Study of late-Mesozoic magmatic rocks and their related copper-gold-polymetallic deposits in the Guichi ore-cluster district,Lower Yangtze River Metallogenic Belt,East China

ABSTRACT

The Guichi ore-cluster district in the Lower Yangtze River Metallogenic Belt hosts extensive Cu–Au–Mo polymetallic deposits including the Tongshan Cu–Mo, Paodaoling Au, Matou Cu–Mo, Anzishan Cu–Mo, Guilinzheng Mo and Zhaceqiao Au deposits, mostly associated with the late Mesozoic magmatic rocks, which has been drawn to attention of study and exploration. However, the metallogenic relationship between magmatic rocks and the Cu–Au-polymetallic deposits is not well constrained. In this study, we report new zircon U–Pb ages, Hf isotopic, and geochemical data for the ore-bearing intrusions of Guichi region. LA-ICP-MS U–Pb ages for the Anzishan quartz diorite porphyrite is 143.9 ± 1.0 Ma. Integrated with previous geochronological data, these late Mesozoic magmatic rocks can be subdivided into two stages of magmatic activities. The first stage (150–132 Ma) is characterized by high-K calc-alkaline intrusions closely associated with Cu–Au polymetallic ore deposits. Whereas, the second stage (130–125 Ma) produced granites and syenites and is mainly characterized by shoshonite series that are related to Mo–Cu mineralization. The first stage of magmatic rocks is considered to be formed by partial melting of subducted Palaeo-Pacific Plate, assimilated with Yangtze lower crust and remelting Meso-Neoproterozoic crust/sediments. The second stage of magmatism is originated from partial melting of Mesoproterozoic-Neoproterozoic crust, mixed with juvenile crustal materials. The depression cross to the uplift zone of the Jiangnan Ancient Continent forms a gradual transition relation, and the hydrothermal mineralization composite with two stages have certain characteristics along the regional fault (Gaotan Fault). Guichi region results from two episodes of magmatism probably related to tectonic transition from subduction of Palaeo-Pacific Plate to back-arc extensional setting between 150 and 125 Ma, which lead to the Mesozoic large-scale polymetallic mineralization events in southeast China.     

Simplified formulae for designing coastal forest against tsunami run-up: one-dimensional approach

In the present study, laboratory experiments were conducted to validate the applicability of a numerical model based on one-dimensional nonlinear long-wave equations. The model includes drag and inertia resistance of trees to tsunami flow and porosity between trees and a simplified forest in a wave channel. It was confirmed that the water surface elevation and flow velocity by the numerical simulations agree well with the experimental results for various forest conditions of width and tree density. Further, the numerical model was applied to prototype conditions of a coastal forest of Pandanus odoratissimus to investigate the effects of forest conditions (width and tree density) and incident tsunami conditions (period and height) on run-up height and potential tsunami force. The modeling results were represented in curve-fit equations with the aim of providing simplified formulae for designing coastal forest against tsunamis. The run-up height and potential tsunami forces calculated by the curve-fit formulae and the numerical model agreed within ± 10% error.     

Objective Analysis on Large-scale Circulation Type and Its Links to Precipitation over China

Atmospheric circulation anomaly is a direct cause of weather and climate change. In the past, most researches for the relationship between Weather Type (WT) and precipitation have mainly focused on the subjective classification and diagnosis. Compared to the subjective analysis, objective classification uses more consistent index and standard unification, thus, we can get more WTs, and it has been widely used in many areas. By using daily 12UTC Sea Level Pressure (SLP), Precipitable Water (PW), and 700 hPa wind speed (UV700) data from ECMWF’s Interim Reanalysis, the classification of WTs over China was performed with the method of obliquely rotated T-mode principle component analysis. WT and its link to precipitation over China were further analyzed. The results show that the influence of different WTs on precipitation is not uniform over China, and also show distinctly difference in different seasons. A common feature is that WTs great impact on the regions and months with large precipitation, while less impact on regions and months have with less precipitation. In addition, precipitation trends originating from WT intensity changes are much more deterministic, significant, and predictable than trends from WT frequency changes.     

Satellite estimates and subpixel variability of rainfall in a semi-arid grassland

卫星估雨精度的不确定性受到当地降雨类型和像元内降雨非均匀性影响,而结合这两个关键因素开展半干旱草原卫星估雨的研究有限.2009年夏,我们在中国锡林郭勒半干旱草原用多部微雨雷达和雨量计构建了9 km卫星像元降雨观测网,观测了像元内降雨非均匀性(空间变异系数CV),并评估了卫星估雨精度.结果表明:(1)CV值受像元内平均降雨量,降雨类型,降雨云面积及移向等影响,如高Cv值的降雨过程大多为平均降雨量小,对流性降雨过程,降雨云边缘像元CV值较高;(2)TRMM 3B42V7卫星估雨产品适用性较好,CMORPH和PERSIANN次之,但TRMM 3B42V7易在半干旱草原湖泊处高估降雨.     

