首页 > 最新文献

Journal of Earth System Science最新文献

英文 中文
Spatiotemporal coda Q variations in the northeastern margin of the Qinghai–Tibet Plateau, China 中国青藏高原东北缘的时空尾波 Q 值变化
IF 1.9 4区 地球科学 Q3 GEOSCIENCES, MULTIDISCIPLINARY Pub Date : 2024-06-04 DOI: 10.1007/s12040-024-02316-0
Zhaocheng Liang, Xiao Guo, Rui Zou, Xuzhou Liu, Manzhong Qin, Shaohua Li

Abstract

The seismic quality factor (Q) is an important physical parameter to characterize seismic wave attenuation. Therefore, analyzing its spatiotemporal variation is essential to better understand tectonic activity, characterize earthquake source mechanisms, and assess seismic hazards. In this study, we used a single-scattering model to calculate Q for coda waves (Qc values) generated by earthquakes with epicentral distances <100 km and magnitudes M > 2.0 recorded in 2000–2023 in the northeastern margin of the Qinghai–Tibet Plateau (the study area). The calculated dependence of Qc on the bandpass filter central frequency f in the study area was ({Q}_{c}=left(72.40pm 9right){f}^{left(1.10pm 0.06right)}), ({Q}_{c}=left(100.95pm 15right){f}^{left(1.03pm 0.07right)}), and ({Q}_{c}=left(128.76pm 20right){f}^{left(0.97pm 0.07right)}) within lapse-time windows of length 20, 30, and 40 s, respectively. To estimate Qc in distinct active tectonic and fault regions, we divided the study area into two subregions, the Haiyuan and Qinling active tectonic zones. We determined a strong spatial correlation between the Qc distribution and tectonic activity in the study area, with correspondingly low Qc values. Finally, by analyzing the temporal evolution of Qc, we established that nearly all strong earthquakes (M > 6.0) that occurred in the study area in 2000–2023 were preceded by a 10–27% decrease in Qc values, a phenomenon possibly related to the ‘rock dilatancy’ theory.

Research highlights

  1. 1.

    Characteristics of code-wave attenuation in the northeastern margin of the Qinghai–Tibet Plateau.

  2. 2.

    Strong correlation between Qc values and active blocks distribution in the northeastern margin of the Qinghai–Tibet Plateau.

  3. 3.

    Most strong earthquakes in the northeastern margin of the Qinghai–Tibet Plateau were preceded by a decrease in Qc values.

摘要 地震品质因数(Q)是表征地震波衰减的重要物理参数。因此,分析其时空变化对于更好地理解构造活动、确定震源机制和评估地震灾害至关重要。在本研究中,我们使用单散射模型计算了 2000-2023 年青藏高原东北缘(研究区)震中距 100 km、震级 Mgt; 2.0 的地震产生的残波 Q 值(Qc 值)。在研究区,Qc与带通滤波器中心频率f的计算关系为({Q}_{c}=left(72.40pm 9right){f}^{left(1.10pm 0.06right)}),({Q}_{c}=left(100.和({Q}_{c}=left(128.76pm 20right){f}^{left(0.97pm 0.07right)}) 分别在长度为 20、30 和 40 秒的时间窗口内。为了估算不同活动构造和断层区域的Qc,我们将研究区域划分为两个子区域,即海原活动构造带和秦岭活动构造带。我们确定研究区的 Qc 分布与构造活动之间存在较强的空间相关性,Qc 值也相应较低。最后,通过分析 Qc 的时间演变,我们确定了 2000-2023 年在研究区发生的几乎所有强震(M > 6.0)之前,Qc 值都下降了 10-27%,这一现象可能与 "岩石膨胀 "理论有关。青藏高原东北缘码波衰减特征2.青藏高原东北缘Qc值与活动块体分布密切相关3.青藏高原东北缘大部分强震发生前Qc值均有下降。
{"title":"Spatiotemporal coda Q variations in the northeastern margin of the Qinghai–Tibet Plateau, China","authors":"Zhaocheng Liang, Xiao Guo, Rui Zou, Xuzhou Liu, Manzhong Qin, Shaohua Li","doi":"10.1007/s12040-024-02316-0","DOIUrl":"https://doi.org/10.1007/s12040-024-02316-0","url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract</h3><p>The seismic quality factor (<i>Q</i>) is an important physical parameter to characterize seismic wave attenuation. Therefore, analyzing its spatiotemporal variation is essential to better understand tectonic activity, characterize earthquake source mechanisms, and assess seismic hazards. In this study, we used a single-scattering model to calculate <i>Q</i> for coda waves (<i>Q</i><sub><i>c</i></sub> values) generated by earthquakes with epicentral distances &lt;100 km and magnitudes <i>M</i> &gt; 2.0 recorded in 2000–2023 in the northeastern margin of the Qinghai–Tibet Plateau (the study area). The calculated dependence of <i>Q</i><sub><i>c</i></sub> on the bandpass filter central frequency <i>f</i> in the study area was <span>({Q}_{c}=left(72.40pm 9right){f}^{left(1.10pm 0.06right)})</span>, <span>({Q}_{c}=left(100.95pm 15right){f}^{left(1.03pm 0.07right)})</span>, and <span>({Q}_{c}=left(128.76pm 20right){f}^{left(0.97pm 0.07right)})</span> within lapse-time windows of length 20, 30, and 40 s, respectively. To estimate <i>Q</i><sub><i>c</i></sub> in distinct active tectonic and fault regions, we divided the study area into two subregions, the Haiyuan and Qinling active tectonic zones. We determined a strong spatial correlation between the <i>Q</i><sub><i>c</i></sub> distribution and tectonic activity in the study area, with correspondingly low <i>Q</i><sub><i>c</i></sub> values. Finally, by analyzing the temporal evolution of <i>Q</i><sub><i>c</i></sub>, we established that nearly all strong earthquakes (<i>M</i> &gt; 6.0) that occurred in the study area in 2000–2023 were preceded by a 10–27% decrease in <i>Q</i><sub><i>c</i></sub> values, a phenomenon possibly related to the ‘rock dilatancy’ theory.</p><h3 data-test=\"abstract-sub-heading\">Research highlights</h3><ol>\u0000<li>\u0000<span>1.</span>\u0000<p>Characteristics of code-wave attenuation in the northeastern margin of the Qinghai–Tibet Plateau.</p>\u0000</li>\u0000<li>\u0000<span>2.</span>\u0000<p>Strong correlation between <i>Q</i><sub><i>c</i></sub> values and active blocks distribution in the northeastern margin of the Qinghai–Tibet Plateau.</p>\u0000</li>\u0000<li>\u0000<span>3.</span>\u0000<p> Most strong earthquakes in the northeastern margin of the Qinghai–Tibet Plateau were preceded by a decrease in <i>Q</i><sub><i>c</i></sub> values.</p>\u0000</li>\u0000</ol>","PeriodicalId":15609,"journal":{"name":"Journal of Earth System Science","volume":"32 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141253068","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Estimation of missing daily temperature and rainfall for longer durations at Hatiya and Sandwip islands in the Bay of Bengal 估算孟加拉湾哈提亚岛和桑德韦普岛缺失的较长时间日气温和降雨量
IF 1.9 4区 地球科学 Q3 GEOSCIENCES, MULTIDISCIPLINARY Pub Date : 2024-05-30 DOI: 10.1007/s12040-024-02318-y
Syed Mustafizur Rahman, Md Alif Hosen Babla, Razia Sultana, Saidatus Saba, Ashabul Hoque

