
Xiaogang Wu, Dayong Zhu, Hao Lu, Liangmeng Li
This study established a numerical model that considers elevation conditions and slope shape factors by the modified Sadovsky formula to analyze the vibration attenuation law of open-pit slopes under blasting vibration conditions. The blasting excavation of a slope in a certain open-pit mine in Yunfu, Guangdong, is selected as an example. Using a numerical model that considers elevation conditions and slope shape factors by the modified Sadovsky formula, a triangular pulse load was utilized to approximate the time-history characteristics of explosion vibration with FLAC3D software. The simulation results showed the radiation range of the blasting vibration seismic wave. By comparison with field monitoring data, the numerical model that considers the slope shape factor had a relative error of ∼10%, while the numerical model that disregards the slope shape factor had a relative error of ∼15%. The relative accuracy of the calculation results of the new numerical model is higher and closer to the actual attenuation law of blasting particle vibration speed, providing more reliable results for slope stability assessment. The peak particle velocities obtained from the numerical simulation results were generally higher than the field monitoring data. These discrepancies might be attributed to the use of simplified models that disregard the discontinuous structural planes within the rock mass. This study provides an important reference for the stability assessment of open-pit slopes under blasting vibration conditions, offering guidance for improving slope stability assessment and related engineering practices.
{"title":"Frontiers | Simulation research on blasting of an open pit mine slope considering elevation conditions and slope shape factors","authors":"Xiaogang Wu, Dayong Zhu, Hao Lu, Liangmeng Li","doi":"10.3389/feart.2024.1417895","DOIUrl":"https://doi.org/10.3389/feart.2024.1417895","url":null,"abstract":"This study established a numerical model that considers elevation conditions and slope shape factors by the modified Sadovsky formula to analyze the vibration attenuation law of open-pit slopes under blasting vibration conditions. The blasting excavation of a slope in a certain open-pit mine in Yunfu, Guangdong, is selected as an example. Using a numerical model that considers elevation conditions and slope shape factors by the modified Sadovsky formula, a triangular pulse load was utilized to approximate the time-history characteristics of explosion vibration with FLAC3D software. The simulation results showed the radiation range of the blasting vibration seismic wave. By comparison with field monitoring data, the numerical model that considers the slope shape factor had a relative error of ∼10%, while the numerical model that disregards the slope shape factor had a relative error of ∼15%. The relative accuracy of the calculation results of the new numerical model is higher and closer to the actual attenuation law of blasting particle vibration speed, providing more reliable results for slope stability assessment. The peak particle velocities obtained from the numerical simulation results were generally higher than the field monitoring data. These discrepancies might be attributed to the use of simplified models that disregard the discontinuous structural planes within the rock mass. This study provides an important reference for the stability assessment of open-pit slopes under blasting vibration conditions, offering guidance for improving slope stability assessment and related engineering practices.","PeriodicalId":12359,"journal":{"name":"Frontiers in Earth Science","volume":null,"pages":null},"PeriodicalIF":2.9,"publicationDate":"2024-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141572265","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In multi-seam mining, as mining ranges expand and depths increase, the strong ground pressure exerted on the lower coal-seam working faces (WFs) or roadways by coal pillars (CPs) and the hard roof between the interburdens becomes increasingly severe, leading to periodic roof-fall accidents. This study focused on the 42108 WF of the 4–2 coal seam in the Buertai Coal Mine of Shandong mining. It combined field tests, theoretical research, and numerical calculations to investigate the superposition or amplification of ground pressure as WF traversed the CP with the hard roof between interburdens. The ground pressure behavior of WF entering and exiting the CP stage progressed from strong to weak: exiting the CP > under the CP > entering the CP, with the CP stage being prone to a strong ground pressure occurrence. We proposed the influence mechanism of strong ground pressure and a seesaw structural mechanics model under the mining conditions with parallel CPs and hard roofs. The relationship between the geometric structure movement and stress evolution of the seesaw space of the overlying hard roof was analyzed, revealing the mechanism behind stress increase, evident damage, and the likelihood of dynamic disasters within 5–10 m from the CP boundary of the WF. The stress concentration factor (SCF) of the advance abutment pressure in the coal wall was the primary controlling factor determining seesaw instability, effectively ensuring safe and efficient mining practices. This research holds significant theoretical importance and practical engineering value for controlling strong mine pressure under the overlying CPs and hard roofs.
