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阿尔金山东端北部区域生态环境修复模式研究 总被引：1，自引：0，他引：1
阿尔金山荒漠化防治生态功能区是甘肃西部、新疆乃至整个西北地区重要生态屏障,对阿尔金山东端北部区域为代表的西土沟流域生态环境现状和存在主要问题进行分析,提出区域生态环境治理构想和因势治洪-以洪治沙-自然净化-综合利用的区域洪水资源开发利用模式和以“水害”治“沙害”、变害为利的区域生态环境、沙漠治理模式。国内外学者对本区域荒漠化防治、草地生态安全评价有部分研究,但对沙漠区洪水资源开发利用问题研究比较罕见,在沙漠地区洪水资源化利用方面具有很强的代表性,为阿尔金山保护区的规范管理和可持续对策制定提供科学依据,对同类地区生态环境修复提供示范。 相似文献
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地理信息系统在商业上的应用是近年来GIS应用研究的新热点。分析了GIS在城市商业网点中的应用,构建梅州城区商业网点空间数据库。从网点编码、数据库详细设计、数据库发布及优化等方面进行探讨,目的是实现商业网点数据的规范入库、空间数据和属性数据的无间隙管理和维护,改变传统落后低效的管理模式,实现高效可视化的商业网点数据管理,为商业网点空间管理规划系统的设计提供基础数据。 相似文献
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FU Changlei HE Xiaohu YAN Zhen Jonathan C. AITCHISON XIAO Wenjiao WANG Bingzhang LI Wufu LI Yusen 《《地质学报》英文版》2024,98(2):285-302
Identification and anatomy of oceanic arcs within ancient orogenic belt are significant for better understanding the tectonic framework and closure process of paleo-ocean basin. This article summarizes the geological, geochemical, and geochronological characteristics of upper crust of Proto-Tethyan Lajishan intra-oceanic arc and provides new data to constrain the subduction evolution of the South Qilian Ocean. The intra-oceanic arc volcanic rocks, including intermediate–mafic lava, breccia, tuff, and minor felsic rocks, are distributed along southern part of the Lajishan ophiolite belt. Geochemical and isotopic compositions indicate that the intermediate–mafic lava were originated from depleted mantle contaminated by sediment melts or hydrous fluids, whereas the felsic rocks were likely generated by partial melting of juvenile mafic crust in intra-oceanic arc setting. Zircons from felsic rocks yield consistent and concordant ages ranging from 506 to 523 Ma, suggesting these volcanic rocks represent the relicts of upper crust of the Cambrian intra-oceanic arc. Combined with the Cambrian forearc ophiolite and accretionary complex, we suggest that the Cambrian intra-oceanic arc in the Lajishan ophiolite belt is belonging to the intra-oceanic arc system which was generated by south-directed subduction in the South Qilian Ocean at a relatively short interval between approximately 530 and 480 Ma. 相似文献
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慢特征分析（SFA）方法可以从非平稳时间序列中提取出慢变的外强迫信息。近年来,SFA方法被应用于气候变化研究领域,用于探究气候变化的潜在驱动力及相关的动力学机制。本文基于SFA方法,提取全球陆地表面气温（LSAT）的慢变外强迫信息,研究全球LSAT慢变驱动力的空间结构特征及低频变率的主要驱动因子。SFA方法提取的LSAT慢变驱动力与历史时期全球辐射强迫（GRF）和全球海表温度（SST）的主模态（大西洋多年代际振荡AMO、热带太平洋ENSO变率和太平洋年代际振荡PDO）有显著的相关关系,表明全球大部分地区LSAT的变率受到GRF和三个SST模态的显著影响。GRF对LSAT变率的影响有全球一致性的特征,而三个SST模态对LSAT变率的影响则呈现出明显的区域特点。此外,由于SFA方法可以有效降低原始LSAT序列中随机噪声的干扰,GRF和SST模态对LSAT变率的解释方差显著提高,进一步表明GRF和SST模态是全球LSAT低频变率主要的驱动因子。最后,利用历史海温驱动AGCM试验（即AMIP试验）的结果,验证了三个SST模态对区域LSAT变率的显著影响。 相似文献
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Lu Kaihui Liu Weiwei Warren Alan Xu Yusen Zhu Changyu Zhao Yan Yi Zhenzhen 《中国海洋湖沼学报》2020,38(1):156-167
Journal of Oceanology and Limnology - Although the taxonomy of oligotrich ciliates has been widely investigated, yet the species diversity remains poorly known. We newly designed a pair of... 相似文献