This study has estimated the missing values of minimum temperature, maximum temperature and rainfall records of longer lengths, respectively, from 1994 to 1996 in Hatiya and 2000–2003 in Sandwip islands of the Bay of Bengal with harmonic regression analysis to realize the past climate. The work has provided past climate of records, which have justified with the mean absolute error, root mean squared error and skill score respectively 1.50, 2.00 and 0.84 for minimum temperature, 1.66, 2.10 and 0.48 for maximum temperature, and 8.60, 14.69 and –0.43 for rainfall for the stations with known records. The mean of the two estimations varies respectively for temperature and rainfall from –0.69 to 0.64°C and –0.36 to 4.79 mm, where one estimation is done with the proposed harmonic analysis and another estimation has been done with inverse-distance-weighting technique for the stations with missing records. The study is advantageous because it uses data from its own station on the island rather than data from neighbouring stations on the continent. It has avoided the probability of mixing up the continental climate with the climate of the island and vice versa. Hence, the estimations provided are spatially unbiased and meaningful past climate.

本研究利用调和回归分析法估算了孟加拉湾哈提亚岛 1994 年至 1996 年和桑德韦普岛 2000 年至 2003 年较长时期的最低气温、最高气温和降雨量记录的缺失值,以了解过去的气候。这项工作提供了过去气候的记录,对于有已知记录的站点,其平均绝对误差、均方根误差和技能得分分别为:最低气温 1.50、2.00 和 0.84;最高气温 1.66、2.10 和 0.48;降雨量 8.60、14.69 和 -0.43。对于气温和降雨量,两种估算值的平均值分别为-0.69 至 0.64°C 和-0.36 至 4.79 毫米,其中一种估算值采用了拟议的谐波分析方法,另一种估算值则采用了反距离加权技术,用于对记录缺失的站点进行估算。这项研究的优势在于,它使用的数据来自岛上自己的站点,而不是大陆上邻近站点的数据。它避免了将大陆气候与岛屿气候混为一谈的可能性,反之亦然。因此,所提供的估算在空间上没有偏差,对过去的气候有意义。
{"title":"Estimation of missing daily temperature and rainfall for longer durations at Hatiya and Sandwip islands in the Bay of Bengal","authors":"Syed Mustafizur Rahman, Md Alif Hosen Babla, Razia Sultana, Saidatus Saba, Ashabul Hoque","doi":"10.1007/s12040-024-02318-y","DOIUrl":"https://doi.org/10.1007/s12040-024-02318-y","url":null,"abstract":"<p>This study has estimated the missing values of minimum temperature, maximum temperature and rainfall records of longer lengths, respectively, from 1994 to 1996 in Hatiya and 2000–2003 in Sandwip islands of the Bay of Bengal with harmonic regression analysis to realize the past climate. The work has provided past climate of records, which have justified with the mean absolute error, root mean squared error and skill score respectively 1.50, 2.00 and 0.84 for minimum temperature, 1.66, 2.10 and 0.48 for maximum temperature, and 8.60, 14.69 and –0.43 for rainfall for the stations with known records. The mean of the two estimations varies respectively for temperature and rainfall from –0.69 to 0.64°C and –0.36 to 4.79 mm, where one estimation is done with the proposed harmonic analysis and another estimation has been done with inverse-distance-weighting technique for the stations with missing records. The study is advantageous because it uses data from its own station on the island rather than data from neighbouring stations on the continent. It has avoided the probability of mixing up the continental climate with the climate of the island and vice versa. Hence, the estimations provided are spatially unbiased and meaningful past climate.</p>","PeriodicalId":15609,"journal":{"name":"Journal of Earth System Science","volume":"39 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141194255","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
A stacked ensemble learning-based framework for mineral mapping using AVIRIS-NG hyperspectral image 利用 AVIRIS-NG 高光谱图像绘制矿物图的基于堆叠集合学习的框架
IF 1.9 4区 地球科学 Q3 GEOSCIENCES, MULTIDISCIPLINARY Pub Date : 2024-05-30 DOI: 10.1007/s12040-024-02317-z
Ram Nivas Giri, Rekh Ram Janghel, Himanshu Govil, Gaurav Mishra

Abstract

Hyperspectral data has a significant count of spectral channels with an enhanced spectral resolution, which provides detailed information at each pixel. This data can be used in numerous remote sensing (RS) applications, along with mineral mapping. Mineral mapping is an important component of geological mapping, which helps in investigating the mineralization potential of an area. This work can be completed effectively by applying machine learning (ML) techniques to RS data. This paper proposes a stacked ensemble-based framework for mineral mapping using the dataset obtained by the Airborne Visible Infrared Imaging Spectrometer-Next Generation (AVIRIS-NG). The study area is situated in Jahazpur, Rajasthan, India. The purpose of this stacked ensemble-based model is to enhance the performance of ML-based mineral mapping. The proposed stacked ensemble model consists of two major elements: a base learner (Naïve Bayes, KNN, artificial neural network, decision tree, and support vector machine) and a stacked learner (random forest). The results of the experiments show that the stacked ensemble-based model has a lot of potential for accurately mapping the minerals talc, montmorillonite, kaolionite, and kaosmec. The proposed model has obtained an overall accuracy of 98.96%, an average accuracy of 98.21%, and a Kappa coefficient of 0.9628.

Research highlights

  • A stacked ensemble-based model for mineral mapping is proposed.

  • The well-known five conventional machine learning models (called base models) are investigated for mineral mapping.

  • The performance of the proposed model is evaluated on the AVIRIG–NG dataset. The study area is situated in Jahazpur, Rajasthan, India.

  • The proposed method outperformed all base models.