{"title":"A study on the mechanism and control technology of strong mine pressure in parallel coal pillar and hard roof mining","authors":"Haifeng Zhou, Qingxiang Huang, Yanpeng He, Qingxiong Wang, Yehao Wei","doi":"10.3389/feart.2024.1407084","DOIUrl":"https://doi.org/10.3389/feart.2024.1407084","url":null,"abstract":"In multi-seam mining, as mining ranges expand and depths increase, the strong ground pressure exerted on the lower coal-seam working faces (WFs) or roadways by coal pillars (CPs) and the hard roof between the interburdens becomes increasingly severe, leading to periodic roof-fall accidents. This study focused on the 42108 WF of the 4–2 coal seam in the Buertai Coal Mine of Shandong mining. It combined field tests, theoretical research, and numerical calculations to investigate the superposition or amplification of ground pressure as WF traversed the CP with the hard roof between interburdens. The ground pressure behavior of WF entering and exiting the CP stage progressed from strong to weak: exiting the CP &gt; under the CP &gt; entering the CP, with the CP stage being prone to a strong ground pressure occurrence. We proposed the influence mechanism of strong ground pressure and a seesaw structural mechanics model under the mining conditions with parallel CPs and hard roofs. The relationship between the geometric structure movement and stress evolution of the seesaw space of the overlying hard roof was analyzed, revealing the mechanism behind stress increase, evident damage, and the likelihood of dynamic disasters within 5–10 m from the CP boundary of the WF. The stress concentration factor (SCF) of the advance abutment pressure in the coal wall was the primary controlling factor determining seesaw instability, effectively ensuring safe and efficient mining practices. This research holds significant theoretical importance and practical engineering value for controlling strong mine pressure under the overlying CPs and hard roofs.","PeriodicalId":12359,"journal":{"name":"Frontiers in Earth Science","volume":null,"pages":null},"PeriodicalIF":2.9,"publicationDate":"2024-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141188461","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Introduction: Nearly vertical coal seams present a significant challenge for the coal mining industry due to their difficult accessibility. However, these seams account for a substantial proportion of the world’s coal reserves. Therefore, it is vital to conduct research on disaster control techniques for safe mining of these seams.Method: The research team used experimental research, theoretical analysis, and numerical calculation methods to investigate the creep characteristics and failure mechanisms of layered sandstone roadway in nearly vertical coal seam.Results and discussion: These findings revealed that the maximum moment and concentrated stress of the sandstone located on the side of the roadway roof was positioned in the middle of the nearly vertical structure, making it more susceptible to transverse shear failure. On the other hand, the nearly vertical structure on the floor side was prone to shear slip failure initiated from the bottom of the structure. This led to the asymmetric instability of the roadway. The practical implications of this research are significant for the safe mining of nearly vertical coal seams. The results could help inform the development of disaster control techniques.
