Journal of Earth System Science最新文献

{"title":"Evidence of a Proterozoic suture along the southern part of Eastern Ghats Mobile Belt: Implications for the Nuna supercontinent","authors":"Yellalacheruvu Giri, M Radhakrishna, Peter Betts, T K Biswal, Robin Armit, Sumanta Kumar Sathapathy, P U Naveen","doi":"10.1007/s12040-024-02396-y","DOIUrl":"https://doi.org/10.1007/s12040-024-02396-y","url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract</h3><p>The Mesoproterozoic rocks of the Krishna Province in the Eastern Ghats Mobile Belt are situated at the edge of the Indian interior cratons and the mobile belts along the edge. We use newly acquired high-resolution gravity and magnetic along with the regional geophysical data to delineate the faults, lineaments, and subsurface boundaries between the various domains of the Krishna Province. We use this data to forward model the crustal architecture below these terranes. Our analysis shows that the Ongole domain rocks are continuing further southwards up to the Nellore and below the K–G Basin on the north side at subsurface levels. The Vinjamur and Udayagiri domains of the Krishna Province are merged into a single narrow belt known as the Nellore–Khammam Schist Belt. The joint 2D modelling of the gravity and magnetic data across these domains reveals two easterly dipping parallel thrusts separating the Dharwar–Nellore–Khammam Schist Belt and Nellore–Khammam Schist Belt–Eastern Ghats Mobile Belt, respectively. The interpreted suture between the Nellore–Khammam Schist Belt and Ongole domain of EGMB is characterized by the ophiolite and alkaline complexes of Mesoproterozoic ages. We propose that the collision between the Krishna Province and Indian Cratons occurred during the Nuna amalgamation.</p><h3 data-test=\"abstract-sub-heading\">Research highlights</h3><ul>\u0000<li>\u0000<p>The detailed crustal structure across the Dharwar Craton and EGMB was analyzed using geophysical data.</p>\u0000</li>\u0000<li>\u0000<p>Redefined the boundaries between the various domains of the Krishna Province.</p>\u0000</li>\u0000<li>\u0000<p>A paleo suture was identified between the Eastern Ghats Mobile Belt and the Nellore–Khammam Schist Belt.</p>\u0000</li>\u0000</ul>","PeriodicalId":15609,"journal":{"name":"Journal of Earth System Science","volume":"53 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142262446","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}

{"title":"Integration of machine learning and remote sensing for assessing the change detection of mangrove forests along the Mumbai coast","authors":"Suraj Sawant, Praneetha Bonala, Amit Joshi, Mahesh Shindikar, Abhilasha Patil, Swapnil Vyas, Deepti Deobagkar","doi":"10.1007/s12040-024-02378-0","DOIUrl":"https://doi.org/10.1007/s12040-024-02378-0","url":null,"abstract":"<p>Mangrove forests, being high-yielding ecosystems, often dominate the intertidal sites along equatorial and subtropical coasts. Despite the known significance of mangroves to the coastal ecology, especially fisheries, deforestation remains a severe danger due to coercion for forest products, ground transformation for aquaculture, and seaside urban growth. Remote sensing is integral in mapping and analysing changes in mangrove forests’ areal extent and spatial patterns due to natural disasters and anthropogenic causes over the last three decades. This work depicts remote sensing analysis for change detection in mangrove forest land use land cover from 2014 to 2019. Indian Remote-Sensing Satellite Resourcesat-2 LISS-IV datasets have been used for analysis. A comparison with the Sentinel-2A dataset and two machine learning models: Random Forest and Classification and Regression Tree, has been performed with 2019 data. This work identifies CART as a suitable choice for supervised landform classification utilising remotely sensed geophysical data that is used to decipher spatial changes concurred over time. An overall growth in the mangrove cover was observed from 2014 to 2019, from 86.26 to 89.63 <span>({hbox {km}^{2}})</span>, along the Mumbai coastline. Spatial comparison over the years shows the growth and loss of land-use cover areas. The performance metrics such as overall accuracy, producer accuracy, Kappa coefficient, and Matthews correlation coefficient are computed. The experiments were conducted using the Google Earth Engine, a powerful cloud computing platform.</p>","PeriodicalId":15609,"journal":{"name":"Journal of Earth System Science","volume":"30 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142262491","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}