摘要 高光谱数据具有大量光谱通道,光谱分辨率更高,可提供每个像素的详细信息。这种数据可用于多种遥感(RS)应用以及矿物测绘。矿物测绘是地质测绘的重要组成部分,有助于调查一个地区的成矿潜力。将机器学习(ML)技术应用于遥感数据可以有效地完成这项工作。本文利用机载可见红外成像光谱仪-下一代(AVIRIS-NG)获得的数据集,提出了一种基于堆叠集合的矿产绘图框架。研究区域位于印度拉贾斯坦邦的贾哈兹布尔。该基于叠加集合的模型旨在提高基于 ML 的矿物测绘性能。所提议的堆叠集合模型由两个主要元素组成:基础学习器(奈夫贝叶斯、KNN、人工神经网络、决策树和支持向量机)和堆叠学习器(随机森林)。实验结果表明,基于堆叠集合的模型在精确绘制滑石、蒙脱石、高岭土和高斯米克矿物图谱方面具有很大的潜力。提出的模型总体准确率为 98.96%,平均准确率为 98.21%,Kappa 系数为 0.9628。研究要点提出了基于堆叠集合的矿物测绘模型,研究了用于矿物测绘的著名的五种传统机器学习模型(称为基础模型)。研究区域位于印度拉贾斯坦邦的 Jahazpur。
{"title":"A stacked ensemble learning-based framework for mineral mapping using AVIRIS-NG hyperspectral image","authors":"Ram Nivas Giri, Rekh Ram Janghel, Himanshu Govil, Gaurav Mishra","doi":"10.1007/s12040-024-02317-z","DOIUrl":"https://doi.org/10.1007/s12040-024-02317-z","url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract</h3><p>Hyperspectral data has a significant count of spectral channels with an enhanced spectral resolution, which provides detailed information at each pixel. This data can be used in numerous remote sensing (RS) applications, along with mineral mapping. Mineral mapping is an important component of geological mapping, which helps in investigating the mineralization potential of an area. This work can be completed effectively by applying machine learning (ML) techniques to RS data. This paper proposes a stacked ensemble-based framework for mineral mapping using the dataset obtained by the Airborne Visible Infrared Imaging Spectrometer-Next Generation (AVIRIS-NG). The study area is situated in Jahazpur, Rajasthan, India. The purpose of this stacked ensemble-based model is to enhance the performance of ML-based mineral mapping. The proposed stacked ensemble model consists of two major elements: a base learner (Naïve Bayes, KNN, artificial neural network, decision tree, and support vector machine) and a stacked learner (random forest). The results of the experiments show that the stacked ensemble-based model has a lot of potential for accurately mapping the minerals talc, montmorillonite, kaolionite, and kaosmec. The proposed model has obtained an overall accuracy of 98.96%, an average accuracy of 98.21%, and a Kappa coefficient of 0.9628.</p><h3 data-test=\"abstract-sub-heading\">Research highlights</h3>\u0000<ul>\u0000<li>\u0000<p>A stacked ensemble-based model for mineral mapping is proposed.</p>\u0000</li>\u0000<li>\u0000<p>The well-known five conventional machine learning models (called base models) are investigated for mineral mapping.</p>\u0000</li>\u0000<li>\u0000<p>The performance of the proposed model is evaluated on the AVIRIG–NG dataset. The study area is situated in Jahazpur, Rajasthan, India.</p>\u0000</li>\u0000<li>\u0000<p>The proposed method outperformed all base models.</p>\u0000</li>\u0000</ul>","PeriodicalId":15609,"journal":{"name":"Journal of Earth System Science","volume":"42 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141194256","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Geochemical insights into the 5.4 ka event in the eastern Arabian Shelf 阿拉伯大陆架东部 5.4 ka 事件的地球化学启示
IF 1.9 4区 地球科学 Q3 GEOSCIENCES, MULTIDISCIPLINARY Pub Date : 2024-05-30 DOI: 10.1007/s12040-024-02329-9
Shiba Shankar Acharya, Pallab Dey

This study explores the historical presence of the El Niño-Southern Oscillation (ENSO) phenomenon during the Holocene and its impact on the Indian Summer Monsoon (ISM) and the East Asian Summer Monsoon (EAM). This investigation sheds light on an area with limited prior understanding. The primary objective is to analyse ISM variations from ~ 6000 to 1700 calibrated years before the Present (cal yr BP) and decipher their connection with the EAM. Sediment samples were obtained from core SK-291/GC-15, collected off the coast of Goa, and underwent comprehensive analysis, including examination of major, trace, and rare earth elements (REEs). The findings from geochemical proxies reveal that variations in sample compositions are primarily attributed to shifts in chemical weathering intensity rather than alterations in the source rock composition, and the sediments were deposited under consistent anoxic conditions. A noteworthy shift in the chemical weathering pattern was identified, particularly during the ~6000–4400 cal yr BP period, coinciding with the onset of intensified ISM around ~5400 cal yr BP. This intensified monsoon phase, recognised as the 5.4 ka event, coincides with the development of the Harappan civilisation, highlighting its historical significance. Notably, an inverse relationship between the ISM and EAM was observed during this 5.4 ka event – a phenomenon explained by the influence of ENSO on the Asian monsoon system.

本研究探讨了全新世期间厄尔尼诺-南方涛动(ENSO)现象的历史存在及其对印度夏季季候风(ISM)和东亚夏季季候风(EAM)的影响。这项调查揭示了一个之前了解有限的领域。主要目的是分析从距今约 6000 年到 1700 年(公元前 1700 年)的印度夏季季候风变化,并解读其与东亚夏季季候风之间的联系。沉积物样本取自果阿海岸外采集的岩芯 SK-291/GC-15,并进行了全面分析,包括主要、痕量和稀土元素(REEs)的检测。地球化学代用指标的研究结果表明,样品成分的变化主要归因于化学风化强度的变化,而不是源岩成分的改变,沉积物是在一致的缺氧条件下沉积的。化学风化模式发生了值得注意的变化,尤其是在约公元前 6000-4400 年期间,这与约公元前 5400 年左右开始的强化 ISM 相吻合。这一季风增强阶段被认为是 5.4 ka 事件,与哈拉帕文明的发展相吻合,突出了其历史意义。值得注意的是,在 5.4 ka 事件期间观测到了 ISM 与 EAM 之间的反比关系--这一现象可以用厄尔尼诺/南方涛动对亚洲季风系统的影响来解释。
{"title":"Geochemical insights into the 5.4 ka event in the eastern Arabian Shelf","authors":"Shiba Shankar Acharya, Pallab Dey","doi":"10.1007/s12040-024-02329-9","DOIUrl":"https://doi.org/10.1007/s12040-024-02329-9","url":null,"abstract":"<p>This study explores the historical presence of the El Niño-Southern Oscillation (ENSO) phenomenon during the Holocene and its impact on the Indian Summer Monsoon (ISM) and the East Asian Summer Monsoon (EAM). This investigation sheds light on an area with limited prior understanding. The primary objective is to analyse ISM variations from ~ 6000 to 1700 calibrated years before the Present (cal yr BP) and decipher their connection with the EAM. Sediment samples were obtained from core SK-291/GC-15, collected off the coast of Goa, and underwent comprehensive analysis, including examination of major, trace, and rare earth elements (REEs). The findings from geochemical proxies reveal that variations in sample compositions are primarily attributed to shifts in chemical weathering intensity rather than alterations in the source rock composition, and the sediments were deposited under consistent anoxic conditions. A noteworthy shift in the chemical weathering pattern was identified, particularly during the ~6000–4400 cal yr BP period, coinciding with the onset of intensified ISM around ~5400 cal yr BP. This intensified monsoon phase, recognised as the 5.4 ka event, coincides with the development of the Harappan civilisation, highlighting its historical significance. Notably, an inverse relationship between the ISM and EAM was observed during this 5.4 ka event – a phenomenon explained by the influence of ENSO on the Asian monsoon system.</p>","PeriodicalId":15609,"journal":{"name":"Journal of Earth System Science","volume":"2011 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141194351","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Machine learning assisted lithology prediction using geophysical logs: A case study from Cambay basin 使用地球物理测井的机器学习辅助岩性预测:柬埔寨盆地案例研究
IF 1.9 4区 地球科学 Q3 GEOSCIENCES, MULTIDISCIPLINARY Pub Date : 2024-05-30 DOI: 10.1007/s12040-024-02326-y
Rahul Prajapati, Bappa Mukherjee, Upendra K Singh, Kalachand Sain