{"title":"Experimental research on creep characteristics and failure mechanism of mining roadway in nearly vertical coal seams","authors":"Peng Bai, Zhiyong Li, Cong Yu, Enqiang Liu, Hui Gao, Yuanman Xie, Zhongming Yan","doi":"10.3389/feart.2024.1425208","DOIUrl":"https://doi.org/10.3389/feart.2024.1425208","url":null,"abstract":"Introduction: Nearly vertical coal seams present a significant challenge for the coal mining industry due to their difficult accessibility. However, these seams account for a substantial proportion of the world’s coal reserves. Therefore, it is vital to conduct research on disaster control techniques for safe mining of these seams.Method: The research team used experimental research, theoretical analysis, and numerical calculation methods to investigate the creep characteristics and failure mechanisms of layered sandstone roadway in nearly vertical coal seam.Results and discussion: These findings revealed that the maximum moment and concentrated stress of the sandstone located on the side of the roadway roof was positioned in the middle of the nearly vertical structure, making it more susceptible to transverse shear failure. On the other hand, the nearly vertical structure on the floor side was prone to shear slip failure initiated from the bottom of the structure. This led to the asymmetric instability of the roadway. The practical implications of this research are significant for the safe mining of nearly vertical coal seams. The results could help inform the development of disaster control techniques.","PeriodicalId":12359,"journal":{"name":"Frontiers in Earth Science","volume":null,"pages":null},"PeriodicalIF":2.9,"publicationDate":"2024-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141511395","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Drought, being one of the most devastating natural disasters, has a far-reaching impact. In the context of global warming, it becomes crucial to quantitatively and scientifically assess the effects of anthropogenic climate change on meteorological drought in China. This assessment not only enhances our understanding of anthropogenic climate change but also aids in formulating more effective strategies for managing the risks associated with meteorological drought. This study employs the standardized precipitation evapotranspiration index (SPEI) to compute drought events by utilizing both observational data and counterfactual climate data (i.e., detrended observations). Subsequently, it analyzes the impact of anthropogenic climate change on the characteristics of drought, including frequency, intensity, duration, and affected area, in China as well as nine major river basins from 1960 to 2019. The outcomes of the analysis reveal that based on observational data, there is a discernible upward trend in the frequency, intensity, duration, and affected area of meteorological droughts in China. Notably, the regions experiencing an increase in frequency, intensity, and duration are primarily situated in the northeastern part of the Northwestern Rivers basin, the central and western parts of the Yellow River basin, the central and northern parts of the Yangtze River basin, the western part of the Southeastern River basins, and the eastern part of the Pearl River basin. Conversely, when considering a counterfactual climate scenario, the frequency and intensity of meteorological droughts in China demonstrate an upward trend, while the duration and affected area exhibit a downward trend. The impact of anthropogenic climate change on China has been evident in the increased frequency, intensity, duration, and affected area of droughts. Specifically, regions located in the northeastern parts of Northwest River basins, the southern part of the Songliao River basin, the northern part of the Haihe River basin, the central-northern part of the Yangtze River basin, the eastern part of the Pearl River basin, and the western part of the Southwest River basins have experienced amplified levels of drought. Anthropogenic climate change is highlighted as the primary factor influencing the observed drought characteristics changes in China, with contribution rates of 84.67%, 75.25%, 190.32%, and 133.99% for changes in the increased drought frequency, intensity, duration, and affected area, respectively. These changes have significant implications for water resource management and agricultural practices in the affected regions.