{"title":"Impact assessment of precipitation and temperature trends on crop yield in water stress zone of Bundelkhand, India","authors":"Rahul Dwivedi, Vivek Kumar, Deepak Khare","doi":"10.1007/s12040-024-02382-4","DOIUrl":"https://doi.org/10.1007/s12040-024-02382-4","url":null,"abstract":"<p>The study of the statistical trends on rainfall and temperature is much more efficient for hydrological design and planning for scarce water availability zones. In the present study, the sequential Mann–Kendall test (SqMKT) on the Mat-Lab platform is used to study the pattern of rainfall series and temperature series data of the Tikamgarh area of India, surrounded by five stations (nearby) from 2000 to 2020. The SqMKT is mainly used to perform non-linear trends on the rainfall and temperature series. In the SqMKT analysis on rainfall series projects, there was no significant trend in all months, except in the month of June. These months have intersecting points, and each point has <i>Z</i> values in the range of –0.5 &lt; <i>Z</i> &lt; 1.5. The SqMKT analysis on the temperature series shows a significant trend in the months of April, June, July and December, respectively, whereas the remaining months do not have any pattern or trend, similar to the rainfall series and temperature series have <i>u</i> values in the range of –0.5 &lt; <i>u</i> &lt; 1.5. The global climatic pattern is somewhat directly or indirectly connected to the Indian climate pattern, which results in variations in rainfall and temperature patterns from year to year. The indefinite variation in rainfall and temperature results in a direct impact on crop yield and crop water demand or total water availability.</p>","PeriodicalId":15609,"journal":{"name":"Journal of Earth System Science","volume":"3 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142262444","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}

{"title":"Chrono-environmental dynamics of Yercaud Lake sediments (Eastern Ghats, South India) over the last 2500 years: Insights from AMS radiocarbon dating, particle size distribution, and stable isotope composition","authors":"Gopal Veeramalai, Hema Achyuthan, Christopher Eastoe","doi":"10.1007/s12040-024-02371-7","DOIUrl":"https://doi.org/10.1007/s12040-024-02371-7","url":null,"abstract":"<p>A 40-cm core of lake-bottom silt from Yercaud Lake (Eastern Ghats, south India) dates from 2500 years ago to the present, as confirmed by AMS radiocarbon dating. The average deposition rate varied from 0.024 to 0.008 cm/yr. Sediment particle size distribution, stable isotopes (<i>δ</i>¹³C and <i>δ</i>¹⁵N), C/N, and total organic carbon (TOC) were investigated as indicators of environmental change. In the top 10 cm are the coarsest sediments, which range from silt to silty sand and have a TOC of up to 5%. Algal lacustrine organic matter is combined with terrestrial or wetland organic matter from vascular plants to form organic matter (OM) with a C/N ratio of 12–18. High C/N levels are associated with low ¹³C and high TOC contents, indicating periods of drier climate between 0–500 and 800–2000 years BP. Grain-size characteristics, which fluctuate independently of OM qualities, are likely to have changed because of intensive human use of the lake basin in the past 600 years. Climate changes observed in OM do not correspond to changes observed in other south Indian lakes where precipitation is primarily from the southwest monsoon.</p>","PeriodicalId":15609,"journal":{"name":"Journal of Earth System Science","volume":"27 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142262447","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}