Abstract

Identification and characterisation of reservoir facies is a prime factor in delimiting the hydrocarbon potential zones of a reservoir for hydrocarbon exploration. The geophysical logs, which are physical parameters of reservoir facies measured in the vicinity of boreholes, play a crucial role in the interpretation of reservoir facies. The present study deals with the identification of the lithology of the Limbodara oil field in the Cambay basin using machine learning (ML) techniques on geophysical logs. The supervised techniques of machine learning, such as support vector machines (SVM), artificial neural networks (ANN), and k-nearest neighbours (kNN), are used as nonlinear classifiers for the identification of lithology from nonlinear geophysical logs. The hyperparameters of the ML model are optimised using the grid search cross-validation (CV) method to increase the performance of the model, as evaluated by confusion matrix, area under receiver operating characteristics curve (AUC), precision, recall, and F1 score. The ML model used five geophysical parameters of two wells with four known distinguished lithologies (Class-A, Class-B, Class-C, and Class-D) for optimisation and training of the model. The optimised and trained model for each lithology for kNN, SVM, and ANN shows an overall correct prediction of true values with 85.4, 87.0, and 88.9%, respectively, from the confusion matrix. Apart from this, the receiver operative characteristics (ROC) also show that the overall area under the curve for each lithology is greater than 90%, and other evaluation parameters such as precision, recall, and F1 score show accuracy greater than 84%, except for the cases of Class C and Class D from SVM and ANN. Thus, the accuracy of each model from evaluation parameters suggests that the combined analysis of different ML models offers to select the optimised ML model for better results and validation to achieve and model the lithology with better precision.

Highlights

  • A way out for obtaining litholog supplements at uncored section in boreholes

  • Established ML assisted mapping function between wireline logs and lithologs

  • Predicted litholog sequence with secure level of accuracy (>80%)

摘要储油层面的识别和特征描述是油气勘探中划分储油层油气潜力区的首要因素。地球物理测井记录是在钻孔附近测量的储层岩相物理参数,在解释储层岩相方面起着至关重要的作用。本研究涉及利用地球物理测井的机器学习(ML)技术识别柬埔寨盆地林博达拉油田的岩性。机器学习的监督技术,如支持向量机(SVM)、人工神经网络(ANN)和 k-近邻(kNN),被用作非线性分类器,用于从非线性地球物理测井记录中识别岩性。使用网格搜索交叉验证(CV)方法对 ML 模型的超参数进行了优化,以提高模型的性能,评估指标包括混淆矩阵、接收者工作特性曲线下面积(AUC)、精确度、召回率和 F1 分数。ML 模型使用两口井的五个地球物理参数和四种已知的不同岩性(A 类、B 类、C 类和 D 类)来优化和训练模型。从混淆矩阵来看,kNN、SVM 和 ANN 针对每种岩性优化和训练的模型对真实值的预测正确率分别为 85.4%、87.0% 和 88.9%。此外,接受者操作特征(ROC)也显示,除 SVM 和 ANN 的 C 类和 D 类外,各岩性的整体曲线下面积均大于 90%,精度、召回率和 F1 分数等其他评价参数的准确度均大于 84%。因此,从评价参数来看,每个模型的精确度都表明,综合分析不同的 ML 模型,可以选择优化的 ML 模型,以获得更好的结果和验证,从而以更高的精确度实现岩性建模。 亮点获取钻孔无刻蚀段岩性补充的出路建立了线性测井和岩性之间的 ML 辅助绘图功能预测岩性序列的精确度达到了安全水平(80%)。
{"title":"Machine learning assisted lithology prediction using geophysical logs: A case study from Cambay basin","authors":"Rahul Prajapati, Bappa Mukherjee, Upendra K Singh, Kalachand Sain","doi":"10.1007/s12040-024-02326-y","DOIUrl":"https://doi.org/10.1007/s12040-024-02326-y","url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract</h3><p>Identification and characterisation of reservoir facies is a prime factor in delimiting the hydrocarbon potential zones of a reservoir for hydrocarbon exploration. The geophysical logs, which are physical parameters of reservoir facies measured in the vicinity of boreholes, play a crucial role in the interpretation of reservoir facies. The present study deals with the identification of the lithology of the Limbodara oil field in the Cambay basin using machine learning (ML) techniques on geophysical logs. The supervised techniques of machine learning, such as support vector machines (SVM), artificial neural networks (ANN), and k-nearest neighbours (kNN), are used as nonlinear classifiers for the identification of lithology from nonlinear geophysical logs. The hyperparameters of the ML model are optimised using the grid search cross-validation (CV) method to increase the performance of the model, as evaluated by confusion matrix, area under receiver operating characteristics curve (AUC), precision, recall, and F1 score. The ML model used five geophysical parameters of two wells with four known distinguished lithologies (Class-A, Class-B, Class-C, and Class-D) for optimisation and training of the model. The optimised and trained model for each lithology for kNN, SVM, and ANN shows an overall correct prediction of true values with 85.4, 87.0, and 88.9%, respectively, from the confusion matrix. Apart from this, the receiver operative characteristics (ROC) also show that the overall area under the curve for each lithology is greater than 90%, and other evaluation parameters such as precision, recall, and F1 score show accuracy greater than 84%, except for the cases of Class C and Class D from SVM and ANN. Thus, the accuracy of each model from evaluation parameters suggests that the combined analysis of different ML models offers to select the optimised ML model for better results and validation to achieve and model the lithology with better precision.</p><h3 data-test=\"abstract-sub-heading\">Highlights</h3><ul>\u0000<li>\u0000<p>A way out for obtaining litholog supplements at uncored section in boreholes</p>\u0000</li>\u0000<li>\u0000<p>Established ML assisted mapping function between wireline logs and lithologs</p>\u0000</li>\u0000<li>\u0000<p>Predicted litholog sequence with secure level of accuracy (&gt;80%)</p>\u0000</li>\u0000</ul>","PeriodicalId":15609,"journal":{"name":"Journal of Earth System Science","volume":"329 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141194257","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Spatial and temporal trend analysis of rainfall in Nagaland (India) using machine learning techniques 利用机器学习技术分析印度那加兰邦降雨量的时空趋势
IF 1.9 4区 地球科学 Q3 GEOSCIENCES, MULTIDISCIPLINARY Pub Date : 2024-05-28 DOI: 10.1007/s12040-024-02320-4
Santosh Pathak, Mhalevonuo Chielie, Y Satish, B C Kusre