{"title":"Impacts of anthropogenic climate change on meteorological drought in China","authors":"Ran Dai, Jinlong Huang, Ziyan Chen, Jian Zhou, Peni Hausia Havea","doi":"10.3389/feart.2024.1369523","DOIUrl":"https://doi.org/10.3389/feart.2024.1369523","url":null,"abstract":"Drought, being one of the most devastating natural disasters, has a far-reaching impact. In the context of global warming, it becomes crucial to quantitatively and scientifically assess the effects of anthropogenic climate change on meteorological drought in China. This assessment not only enhances our understanding of anthropogenic climate change but also aids in formulating more effective strategies for managing the risks associated with meteorological drought. This study employs the standardized precipitation evapotranspiration index (SPEI) to compute drought events by utilizing both observational data and counterfactual climate data (i.e., detrended observations). Subsequently, it analyzes the impact of anthropogenic climate change on the characteristics of drought, including frequency, intensity, duration, and affected area, in China as well as nine major river basins from 1960 to 2019. The outcomes of the analysis reveal that based on observational data, there is a discernible upward trend in the frequency, intensity, duration, and affected area of meteorological droughts in China. Notably, the regions experiencing an increase in frequency, intensity, and duration are primarily situated in the northeastern part of the Northwestern Rivers basin, the central and western parts of the Yellow River basin, the central and northern parts of the Yangtze River basin, the western part of the Southeastern River basins, and the eastern part of the Pearl River basin. Conversely, when considering a counterfactual climate scenario, the frequency and intensity of meteorological droughts in China demonstrate an upward trend, while the duration and affected area exhibit a downward trend. The impact of anthropogenic climate change on China has been evident in the increased frequency, intensity, duration, and affected area of droughts. Specifically, regions located in the northeastern parts of Northwest River basins, the southern part of the Songliao River basin, the northern part of the Haihe River basin, the central-northern part of the Yangtze River basin, the eastern part of the Pearl River basin, and the western part of the Southwest River basins have experienced amplified levels of drought. Anthropogenic climate change is highlighted as the primary factor influencing the observed drought characteristics changes in China, with contribution rates of 84.67%, 75.25%, 190.32%, and 133.99% for changes in the increased drought frequency, intensity, duration, and affected area, respectively. These changes have significant implications for water resource management and agricultural practices in the affected regions.","PeriodicalId":12359,"journal":{"name":"Frontiers in Earth Science","volume":null,"pages":null},"PeriodicalIF":2.9,"publicationDate":"2024-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141188453","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-05-31DOI: 10.3389/feart.2024.1344690
Priyanka Priyanka, Praveen Kumar, Sucheta Panda, Tejinder Thakur, K. V. Uday, Varun Dutt
Extreme weather events and global climate change have exacerbated the problem of evaporation rates. Thus, accurately predicting soil moisture evaporation rates affecting soil cracking becomes crucial. However, less is known about how novel feature engineering techniques and machine-learning predictions may account for estimating the soil moisture evaporation rate. This research focuses on predicting the evaporation rate of soil using machine learning (ML) models. The dataset comprised twenty-one ground-based parameters, including temperature, humidity, and soil-related features, used as features to predict evaporation potential. To tackle the high number of features and potential uncorrelated features, a novel guided backpropagation-based feature selection technique was developed to rank the most relevant features. The top-10 features, highly correlated with evaporation rate, were selected for ML model input, alongside the top-5 and all features. Several ML models, including multiple regression (MR), K-nearest neighbor (KNN), multilayer perceptron (MLP), sequential minimal optimization regression (SMOreg), random forest (RF), and a novel K-Nearest Oracles (KNORA) ensemble, were constructed for the purpose of forecasting the evaporation rate. The average error of these models was assessed using the root mean squared error (RMSE). Experimental results showed that the KNORA ensemble model performed the best, achieving a 7.54 mg/h RMSE in testing with the top-10 features. MLP was followed closely by a 25.1 mg/h RMSE in the same testing. An empirical model using all features showed a higher RMSE of 1319.1 mg/h, indicating the superiority of the ML models for accurate evaporation rate predictions. We highlight the implications of our results for climate-induced soil cracking in the real world.