{"title":"Spatio-temporal changes in b-value associated with the 2023 Türkiye earthquake","authors":"Fahriye Akar","doi":"10.1007/s12040-024-02398-w","DOIUrl":"https://doi.org/10.1007/s12040-024-02398-w","url":null,"abstract":"<p>b-value analysis obtained using earthquake catalogues has been associated with stress accumulation for a very long time. In this study, the spatial and temporal distribution of the b-value, also known as the frequency magnitude distribution factor, was calculated and examined before and after the February 6, 2023, Kahramanmaraş earthquakes (Mw 7.7 and Mw 7.6). For this, all earthquakes that occurred between 1900 and the earthquakes of February 6, 2023, and all aftershocks that occurred until September 1, 2023, were used. A circular area with a radius of 300 km, including nearby active faults from the center of the first earthquake to the center of the second earthquake, was divided into grids of equal size. The b-value was calculated for each grid using the maximum likelihood method. Very low b values were detected in the area where the first earthquake occurred, and it was observed that the b-value decreased relatively in the area where the second earthquake occurred. From the change in b-value over time, it was determined that the b-value has decreased significantly in recent years. This situation is associated with stress accumulation in the area where both earthquakes occurred, especially the low b values of the region where the first earthquake occurred. The fact that b values obtained using aftershocks are still low suggests that stress in the region is not completely released, has not been completely relieved and aftershocks will continue for a long time.</p>","PeriodicalId":15609,"journal":{"name":"Journal of Earth System Science","volume":"8 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142262445","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}

{"title":"Identifying and detecting causes of changes in spatial patterns of extreme rainfall in southwestern Iran","authors":"Esmaeil Abbasi, Hana Etemadi, Mohammad Hassan Mahoutchi, Morteza Khalaj, Ali Torabi Haghighi","doi":"10.1007/s12040-024-02400-5","DOIUrl":"https://doi.org/10.1007/s12040-024-02400-5","url":null,"abstract":"&lt;h3 data-test=\"abstract-sub-heading\"&gt;Abstract&lt;/h3&gt;&lt;p&gt;Extreme rainfall in southwestern Iran annually leads to considerable financial and human losses. Reports over several years show different levels of damage caused by these events. This study aims to identify and investigate changes in the spatial patterns of systems that generate extreme rainfall in southwestern Iran. We utilized the maximum 24-hr precipitation from seven synoptic stations in southwestern Iran from 1971 to 2020. The principal component analysis technique was utilized on geopotential height data at 500 hpa to identify spatial patterns of precipitation. The data was collected from 5° to 60°N and 10° to 70°E that were received from the NCEP/NCAR reanalysis dataset. The study period was divided into two based on the identified change point by the Pettitt test, and according to the results, the first climatic period in southwestern Iran had nine sources or components of extreme rainfall. In comparison, in the second period, they had eight sources of extreme rainfall. The most important source of extreme rainfall for both periods and the first source of the second period are located at 15° north latitude over the Indian Ocean, the Arabian Sea, the southern Red Sea, the Gulf of Aden, and certain areas in the eastern tropical regions of Africa.&lt;/p&gt;&lt;h3 data-test=\"abstract-sub-heading\"&gt;Research highlights&lt;/h3&gt;&lt;p&gt;As a result, the statistical period was divided into two periods of 21 and 29 years. The first period, which includes 82 extreme rainfall events, spans from 1971 to 1991, and the second period, which provides 96 extreme rainfall events, spans from 1992 to 2020. The most important source of extreme rainfall for both periods and the first source of the second period are located at 15º north latitude over the Indian Ocean, the Arabian Sea, the southern Red Sea, the Gulf of Aden, and certain areas in the eastern tropical regions of Africa. This component accounts for 18.8 and 20.8% of the total variance in the data for the first and second climatic periods, respectively. It has the most significant impact on changes in the topography of the 500 hpa geopotential height. As a result, changes in the topography of the 500 hpa geopotential height in these regions have played a crucial role in forming systems that create extreme rainfall in southwestern Iran. This source facilitates the advection of moisture in the upper and middle levels of the atmosphere towards the studied area due to the circulation of high pressure at the 500 hpa level. In addition, the formation of low-pressure thermal centers and the displacement of their tongues towards the studied area are crucial in extreme rainfall in the study area. The location of sources that create extreme rainfall systems did not see significant changes between the two climatic periods, but their importance in forming these systems varied. Additionally, there were no significant spatial changes in the sources of extreme rainfall formation i","PeriodicalId":15609,"journal":{"name":"Journal of Earth System Science","volume":"26 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142195836","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}

