球壳形磁性层磁异常正反演方法

为了适应卫星磁测资料解释的需要,作者在磁性界面和磁性层磁异常正反演方法研究的基础上,首次提出了球壳形磁性层磁异常正反演理论和方法。 作者首先阐述了垂直磁化球壳型磁性层模型,导出了场垂直分量Z_(λο)的球谐系数正演公式。然后,给出了磁性层上,下层面埋深变化值与磁化强度变化值的球谐系数反演公式。进而导出了迭代反演收敛条件。本文的磁化强度反演方法不同于目前国内外已有的方法,其反演对象是磁化强度变化值△J_(λθ),磁化强度平均值J是必须给定的定解条件。这种反演方法能给出尽可能满足人们解释要求的解,克服了前人反演方法总存在负值的困难。 为了增加球壳形磁性层反演方法的实用性,作者还在类似平面频率城反演方法所作假设的前提下,把这种利用球谐分析理论在全球面导出的方法,严格地推广应用于局部区域。这也是球谐分析理论在局部区域应用的一个实例,在理沦上具有一定的意义。     

我国西南地区一次暴雨过程特征及成因

利用卫星云图、多普勒天气雷达资料和高空风等各种天气学资料,对2009年6月8—9日广西、贵州、以及和湖南交界地带的一次暴雨过程进行了综合分析。结果表明,暴雨是由中尺度对流复合体东移、β中尺度强对流云团发展、以及二者合并造成的;地面α中尺度低压带配合α中尺度纬向切变线的生成,为中尺度对流复合体（mesoscale convective complex,MCC）的东移发展、β中尺度强对流云团的发展、以及二者的合并创造了有利条件;地面能量比低值舌的活动是MCC和β中尺度强对流云团生成和发展的触发机制之一;在多普勒雷达径向速度图上,MCC的生成和发展,伴随西南低空急流的建立和维持,大范围的逆风区的生成;MCC的消亡,伴随西南低空急流的减弱和消失,对应西北气流建立和东扩。MCC发展期和β中尺度强对流云团发展期、MCC消散期和β中尺度强对流云团消散期的涡度收支以及视热源和视水汽汇有很大的不同。     

福建政和东际金(银)矿床矿浆隐爆角砾岩成矿模型及其动力学研究

本文描述政和东际金(银)矿床地质特征,建立矿床成矿模型,论证矿床物质运移动力学过程,探讨成矿物质来源。矿山经过系统的勘探和开采,将暴露于地表580~620 m的矿体直至延深到地下-200 m,均得到钻探和探硐的完整揭露。采用常规、可靠的地质论证法全面收集了第一手资料以及宏微观的岩矿鉴定及部分电子探针分析,对研究标的进行综合论述。政和东际金(银)矿床矿化角砾岩筒自上而下可分为5个相带:震裂相、震碎相、隐爆相、上部通道相及下部通道相。从矿石结构构造特征、矿体侵入围岩接触关系、角砾特征、胶结物成分等一系列现象判断,矿床为矿浆隐爆成因。源于壳幔过渡带深部中酸性岩浆熔离分异的富硅、富铁熔浆,富硅熔浆先一步上侵形成大规模的火山喷发及潜火山岩的侵入,富铁熔浆滞留于"源地",俘获硫化物液滴,储集形成混合矿浆。物理性状及运移动力学特征表明,在外驱动力作用下,矿浆沿着石英斑岩"岩浆热场通道"上侵,在古地表之下2.0~2.5 km处,石英斑岩硅帽隔挡层下聚集、隐爆、定位成矿。石英斑岩为容矿围岩,与矿床有密切的时空关系但与成因无关。深部钻探验证表明隐爆角砾岩筒尾部在石英斑岩中收敛,矿化随之结束。"矿浆隐爆"作为"隐爆角砾岩型金矿"大家族中新成员,目前尚未见报道。该新类型的发现,为中酸性岩浆熔离分异成矿理论提供了难得的实例,也将有助于中国东南沿海中生代陆相火山岩区同类型金矿的找矿工作。     

橄榄石斑晶和捕虏晶与年青橄榄玄武岩的K-Ar定年

取自黑龙江北部5个年青橄榄石玄武岩样品，分别对挑出橄榄石细小斑晶和捕虏晶的玄武岩、橄榄石斑晶和其他斑晶作了K-Ar定年。结果表明橄榄石和玄武岩浆不是同时代的，挑出橄榄石晶体后表现年龄将下降（年轻）50%至90%.     