Rainfall plays a vital role in the field of agriculture as it affects agricultural production and associated economy. However, the changing trend of rainfall has become a global concern. So the study of changes in the trend of rainfall is necessary. In the present study, an innovative trend analysis method was adopted to assess the changing trend in the state of Nagaland. Data of 40 years was taken for performing the trend analysis using ITA. The entire process of trend change analysis was automated using Python programming. The analysis indicated that out of the 11 stations considered, three stations indicated a rising trend, eight indicated falling trends (annual), four rising and seven falling (monsoon), 0 rising and 11 falling (winter). The extent of trend change varied from –34.5 to 1.1. The spatial distribution of the trend change was also performed. It was observed that the southeast part of Nagaland’s rising trend was more pronounced compared to the southwest. The change was more prominent during the winter season followed by pre-monsoon and monsoon. The trend analysis is important for making appropriate water management decisions, such as water conservation in areas with falling trends and soil conservation in areas affected by rising trends.

降雨在农业领域发挥着至关重要的作用,因为它影响着农业生产和相关经济。然而,降雨趋势的变化已成为全球关注的问题。因此,有必要对降雨趋势的变化进行研究。本研究采用了一种创新的趋势分析方法来评估那加兰邦的变化趋势。在使用 ITA 进行趋势分析时,采用了 40 年的数据。整个趋势变化分析过程使用 Python 程序自动完成。分析结果表明,在所考虑的 11 个站点中,3 个站点呈上升趋势,8 个站点呈下降趋势(年度),4 个站点呈上升趋势,7 个站点呈下降趋势(季风),0 个站点呈上升趋势,11 个站点呈下降趋势(冬季)。趋势变化范围从-34.5 到 1.1 不等。此外,还对趋势变化的空间分布进行了研究。据观察,与西南部相比,那加兰邦东南部的上升趋势更为明显。这种变化在冬季更为明显,其次是季风前和季风季节。趋势分析对于做出适当的水资源管理决策非常重要,例如在趋势下降的地区进行水资源保护,以及在受趋势上升影响的地区进行土壤保护。
{"title":"Spatial and temporal trend analysis of rainfall in Nagaland (India) using machine learning techniques","authors":"Santosh Pathak, Mhalevonuo Chielie, Y Satish, B C Kusre","doi":"10.1007/s12040-024-02320-4","DOIUrl":"https://doi.org/10.1007/s12040-024-02320-4","url":null,"abstract":"<p>Rainfall plays a vital role in the field of agriculture as it affects agricultural production and associated economy. However, the changing trend of rainfall has become a global concern. So the study of changes in the trend of rainfall is necessary. In the present study, an innovative trend analysis method was adopted to assess the changing trend in the state of Nagaland. Data of 40 years was taken for performing the trend analysis using ITA. The entire process of trend change analysis was automated using Python programming. The analysis indicated that out of the 11 stations considered, three stations indicated a rising trend, eight indicated falling trends (annual), four rising and seven falling (monsoon), 0 rising and 11 falling (winter). The extent of trend change varied from –34.5 to 1.1. The spatial distribution of the trend change was also performed. It was observed that the southeast part of Nagaland’s rising trend was more pronounced compared to the southwest. The change was more prominent during the winter season followed by pre-monsoon and monsoon. The trend analysis is important for making appropriate water management decisions, such as water conservation in areas with falling trends and soil conservation in areas affected by rising trends.</p>","PeriodicalId":15609,"journal":{"name":"Journal of Earth System Science","volume":"30 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141170895","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Downscaling algorithms for CMIP6 GCM daily rainfall over India 印度 CMIP6 GCM 日降雨量的降尺度算法
IF 1.9 4区 地球科学 Q3 GEOSCIENCES, MULTIDISCIPLINARY Pub Date : 2024-05-28 DOI: 10.1007/s12040-024-02323-1
Rajendra Raj, Degavath Vinod, Amai Mahesha

The global climate models (GCMs) are sophisticated tools for determining how the climate system will respond. However, the output of GCMs has a coarse resolution, which is unsuitable for basin-level modelling. Global climate models need to be downscaled at a local/basin scale to determine the impacts of climate change on hydrological responses. The present study attempted to evaluate how effectively various large-scale predictors could reproduce local-scale rain in 35 different locations in India using artificial neural networks (ANN), change-factors (CF), K-nearest neighbour (KNN), and multiple linear regression (MLR). The selection of predictors is made based on the correlation value. As potential predictors, air temperature, geo-potential height, wind velocity component, and relative humidity at specific mean sea-level pressure are selected. The comparison of four different downscaling methods concerning the reproduction of various statistics such as mean, standard deviation at chosen locations, quantile–quantile plots, cumulative distribution function, and kernel density estimation of the PDFs of daily rainfall for selected stations is examined. The CF approach outperforms the other methods at almost all sites (R2 = 0.92–0.99, RMSE = 1.37–28.88 mm, and NSE = –16.55–0.99). This also closely resembles the probability distribution pattern of IMD data.