{"title":"Lithospheric magnetic anomaly map of Indian subcontinent (LAMI-1) from Swarm satellite data","authors":"Monica Rawat, S P Anand, Adel Fathy, A P Dimri, Shaik Kareemunnisa Begum","doi":"10.1007/s12040-024-02393-1","DOIUrl":"https://doi.org/10.1007/s12040-024-02393-1","url":null,"abstract":"<p>A preliminary lithospheric magnetic anomaly map of the Indian subcontinent (LAMI-1) was generated utilising seven years (April 2014–December 2020) of data recorded by the Swarm satellite constellation. To obtain a high-resolution lithospheric anomaly map, the fields originating from sources other than lithospheric sources are eliminated sequentially. The external field component is minimised by selecting the days of low geomagnetic activity (Kp &lt; 2 and –20 &lt; Dst &lt; 20) within night-time hours. The main and the remaining external field sources are removed using data from CHAOS model. The model of residual data is achieved directly through the damped least square inversion technique by expanding the Legendre polynomial of order <i>n</i> = 6–50. The resulting satellite-derived lithospheric magnetic anomaly mostly reflects intermediate to long wavelength deep geological phenomena, with diverse tectonic provinces exhibiting discrete magnetic fingerprints/impressions with amplitudes ranging from high to low. Various tectonic blocks of the Indian subcontinent show distinct signature in the derived lithospheric anomaly map. The Himalayas and the Deccan Volcanic Province are associated with low magnetic signatures. The Central Indian Tectonic Zone and the Arakan Yoma Fold belt appear to have positive magnetisation. The division of Dhawar Craton into Western and Eastern Dharwar by Chitradurga Boundary shear is clearly evident in the anomaly map. A possible track of the Reunion hotspot is depicted as a north–south oriented high within the Marwar block. The comparison between the vertical (Z) component of LAMI-1 with the vertical component of MAGSAT data and MF7 lithospheric model from Champ satellite data indicates the LAMI-1 model shows far less noise and sharper anomalies with tectonic blocks better resolved compared to the other models.</p>","PeriodicalId":15609,"journal":{"name":"Journal of Earth System Science","volume":"2 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142195834","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}

{"title":"Application and comparison of RBF and BP neural networks for lithology identification of Permian volcanic rocks in the Shunbei area of the Tarim Basin in China","authors":"Shuo Shi, Wenlong Ding, Zhan Zhao, Ruiqiang Yang, Teng Zhao, Jinhua Liu, Tan Zhang","doi":"10.1007/s12040-024-02352-w","DOIUrl":"https://doi.org/10.1007/s12040-024-02352-w","url":null,"abstract":"<p>Due to the complexity of the sedimentary environment and the heterogeneities and similarities between logging data, lithology identification is difficult. Taking the Permian in Shunbei area of Tarim Basin as an example, based on a complete understanding of the target reservoir characteristics, used the crossplot method, BP (backpropagation) neural network method and RBF (radial basis function) neural network method to identify three types of volcanic rocks: tuff, andesite, and basalt. At the same time, the crossplot method was used to select four logging curves that are sensitive to lithofacies changes as important indicators for identifying volcanic rocks, such as the natural gamma ray (GR), compensated density (DEN), compensated neutron (CNL) and spontaneous potential (SP) logs. Then, the sensitive curves were preprocessed by standardization, and suitable learning samples were selected. Two types of neural network prediction models were established, and the mapping relationship between the lithology and logging curves was used to identify the lithofacies of the key wells in the study area. Finally, by comparing the recognition results of the three methods, it was found that the RBF network not only achieved higher accuracy in the prediction results but also had fewer learning iterations than the BP network could more accurately identify volcanic rocks, and has certain popularization and application values, while the crossplot method had the worst recognition results.</p>","PeriodicalId":15609,"journal":{"name":"Journal of Earth System Science","volume":"12 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142195835","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}