极端天气事件和全球气候变化加剧了蒸发率问题。因此，准确预测影响土壤开裂的土壤水分蒸发率变得至关重要。然而，人们对新型特征工程技术和机器学习预测如何估算土壤水分蒸发率知之甚少。本研究的重点是利用机器学习（ML）模型预测土壤蒸发率。数据集由 21 个地面参数组成，包括温度、湿度和土壤相关特征，用作预测蒸发潜力的特征。针对大量特征和潜在的不相关特征，开发了一种新颖的基于反向传播引导的特征选择技术，对最相关的特征进行排序。除前 5 个特征和所有特征外，还选择了与蒸发率高度相关的前 10 个特征作为 ML 模型的输入。为了预测蒸发率，构建了多个 ML 模型，包括多元回归模型（MR）、K-近邻模型（KNN）、多层感知器模型（MLP）、连续最小优化回归模型（SMOreg）、随机森林模型（RF）和新型 K-近邻模型（KNORA）。这些模型的平均误差采用均方根误差（RMSE）进行评估。实验结果表明，KNORA 集合模型表现最佳，在使用前 10 个特征进行测试时，RMSE 为 7.54 mg/h。MLP 紧随其后，在相同测试中的 RMSE 为 25.1 毫克/小时。使用所有特征的经验模型显示出更高的均方根误差（RMSE），达到 1319.1 毫克/小时，这表明 ML 模型在准确预测蒸发率方面更具优势。我们强调了我们的结果对现实世界中由气候引起的土壤开裂的影响。
{"title":"Can machine learning models predict soil moisture evaporation rates? An investigation via novel feature selection techniques and model comparisons","authors":"Priyanka Priyanka, Praveen Kumar, Sucheta Panda, Tejinder Thakur, K. V. Uday, Varun Dutt","doi":"10.3389/feart.2024.1344690","DOIUrl":"https://doi.org/10.3389/feart.2024.1344690","url":null,"abstract":"Extreme weather events and global climate change have exacerbated the problem of evaporation rates. Thus, accurately predicting soil moisture evaporation rates affecting soil cracking becomes crucial. However, less is known about how novel feature engineering techniques and machine-learning predictions may account for estimating the soil moisture evaporation rate. This research focuses on predicting the evaporation rate of soil using machine learning (ML) models. The dataset comprised twenty-one ground-based parameters, including temperature, humidity, and soil-related features, used as features to predict evaporation potential. To tackle the high number of features and potential uncorrelated features, a novel guided backpropagation-based feature selection technique was developed to rank the most relevant features. The top-10 features, highly correlated with evaporation rate, were selected for ML model input, alongside the top-5 and all features. Several ML models, including multiple regression (MR), K-nearest neighbor (KNN), multilayer perceptron (MLP), sequential minimal optimization regression (SMOreg), random forest (RF), and a novel K-Nearest Oracles (KNORA) ensemble, were constructed for the purpose of forecasting the evaporation rate. The average error of these models was assessed using the root mean squared error (RMSE). Experimental results showed that the KNORA ensemble model performed the best, achieving a 7.54 mg/h RMSE in testing with the top-10 features. MLP was followed closely by a 25.1 mg/h RMSE in the same testing. An empirical model using all features showed a higher RMSE of 1319.1 mg/h, indicating the superiority of the ML models for accurate evaporation rate predictions. We highlight the implications of our results for climate-induced soil cracking in the real world.","PeriodicalId":12359,"journal":{"name":"Frontiers in Earth Science","volume":null,"pages":null},"PeriodicalIF":2.9,"publicationDate":"2024-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141188261","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-05-30DOI: 10.3389/feart.2024.1403043
Dariusz Nawrocki, Maciej J. Mendecki, Leslaw Teper
The horizontal-to-vertical (H/V) method is a fundamental fast tool to estimate local site effect parameters by using the registered signals of the translational motion. The spectral ratio is mostly calculated using the Fourier Spectrum Analysis (FSA), which may lead to problems with accurate resonant frequency determination due to evident multi-amplification peaks occurrence on the spectrum. Alternatively the H/V ratio may be estimated by use Response Spectrum Analysis (RSA), where only a general amplification peak is expected. However, the fundamental limitations of the RSA assumption are related to the real impact of the events’ scenario dependence (i.e., magnitude, distance, focal mechanism, etc.). The limitations and advantages of the RSA and FSA are commonly known in the case of the analysis performed for the translational signals. Therefore, the critical question is: should the RSA and FSA methods be used to estimate the H/V ratio of the recorded rotational signals of the events? The article presents horizontal-to-vertical (H/V) spectral ratios calculated for rotational and translational signals registered as an effect of mining-induced