全球气候模型(GCMs)是确定气候系统如何反应的精密工具。然而,全球气候模型的输出分辨率较低,不适合流域尺度的建模。全球气候模型需要在地方/流域尺度上进行缩减,以确定气候变化对水文响应的影响。本研究试图利用人工神经网络 (ANN)、变化因子 (CF)、K-近邻 (KNN) 和多元线性回归 (MLR),评估各种大尺度预测因子如何有效地再现印度 35 个不同地点的地方尺度降雨。预测因子的选择基于相关值。作为潜在的预测因子,选择了气温、地电位高度、风速分量和特定平均海平面气压下的相对湿度。比较了四种不同的降尺度方法对各种统计数据的再现情况,如选定地点的平均值、标准偏差、矩阵-矩阵图、累积分布函数以及选定站点日降雨量 PDF 的核密度估计。在几乎所有站点,CF 方法都优于其他方法(R2 = 0.92-0.99,RMSE = 1.37-28.88 毫米,NSE = -16.55-0.99)。这也与 IMD 数据的概率分布模式非常相似。
{"title":"Downscaling algorithms for CMIP6 GCM daily rainfall over India","authors":"Rajendra Raj, Degavath Vinod, Amai Mahesha","doi":"10.1007/s12040-024-02323-1","DOIUrl":"https://doi.org/10.1007/s12040-024-02323-1","url":null,"abstract":"<p>The global climate models (GCMs) are sophisticated tools for determining how the climate system will respond. However, the output of GCMs has a coarse resolution, which is unsuitable for basin-level modelling. Global climate models need to be downscaled at a local/basin scale to determine the impacts of climate change on hydrological responses. The present study attempted to evaluate how effectively various large-scale predictors could reproduce local-scale rain in 35 different locations in India using artificial neural networks (ANN), change-factors (CF), K-nearest neighbour (KNN), and multiple linear regression (MLR). The selection of predictors is made based on the correlation value. As potential predictors, air temperature, geo-potential height, wind velocity component, and relative humidity at specific mean sea-level pressure are selected. The comparison of four different downscaling methods concerning the reproduction of various statistics such as mean, standard deviation at chosen locations, quantile–quantile plots, cumulative distribution function, and kernel density estimation of the PDFs of daily rainfall for selected stations is examined. The CF approach outperforms the other methods at almost all sites (<i>R</i><sup>2</sup> = 0.92–0.99, RMSE = 1.37–28.88 mm, and NSE = –16.55–0.99). This also closely resembles the probability distribution pattern of IMD data.</p>","PeriodicalId":15609,"journal":{"name":"Journal of Earth System Science","volume":"7 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141170892","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Analysis of temperature and rainfall trends in Beni City, Democratic Republic of Congo 刚果民主共和国贝尼市气温和降雨趋势分析
IF 1.9 4区 地球科学 Q3 GEOSCIENCES, MULTIDISCIPLINARY Pub Date : 2024-05-27 DOI: 10.1007/s12040-024-02308-0
Vithundwa Richard Posite, Bayongwa Samuel Ahana, Chérifa Abdelbaki, Abdellatif Zerga, Awoke Guadie

Abstract

Understanding local-scale climate change is vital to developing adaptive strategies in the face of the century-old river of global warming posing a threat to humanity. This study focuses on assessing temperature and rainfall trends in Beni City, using monthly and yearly (1990–2020) weather station data. Climate variability was analysed using the standardised variable index, and rainfall concentration patterns were highlighted using the precipitation concentration index (PCI). The climate trends were analysed by using the Mann–Kendall test and Sen's slope estimator. The findings indicated that the Tmin is 18.82±0.62°C, and Tmax is 28.22±0.75°C, resulting in a mean temperature of 23.52±0.57°C. The annual and seasonal temperature trend analysis indicated that a significant warming trend was observed in both Tmin and Tmax. Beni City's precipitation trends also showed a mean annual rainfall of 1988.38±416.59 mm, with significant year-to-year variations. Annual rainfall analysis exhibited a slight upward trend; meanwhile, the seasonal trend analysis revealed an increase in rainfall during Mar–Apr–May (MAM) and Aug–Sep–Oct–Nov (ASON) seasons with roughly no discernible trend during Dec–Jan–Feb (DJF), and Jun–Jul (JJ) seasons. Overall, annual and seasonal analyses of specific temperature and rainfall patterns have shown pronounced warming and increased rainfall in the study area.

Research highlights

  • The study reveals significant trends in temperature and rainfall in Beni city, Democratic Republic of Congo, over a 31-year period (1990–2020).

  • Both minimum and maximum temperatures show significant warming trends, with the most recent decade witnessing substantial increases in maximum temperatures.

  • Rainfall patterns exhibit variations, with a slight upward trend in annual rainfall, although the 1990s experienced a notable decrease in precipitation.

  • Monthly analyses highlight specific temperature and rainfall patterns with some months experiencing pronounced warming and increased rainfall.

摘要 面对全球变暖对人类构成威胁的百年大河,了解当地尺度的气候变化对制定适应战略至关重要。本研究利用每月和每年(1990-2020 年)的气象站数据,重点评估贝尼市的气温和降雨趋势。使用标准化变量指数分析气候变异性,使用降水集中指数(PCI)突出降水集中模式。使用 Mann-Kendall 检验和 Sen 的斜率估计器分析了气候趋势。结果表明,Tmin 为 18.82±0.62°C,Tmax 为 28.22±0.75°C,平均气温为 23.52±0.57°C。年和季节气温趋势分析表明,Tmin 和 Tmax 均有明显的变暖趋势。贝尼市的降水趋势也显示,年平均降水量为 1988.38±416.59 毫米,年际变化显著。年降雨量分析显示出轻微的上升趋势;同时,季节趋势分析显示,3 月-4 月-5 月(MAM)和 8 月-9 月-10 月-11 月(ASON)季节的降雨量有所增加,而 12 月-1 月-2 月(DJF)和 6 月-7 月(JJ)季节的降雨量基本没有明显趋势。总体而言,对特定气温和降雨模式的年度和季节分析表明,该研究地区的气温明显升高,降雨量明显增加。 研究重点 该研究揭示了刚果民主共和国贝尼市 31 年间(1990-2020 年)气温和降雨量的显著变化趋势。月度分析突出显示了特定的气温和降雨模式,有些月份的气温明显升高,降雨量明显增加。
{"title":"Analysis of temperature and rainfall trends in Beni City, Democratic Republic of Congo","authors":"Vithundwa Richard Posite, Bayongwa Samuel Ahana, Chérifa Abdelbaki, Abdellatif Zerga, Awoke Guadie","doi":"10.1007/s12040-024-02308-0","DOIUrl":"https://doi.org/10.1007/s12040-024-02308-0","url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract</h3><p>Understanding local-scale climate change is vital to developing adaptive strategies in the face of the century-old river of global warming posing a threat to humanity. This study focuses on assessing temperature and rainfall trends in Beni City, using monthly and yearly (1990–2020) weather station data. Climate variability was analysed using the standardised variable index, and rainfall concentration patterns were highlighted using the precipitation concentration index (PCI). The climate trends were analysed by using the Mann–Kendall test and Sen's slope estimator. The findings indicated that the <i>T</i><sub>min</sub> is 18.82±0.62°C, and <i>T</i><sub>max</sub> is 28.22±0.75°C, resulting in a mean temperature of 23.52±0.57°C. The annual and seasonal temperature trend analysis indicated that a significant warming trend was observed in both <i>T</i><sub>min</sub> and <i>T</i><sub>max</sub>. Beni City's precipitation trends also showed a mean annual rainfall of 1988.38±416.59 mm, with significant year-to-year variations. Annual rainfall analysis exhibited a slight upward trend; meanwhile, the seasonal trend analysis revealed an increase in rainfall during Mar–Apr–May (MAM) and Aug–Sep–Oct–Nov (ASON) seasons with roughly no discernible trend during Dec–Jan–Feb (DJF), and Jun–Jul (JJ) seasons. Overall, annual and seasonal analyses of specific temperature and rainfall patterns have shown pronounced warming and increased rainfall in the study area.</p><h3 data-test=\"abstract-sub-heading\">Research highlights</h3><ul>\u0000<li>\u0000<p>The study reveals significant trends in temperature and rainfall in Beni city, Democratic Republic of Congo, over a 31-year period (1990–2020).</p>\u0000</li>\u0000<li>\u0000<p>Both minimum and maximum temperatures show significant warming trends, with the most recent decade witnessing substantial increases in maximum temperatures.</p>\u0000</li>\u0000<li>\u0000<p>Rainfall patterns exhibit variations, with a slight upward trend in annual rainfall, although the 1990s experienced a notable decrease in precipitation.</p>\u0000</li>\u0000<li>\u0000<p>Monthly analyses highlight specific temperature and rainfall patterns with some months experiencing pronounced warming and increased rainfall.</p>\u0000</li>\u0000</ul>","PeriodicalId":15609,"journal":{"name":"Journal of Earth System Science","volume":"68 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141170898","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
U–Pb zircon geochronology of the Proterozoic siliciclastic stratal succession of the Kumaun Lesser Himalaya: Implications for regional stratigraphic correlation 库马恩小喜马拉雅山新生代硅质岩地层演替的U-Pb锆石地质年代学:对区域地层关联的影响
IF 1.9 4区 地球科学 Q3 GEOSCIENCES, MULTIDISCIPLINARY Pub Date : 2024-05-27 DOI: 10.1007/s12040-024-02309-z
Poonam Jalal, Sumit K Ghosh, Mohit Puniya, Gajender Kumar