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鄂尔多斯是我国重要的油气盆地,而绝大多数油气储层都会受到天然裂缝的影响。文中通过野外系统观测和室内的统计分析, 详细描述了盆地中生代地层中的天然裂缝发育特征和主要控制因素, 为裂缝性油气藏勘探开发提供基础理论支持。通过研究得知, 盆内中生代地层中主要发育有6组裂缝： E-W向、 ENE-WSW向、 NE-SW向、 N-S向、 NNW-SSE向、 NNE-SSW向。其中E-W向、 ENE-WSW向和NE-SW向为系统裂缝; N-S向、 NNW-SSE向和NNE-SSW向为非系统裂缝。在裂缝组合中, 有两组正交裂缝系统（E-W向和N-S向, ENE-WSW向和NNW-SSE向）, 其中E-W向和N-S向裂缝构成的正交裂缝系统只出露于三叠和侏罗纪地层。同时, 还有两组共轭裂缝（ENE-WSW向和NNE-SSW向, ENE-WSW向和ESE-WNW向）, 其中ENE-WSW向和NNE-SSW向裂缝构成的共轭裂缝出露于整个中生代地层, 而另外一组只出露于上三叠统延长组中。此外, 裂缝间距分析表明： （1）裂缝间距与力学层厚之间的关联性相对较低; （2）E-W向和ENE-WSW向两组系统裂缝的发育强度好于N-S向非系统裂缝组; （3）岩层厚度越小, 对应裂缝密度则越大。（4）除了岩层厚度, 区域应力场对裂缝的发育具有很大的影响。研究区内裂缝主要形成于两期区域应力场： 第一期是晚侏罗世近E-W向的挤压应力场, 由古太平洋板块向欧亚板块的俯冲和碰撞作用所致; 第二期是新生代NE-SW向的挤压应力场, 由印度板块向欧亚板块的俯冲和碰撞作用所致。 相似文献
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ZHOU Weijian HUANG Dezhi YU Zhiqiang M. SANTOSH CAO Yusen ZHANG Jiandong LIU Lei CUI Jianjun LI Jianyuan 《《地质学报》英文版》2023,97(1):35-54
The Neoproterozoic evolution of the Jiangnan Orogen is important for understanding the tectonic history of South China. As a volcanic-sedimentary sequence developed in the Nanhua rift, the Banxi Group preserves the records of important magmatic and tectonic events linked to the assembly and breakup of the Rodinia supercontinent. In this study, we report the results from whole-rock major-and trace-element concentrations, with zircon LA-(MC)-ICP-MS U-Pb ages, trace elements and Lu-Hf isotopic comp... 相似文献
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Prediction of landslide displacement with an ensemble-based extreme learning machine and copula models 总被引：2，自引：0，他引：2
Research on the dynamics of landslide displacement forms the basis for landslide hazard prevention. This paper proposes a novel data-driven approach to monitor and predict the landslide displacement. In the first part, autoregressive moving average time series models are constructed to analyze the autocorrelation of landslide triggering factors. A linear ensemble-based extreme learning machine using the least absolute shrinkage and selection operator is applied in predicting the displacement of landslides. Five benchmarking data-driven models, the support vector machine, neural network, random forest, k-nearest neighbor, and the classical extreme learning machine, are considered as baseline models for validating the ensemble-based extreme learning machines. Numerical experiments demonstrated that the proposed prediction model produces the smallest prediction errors among all the algorithms tested. In the second part, parametric copula models are fitted on the predicted displacement, to investigate the relationship between the triggering factors and landslide displacement values. The Gumbel-Hougaard copula model performs best, which indicates strong upper tail correlation between the triggering factors and displacement values. Thresholds for the triggering factors can be obtained by monitoring the landslide moving patterns with large displacement values. The effectiveness and utility of the proposed data-driven approach have been confirmed with the landslide case study in the region of the Three Gorges Reservoir. 相似文献