seismicity by four independent seismic stations located in Poland's Upper Silesian Coal basin. The spectral ratios of the signals were estimated using the RSA and the FSA method. The studies show that in the case of translational motion, the H/V estimations using the RSA derived clear information of the resonant frequency peak, confirming the method’s usefulness in the case of multi-amplification peaks. The opposite situation was noticed in the case of the rotational motion. The derived H/V spectrum, using the RSA, produced single amplification peaks for the seismic stations, where the sensors were mounted on a small floor at a significant distance from the walls. In cases where the sensors were deployed on the building floor, a decrease in the reliability of the RSA and the FSA method was noticed. The results of the studies suggested that the possibility of the estimations of the H/V spectrum using the RSA and FSA algorithm is strongly limited for rotational motions due to the size of the floor and distance to the building walls where the sensors were mounted. The explanation of that fact is related to the effects of kinematic soil-structure interaction, which may significantly affect rotational measurements due to the tendency to obtain higher frequency content than in the case of the translations. Consequently, the values of the Z- component of the rotational motion may be lovered than in the free-field measurements, decreasing the reliability of the H/V estimations for rotational motion.
{"title":"Estimation of the resonance frequency of rotational and translational signals evoked by mining-induced seismicity","authors":"Dariusz Nawrocki, Maciej J. Mendecki, Leslaw Teper","doi":"10.3389/feart.2024.1403043","DOIUrl":"https://doi.org/10.3389/feart.2024.1403043","url":null,"abstract":"The horizontal-to-vertical (H/V) method is a fundamental fast tool to estimate local site effect parameters by using the registered signals of the translational motion. The spectral ratio is mostly calculated using the Fourier Spectrum Analysis (FSA), which may lead to problems with accurate resonant frequency determination due to evident multi-amplification peaks occurrence on the spectrum. Alternatively the H/V ratio may be estimated by use Response Spectrum Analysis (RSA), where only a general amplification peak is expected. However, the fundamental limitations of the RSA assumption are related to the real impact of the events’ scenario dependence (i.e., magnitude, distance, focal mechanism, etc.). The limitations and advantages of the RSA and FSA are commonly known in the case of the analysis performed for the translational signals. Therefore, the critical question is: should the RSA and FSA methods be used to estimate the H/V ratio of the recorded rotational signals of the events? The article presents horizontal-to-vertical (H/V) spectral ratios calculated for rotational and translational signals registered as an effect of mining-induced seismicity by four independent seismic stations located in Poland's Upper Silesian Coal basin. The spectral ratios of the signals were estimated using the RSA and the FSA method. The studies show that in the case of translational motion, the H/V estimations using the RSA derived clear information of the resonant frequency peak, confirming the method’s usefulness in the case of multi-amplification peaks. The opposite situation was noticed in the case of the rotational motion. The derived H/V spectrum, using the RSA, produced single amplification peaks for the seismic stations, where the sensors were mounted on a small floor at a significant distance from the walls. In cases where the sensors were deployed on the building floor, a decrease in the reliability of the RSA and the FSA method was noticed. The results of the studies suggested that the possibility of the estimations of the H/V spectrum using the RSA and FSA algorithm is strongly limited for rotational motions due to the size of the floor and distance to the building walls where the sensors were mounted. The explanation of that fact is related to the effects of kinematic soil-structure interaction, which may significantly affect rotational measurements due to the tendency to obtain higher frequency content than in the case of the translations. Consequently, the values of the Z- component of the rotational motion may be lovered than in the free-field measurements, decreasing the reliability of the H/V estimations for rotational motion.","PeriodicalId":12359,"journal":{"name":"Frontiers in Earth Science","volume":null,"pages":null},"PeriodicalIF":2.9,"publicationDate":"2024-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141188669","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-05-30DOI: 10.3389/feart.2024.1391509