Abstract

The siliciclastics make the major part of the Proterozoic Kumaun Lesser Himalaya region. These share similar appearance, sedimentology, and petrography. In the absence of fossils and any other age constraint, these are named differently in literature, i.e., Nagthat, Bhowali, Lariakantha, and Berinag quartzites, based on their locality, sedimentological and petrographical characteristics. Their stratal disposition and their regional correlation are always debatable. The present work addresses the stratal disposition of these Proterozoic siliciclastics using the detrital zircon (DZ) U–Pb geochronology. The study suggests that the siliciclastics of Bhowali, Lariakantha, Nagthat and Berinag in the Kumaun region are equivalent and show the maximum depositional age (MDA) of ~1850 Ma. However, the Nagthat Formation in Garhwal Lesser Himalaya has a Neoproterozoic DZ depositional age (~850 Ma) and is a different identity. This study suggests that in the Kumaun Lesser region (inner and outer), only Palaeoproterozoic siliciclastic is present. Also, they can be grouped under Berinag with its implications about the inner and outer Lesser Himalayan division and the relationship with younger strata of Blaini Formation.

Research highlights

  • U-Pb Detrital zircon geochronology from siliciclastics, Kumaun Lesser Himalaya (inner and outer) region

  • Only Palaeoproterozoic detrital zircon ages for Kumaun Lesser region (both inner (ILH) and outer (OLH))

  • Continuous Paleoproterozoic sedimentation in a single basin

摘要硅质岩构成了新生代库曼小喜马拉雅地区的主要部分。它们具有相似的外观、沉积学和岩相学。由于缺乏化石和其他任何年龄限制因素,文献根据它们的地点、沉积学和岩相学特征对它们进行了不同的命名,即 Nagthat、Bhowali、Lariakantha 和 Berinag 石英岩。它们的地层分布及其区域相关性一直存在争议。本研究利用碎屑锆石(DZ)U-Pb 地球地质年代学研究了这些新生代硅质岩的地层分布。研究表明,库马恩地区的Bhowali、Lariakantha、Nagthat和Berinag硅质岩相等同,最大沉积年龄(MDA)约为1850Ma。然而,小喜马拉雅山脉加瓦尔地区的 Nagthat 地层具有新近新生代 DZ 沉积年龄(约 850 Ma),是一个不同的身份。这项研究表明,在库马恩小喜马拉雅地区(内部和外部),只存在古新生代硅质碎屑岩。研究重点库马恩小喜马拉雅山(内、外)地区硅碎屑岩的锆石地质年代U-Pb锆石碎屑岩地质年代库马恩小喜马拉雅山(内、外)地区只有古生代锆石碎屑岩地质年代(内(ILH)和外(OLH))单一盆地的连续古生代沉积作用
{"title":"U–Pb zircon geochronology of the Proterozoic siliciclastic stratal succession of the Kumaun Lesser Himalaya: Implications for regional stratigraphic correlation","authors":"Poonam Jalal, Sumit K Ghosh, Mohit Puniya, Gajender Kumar","doi":"10.1007/s12040-024-02309-z","DOIUrl":"https://doi.org/10.1007/s12040-024-02309-z","url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract</h3><p>The siliciclastics make the major part of the Proterozoic Kumaun Lesser Himalaya region. These share similar appearance, sedimentology, and petrography. In the absence of fossils and any other age constraint, these are named differently in literature, i.e., Nagthat, Bhowali, Lariakantha, and Berinag quartzites, based on their locality, sedimentological and petrographical characteristics. Their stratal disposition and their regional correlation are always debatable. The present work addresses the stratal disposition of these Proterozoic siliciclastics using the detrital zircon (DZ) U–Pb geochronology. The study suggests that the siliciclastics of Bhowali, Lariakantha, Nagthat and Berinag in the Kumaun region are equivalent and show the maximum depositional age (MDA) of ~1850 Ma. However, the Nagthat Formation in Garhwal Lesser Himalaya has a Neoproterozoic DZ depositional age (~850 Ma) and is a different identity. This study suggests that in the Kumaun Lesser region (inner and outer), only Palaeoproterozoic siliciclastic is present. Also, they can be grouped under Berinag with its implications about the inner and outer Lesser Himalayan division and the relationship with younger strata of Blaini Formation.</p><h3 data-test=\"abstract-sub-heading\">Research highlights</h3>\u0000<ul>\u0000<li>\u0000<p>U-Pb Detrital zircon geochronology from siliciclastics, Kumaun Lesser Himalaya (inner and outer) region</p>\u0000</li>\u0000<li>\u0000<p>Only Palaeoproterozoic detrital zircon ages for Kumaun Lesser region (both inner (ILH) and outer (OLH))</p>\u0000</li>\u0000<li>\u0000<p>Continuous Paleoproterozoic sedimentation in a single basin</p>\u0000</li>\u0000</ul>","PeriodicalId":15609,"journal":{"name":"Journal of Earth System Science","volume":"98 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141171384","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Understanding Joshimath landslide using PS interferometry and PSDS InSAR 利用 PS 干涉测量法和 PSDS InSAR 了解乔希马什山体滑坡
IF 1.9 4区 地球科学 Q3 GEOSCIENCES, MULTIDISCIPLINARY Pub Date : 2024-05-18 DOI: 10.1007/s12040-024-02312-4
Asrar Ahmad Rather, Syed Kaiser Bukhari