冷水碳酸盐岩研究现状与展望

长期以来,海相碳酸盐沉积物被广泛认为是温暖浅海沉积环境中的产物,然而近年来国外研究表明,在冷水陆架环境中,也可以形成规模的碳酸盐沉积,即冷水碳酸盐岩。通过对大量文献的调研,综述了冷水碳酸盐岩的概念、地质特征、沉积模式等方面的研究进展,并展望了该研究领域未来的发展方向。研究表明,冷水碳酸盐沉积是指在(古)纬度约30°~35°以上的温带及寒带地区、温度约20℃以下的沉积水体中,或是在富营养的寒冷上升流水体中形成的碳酸盐沉积物或岩石,其沉积特征与暖水碳酸盐岩不同。冷水碳酸盐沉积物中的生物颗粒组合以底栖有孔虫、软体动物、苔藓虫等异养生物和钙质红藻为主,缺乏造礁珊瑚和钙质绿藻以及鲕粒、集合颗粒等非骨架颗粒,而且沉积物中灰泥基质含量较少,矿物成分以方解石为主,氧同位素较重,胶结作用弱,以破坏性成岩作用为主。冷水碳酸盐沉积形态以缓坡为主,波浪磨蚀和再沉积作用较强。古代冷水碳酸盐岩的沉积特征、识别标志及其作为储层的油气资源潜力尚处于探索阶段,仍需进一步深入研究。     

Virtual geographic environment-based integrated rockfall risk simulation method for canyon bridges

Bridges located in mountainous areas are vulnerable to rockfall accidents, posing a threat to bridge engineering construction and operation safety in these regions. Under the coupling effect of complex environments and engineering disturbances, integrated rockfall risk simulation has become increasingly important for canyon bridge structural protection in long-term construction and operation phases. One of the main scientific challenges in rockfall risk simulation is studying the interaction between rockfalls and the topography and engineering environments during consecutive contacts. To systematically simulate the integrated bridge rockfall risk, an integrated construction of multivariable elements coupled with rockfall risk environments and scenarios is required. In this article, we proposed a VGE-based integrated rockfall scenario simulation method that uses the “associated representation—integrated modelling—interactional simulation” core strategy. Our method constructs a virtual rockfall risk environment by fusing multisource data to represent rockfall factors that induce rockfall disasters, hazard-forming environments, and elements at risk. We design rockfall scenarios under different bridge engineering construction conditions and extreme environmental conditions to analyze the interactional rockfall risks. The results demonstrate that our method enables a systematic analysis of the potential integrated rockfall risk, providing realistic reference value for the timely and effective disposal of emergencies, and reducing the harm and losses caused by such emergencies.     

奎玛流域两次冰雹天气成因分析

利用常规气象观测、区域自动站、多普勒雷达和 NCEP1毅伊1毅再分析、ECWMF 细网格 模式等多源资料，对比分析了 2013 年 6 月 11 日和 2017 年 6 月 18 日发生在奎玛流域的两次冰雹过程。分析发现：两次过程环流背景和冷空气影响路径不同“，6·11”过程发生在西西伯利亚低槽底部锋区上短波东移背景下，回波自西西北向东东南移动； “6·18”过程发生在西伯利亚高压脊内中纬度西风带上短波槽沿天山北坡东移背景下，回波为偏西路径。两次过程也有很多相同点，低仰角径向速度的辐合区都对应高仰角的辐散区，降雹前 40 min 内 VIL 和 VILD 明显增大；大气层结维持了对流性不稳定状态；K 指数增大、SI 指数减小，且对流有效位能均增大，抬升指数 LI 降为负数，表明降雹前大气层结不稳定度增强；700 hPa 水汽条件都较好； “6·11”和“6·18”过程都是初始对流沿地面辐合线生成、发展，雹云单体在地面小尺度辐合中心附近生成。     

Geo-environment-aware adversarial transfer learning method for landslide susceptibility evaluation of complex mountainous areas

Landslide susceptibility evaluation (LSE) is a critical issue for disaster prevention. Limited by labor cost and observation technology, landslide samples are extremely limited in dense vegetation-covered and remote areas, making the common supervised learning model underfit with limited samples. Therefore, the reliability of analysis results in mountainous areas is low. Transfer learning can achieve reliable assessment without the need for representative samples. However, transfer learning suffers from environmental heterogeneity in regional LSE and may transfer incorrect classification knowledge of landslide features from dissimilar environments. Aiming at these challenges, we proposed a geo-environment-aware LSE method based on unsupervised adversarial transfer learning. The key is to consider the difference in landslide features in different geo-environments. The study areas were first divided into multiple sub-environments, and the similarity between the sub-environments was calculated. Then an environment-aware adversarial transfer model was built for fine-grained aligning of the landslide feature with similar sub-environments and for reducing negative transfer between dissimilar environments. The fitted classification model was employed to predict the target regions and to generate the final LSE. The experimental results indicated that the proposed method achieves reliable LSE for sample-free regions. The accuracy of the proposed method is 7–12% better than commonly used methods such as support vector machines, random forests, and artificial neural networks. The performance of the proposed method is even close to the results of supervised learning with the presence of representative samples, and it also performs more globally and objectively in susceptibility mapping. These results reveal that the proposed method effectively transfers the knowledge of landslide susceptibility from other regions to the sample-free region.