{"title":"Data analytics for geochemical and petrogenetic study of an igneous province: A case study on Andean andesite, South America","authors":"Sunil Kumar Khare","doi":"10.1007/s12040-024-02399-9","DOIUrl":"https://doi.org/10.1007/s12040-024-02399-9","url":null,"abstract":"<p>Genesis of Phanerozoic Andean andesite rocks is related to the subduction of the oceanic Nazca plate beneath the South American continental plate along the west coast of South America. Exploratory data analytics is done on whole-rock geochemical data of 3311 andesite rock samples collected from the Andes orogenic belt, extending from Argentina, Chile, Bolivia, Peru, and Ecuador to Colombia. Python programming has been used for the visualisation and interpretation of large volumes of geochemical data, and data-driven tectonomagmatic inferences for volcanism extending across the South American continent have been drawn with the help of data analytics. Interelemental diagrams with Zr as a fractionation index reveal relative immobility and incompatibility of several major elements, large ion lithophile elements, high field strength elements, and rare earth elements. The interelemental diagrams, correlation matrix and heat maps drawn for major elements reveal that except K₂O, TiO₂ and SiO₂, all major elements decrease with fractionation. Major element variation trends indicate that plagioclase and pyroxene were the major fractionating phases. The density plots give insight into the range of variation and data density of major and trace elements. Petrogenetic study reveals calc-alkaline, basaltic andesite to andesite, and back-arc tectonomagmatic environment for these volcanic rocks. Mantle source of Andean magma was enriched to primitive upper mantle. Around 25–30% partial melting of the upper mantle led to the genesis of the most primitive Andean magma.</p>","PeriodicalId":15609,"journal":{"name":"Journal of Earth System Science","volume":"36 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142196057","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}

{"title":"Attributing impacts of LULCC on the boundary layer climate of South Africa’s eastern escarpment","authors":"Tumelo Mohomi, Nkanyiso B Mbatha, Danie S Boshoff, Innocent L Mbokodo, Thando Ndarana, Mary-Jane M Bopape, Hector Chikoore","doi":"10.1007/s12040-024-02388-y","DOIUrl":"https://doi.org/10.1007/s12040-024-02388-y","url":null,"abstract":"<p>Land surface characteristics may influence the planetary boundary layer atmosphere and climate through exchanges of moisture, energy, and momentum near the surface. We attributed the impact of multitemporal landsat-derived land use/land cover change (LULCC) on temperature and precipitation variability in eastern South Africa using reanalysis data and satellite-derived estimates from 1979 to 2020. Landsat images were classified into different land cover classes using a machine learning random forest pixel-based supervised algorithm within the cloud-based Google Earth Engine. Time series analysis was employed to analyze cycles and trends in LULCC and hydrometeorological variables, whilst the variable importance model determined the most sensitive variable. The impacts of LULCC on the boundary layer climate were attributed via multiple linear regression. An uninterrupted rapid expansion of urban areas was observed, resulting in the transformation of grasslands, water bodies, forests, and croplands. Statistically significant changes in moisture and energy fluxes, and hydrometeorological variables were observed across the study period. Latent heat flux (LHF), as well as rainfall decreased, while maximum temperature, sensible heat, and potential evapotranspiration (PET) increased significantly. We found that LULCC is significantly impacting the boundary layer climate, with urban and bare land, grasslands, forests, and croplands influencing temperature positively while negatively influencing rainfall. Rainfall was most sensitive to changes in LHF, whilst the key driver of temperature variability was PET. Our results reinforce the significance of LULCC and associated feedbacks to understanding boundary layer processes, climate variability, and change.</p>","PeriodicalId":15609,"journal":{"name":"Journal of Earth System Science","volume":"4 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142195833","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}