The recent subsidence at Joshimath in the Indian State of Uttarakhand led to the displacement of thousands of residents. Large cracks developed in the buildings and on the ground. No extensive and comprehensive deformation measurement of this event has been made. In this study, we use both PS and PSDS InSAR time series to investigate the magnitude, spatiotemporal as well as kinematic evolution of this slow-moving landslide. Eighty-seven ascending Sentinel-1 scenes with a temporal baseline of 1056 days from 2020 to 2023 were stacked for interferometric analysis. StaMPS is employed to identify PS points by their amplitude and phase information. TomoSAR is utilized to stipulate a coherence matrix to form a dense PSDS network of interferograms to surge point density for suitable phase unwrapping. PS and DS points are coupled to develop slope velocity maps revealing mean displacement rates of –84 mm for PS and –107 mm for PSDS, respectively. Cross-section profiles drawn on the slopes of subsidence show target scatterers on CS1, CS2 and CS4, yield a cumulative displacement of 400 mm in the last 3 years. CS3 and CS5 show a total displacement of about 350 mm. This study applies PSDS time-series InSAR to decipher ground movement in traditionally decohered environments. It also seeks to establish the boundaries and intensity of subsidence to aid in the mitigation of failure progression.

印度北阿坎德邦乔希马什最近发生的地陷导致数千居民流离失所。建筑物和地面都出现了大裂缝。目前尚未对这一事件进行广泛而全面的变形测量。在这项研究中,我们使用 PS 和 PSDS InSAR 时间序列来研究这次缓慢移动的山体滑坡的规模、时空和运动学演变。我们对 2020 年至 2023 年期间时间基线为 1056 天的 87 个上升哨兵-1 景象进行了叠加,以进行干涉分析。利用 StaMPS 通过振幅和相位信息识别 PS 点。利用 TomoSAR 规定相干矩阵,形成密集的 PSDS 干涉图网络,以激增点密度,从而进行适当的相位解包。将 PS 点和 DS 点耦合起来,绘制斜坡速度图,显示 PS 和 PSDS 的平均位移率分别为 -84 毫米和 -107 毫米。在下沉斜坡上绘制的横截面剖面图显示,CS1、CS2 和 CS4 上的目标散射体在过去 3 年中产生了 400 毫米的累计位移。CS3 和 CS5 的总位移量约为 350 毫米。本研究应用 PSDS 时间序列 InSAR 来破译传统解译环境中的地面运动。该研究还试图确定沉降的边界和强度,以帮助减轻破坏的进展。
{"title":"Understanding Joshimath landslide using PS interferometry and PSDS InSAR","authors":"Asrar Ahmad Rather, Syed Kaiser Bukhari","doi":"10.1007/s12040-024-02312-4","DOIUrl":"https://doi.org/10.1007/s12040-024-02312-4","url":null,"abstract":"<p>The recent subsidence at Joshimath in the Indian State of Uttarakhand led to the displacement of thousands of residents. Large cracks developed in the buildings and on the ground. No extensive and comprehensive deformation measurement of this event has been made. In this study, we use both PS and PSDS InSAR time series to investigate the magnitude, spatiotemporal as well as kinematic evolution of this slow-moving landslide. Eighty-seven ascending Sentinel-1 scenes with a temporal baseline of 1056 days from 2020 to 2023 were stacked for interferometric analysis. StaMPS is employed to identify PS points by their amplitude and phase information. TomoSAR is utilized to stipulate a coherence matrix to form a dense PSDS network of interferograms to surge point density for suitable phase unwrapping. PS and DS points are coupled to develop slope velocity maps revealing mean displacement rates of –84 mm for PS and –107 mm for PSDS, respectively. Cross-section profiles drawn on the slopes of subsidence show target scatterers on CS1, CS2 and CS4, yield a cumulative displacement of 400 mm in the last 3 years. CS3 and CS5 show a total displacement of about 350 mm. This study applies PSDS time-series InSAR to decipher ground movement in traditionally decohered environments. It also seeks to establish the boundaries and intensity of subsidence to aid in the mitigation of failure progression.</p>","PeriodicalId":15609,"journal":{"name":"Journal of Earth System Science","volume":"51 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141059473","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
期刊
Journal of Earth System Science
全部 Acc. Chem. Res. ACS Applied Bio Materials ACS Appl. Electron. Mater. ACS Appl. Energy Mater. ACS Appl. Mater. Interfaces ACS Appl. Nano Mater. ACS Appl. Polym. Mater. ACS BIOMATER-SCI ENG ACS Catal. ACS Cent. Sci. ACS Chem. Biol. ACS Chemical Health & Safety ACS Chem. Neurosci. ACS Comb. Sci. ACS Earth Space Chem. ACS Energy Lett. ACS Infect. Dis. ACS Macro Lett. ACS Mater. Lett. ACS Med. Chem. Lett. ACS Nano ACS Omega ACS Photonics ACS Sens. ACS Sustainable Chem. Eng. ACS Synth. Biol. Anal. Chem. BIOCHEMISTRY-US Bioconjugate Chem. BIOMACROMOLECULES Chem. Res. Toxicol. Chem. Rev. Chem. Mater. CRYST GROWTH DES ENERG FUEL Environ. Sci. Technol. Environ. Sci. Technol. Lett. Eur. J. Inorg. Chem. IND ENG CHEM RES Inorg. Chem. J. Agric. Food. Chem. J. Chem. Eng. Data J. Chem. Educ. J. Chem. Inf. Model. J. Chem. Theory Comput. J. Med. Chem. J. Nat. Prod. J PROTEOME RES J. Am. Chem. Soc. LANGMUIR MACROMOLECULES Mol. Pharmaceutics Nano Lett. Org. Lett. ORG PROCESS RES DEV ORGANOMETALLICS J. Org. Chem. J. Phys. Chem. J. Phys. Chem. A J. Phys. Chem. B J. Phys. Chem. C J. Phys. Chem. Lett. Analyst Anal. Methods Biomater. Sci. Catal. Sci. Technol. Chem. Commun. Chem. Soc. Rev. CHEM EDUC RES PRACT CRYSTENGCOMM Dalton Trans. Energy Environ. Sci. ENVIRON SCI-NANO ENVIRON SCI-PROC IMP ENVIRON SCI-WAT RES Faraday Discuss. Food Funct. Green Chem. Inorg. Chem. Front. Integr. Biol. J. Anal. At. Spectrom. J. Mater. Chem. A J. Mater. Chem. B J. Mater. Chem. C Lab Chip Mater. Chem. Front. Mater. Horiz. MEDCHEMCOMM Metallomics Mol. Biosyst. Mol. Syst. Des. Eng. Nanoscale Nanoscale Horiz. Nat. Prod. Rep. New J. Chem. Org. Biomol. Chem. Org. Chem. Front. PHOTOCH PHOTOBIO SCI PCCP Polym. Chem.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1