Jian Zhao, Dan Huang, Yongshun Cai, Dengxia Huang, Xiaolong Zhou, Fei Wang, Yuxiang Pan
A newly developed microseismic (MS) monitoring system was employed in the Tianshan-Shengli tunnel to detect MS activities and then predict and provide early warning of rockburst disasters. The system not only has the advantages of accuracy of artificial analysis but also real-time analysis and warnings. The positioning accuracy for MS events is approximately 5–10 m. A new sensor installation scheme was proposed to achieve fast sensor installation and recovery, taking advantage of semicircular steel tubes and hose clamps. In addition, the rockburst risk level prediction criteria adopted multiple evaluation indexes such as MS event energy and moment magnitude and number, and it revealed that the evolution of maximum energy has a good positive correlation with that of maximum moment magnitude through analyzing the monitored MS events. It also showed that the rockburst generally occurred 2 days after the rock mass was exposed by the tunnel boring machine (TBM) tail shield and belonged to the delayed rockburst category, according to the field statistical results. The preliminary application cases indicated that the rockburst prediction and early warning based on MS monitoring agree with the site survey results. Therefore, the new MS monitoring system is a reliable tool for predicting and providing early warnings of rockburst disasters.
天山-胜利隧道采用了新开发的微震（MS）监测系统，以检测 MS 活动，进而预测和预警岩爆灾害。该系统不仅具有人工分析的准确性，还具有实时分析和预警的优势。利用半圆形钢管和软管夹的优势，提出了一种新的传感器安装方案，以实现传感器的快速安装和回收。此外，岩爆风险等级预测标准采用了多种评价指标，如 MS 事件能量、力矩大小和数量，并通过分析监测到的 MS 事件，发现最大能量的演变与最大力矩大小的演变具有良好的正相关性。现场统计结果还表明，岩爆一般发生在隧道掘进机（TBM）尾部盾构露出岩体后 2 天，属于延迟岩爆。初步应用案例表明，基于 MS 监测的岩爆预测和预警与现场勘测结果一致。因此，新型 MS 监测系统是预测和预警岩爆灾害的可靠工具。
{"title":"Rockburst prediction and early warning for a highway tunnel excavated by TBM based on microseismic monitoring","authors":"Jian Zhao, Dan Huang, Yongshun Cai, Dengxia Huang, Xiaolong Zhou, Fei Wang, Yuxiang Pan","doi":"10.3389/feart.2024.1391509","DOIUrl":"https://doi.org/10.3389/feart.2024.1391509","url":null,"abstract":"A newly developed microseismic (MS) monitoring system was employed in the Tianshan-Shengli tunnel to detect MS activities and then predict and provide early warning of rockburst disasters. The system not only has the advantages of accuracy of artificial analysis but also real-time analysis and warnings. The positioning accuracy for MS events is approximately 5–10 m. A new sensor installation scheme was proposed to achieve fast sensor installation and recovery, taking advantage of semicircular steel tubes and hose clamps. In addition, the rockburst risk level prediction criteria adopted multiple evaluation indexes such as MS event energy and moment magnitude and number, and it revealed that the evolution of maximum energy has a good positive correlation with that of maximum moment magnitude through analyzing the monitored MS events. It also showed that the rockburst generally occurred 2 days after the rock mass was exposed by the tunnel boring machine (TBM) tail shield and belonged to the delayed rockburst category, according to the field statistical results. The preliminary application cases indicated that the rockburst prediction and early warning based on MS monitoring agree with the site survey results. Therefore, the new MS monitoring system is a reliable tool for predicting and providing early warnings of rockburst disasters.","PeriodicalId":12359,"journal":{"name":"Frontiers in Earth Science","volume":null,"pages":null},"PeriodicalIF":2.9,"publicationDate":"2024-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141188267","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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