漠河盆地西部二十二站组碎屑锆石U-Pb年龄、地球化学特征及其物源意义

大兴安岭北部漠河盆地内广泛发育二十二站组,其形成时代及物质来源一直以来备受争议.本文在野外地质调查及岩相学的基础上,利用碎屑锆石LA-ICP-MS U-Pb法测年,并结合岩石地球化学等方法,探讨了二十二站组形成时代、物源区大地构造环境及沉积物来源.测年结果显示132个测点年龄主要分布在4个群落,分别为508.3～492.3 Ma;486.9～435.5 Ma;278.3～254.2 Ma;209.5～178.1 Ma.本次获得二十二站组最小碎屑锆石年龄为178.1 Ma,并结合漠河盆地东西部碎屑锆石的年龄,综合认为二十二站组形成时代应为中晚侏罗世.地球化学分析结果显示,二十二站组砂岩的稀土元素与活动大陆边缘的稀土元素曲线吻合较好,且相对亏损高场强元素(Nb和Ta)和大离子亲石元素(Ba和Sr),相对富集高场强元素(La、Th、Zr、Hf),地球化学特征与活动大陆边缘相似.综合古流向、源区母岩分析、碎屑锆石测年分析、微量元素特征等诸多因素,本次研究认为本区二十二站组砂岩的母岩主要来源于盆地南缘广泛分布的前中生代沉积-变质基底(兴华渡口岩群、佳疙瘩组、额尔古纳河组等)及各期中酸性火成岩.     

Flood-prone area mapping using machine learning techniques: a case study of Quang Binh province,Vietnam

Natural Hazards - Vietnam’s central coastal region is the most vulnerable and always at flood risk, severely affecting people’s livelihoods and socio-economic development. In...     

煤炭地质勘查产业转型发展的思考与探讨

煤炭地质勘查工作关系国家能源安全,在国民经济发展中具有重要的战略地位。伴随煤炭行业绿色转型和新能源革命新形势,及时调整产业结构,向大地质、大资源、大生态方向拓展服务领域,为国家生态文明建设和煤炭产业绿色安全高效发展提供坚实的地质技术保障,成为煤炭地质勘查产业转型发展必然趋势和未来发展方向。结合煤田地质勘查工作发展历程及现状、发展趋势,对煤炭地质勘查产业转型发展方向进行深入剖析和探讨。     

Predicting rock size distribution in mine blasting using various novel soft computing models based on meta-heuristics and machine learning algorithms

Blasting is well-known as an effective method for fragmenting or moving rock in open-pit mines. To evaluate the quality of blasting, the size of rock distribution is used as a critical criterion in blasting operations. A high percentage of oversized rocks generated by blasting operations can lead to economic and environmental damage. Therefore, this study proposed four novel intelligent models to predict the size of rock distribution in mine blasting in order to optimize blasting parameters, as well as the efficiency of blasting operation in open mines. Accordingly, a nature-inspired algorithm (i.e., firefly algorithm – FFA) and different machine learning algorithms (i.e., gradient boosting machine (GBM), support vector machine (SVM), Gaussian process (GP), and artificial neural network (ANN)) were combined for this aim, abbreviated as FFA-GBM, FFA-SVM, FFA-GP, and FFA-ANN, respectively. Subsequently, predicted results from the abovementioned models were compared with each other using three statistical indicators (e.g., mean absolute error, root-mean-squared error, and correlation coefficient) and color intensity method. For developing and simulating the size of rock in blasting operations, 136 blasting events with their images were collected and analyzed by the Split-Desktop software. In which, 111 events were randomly selected for the development and optimization of the models. Subsequently, the remaining 25 blasting events were applied to confirm the accuracy of the proposed models. Herein, blast design parameters were regarded as input variables to predict the size of rock in blasting operations. Finally, the obtained results revealed that the FFA is a robust optimization algorithm for estimating rock fragmentation in bench blasting. Among the models developed in this study, FFA-GBM provided the highest accuracy in predicting the size of fragmented rocks. The other techniques (i.e., FFA-SVM, FFA-GP, and FFA-ANN) yielded lower computational stability and efficiency. Hence, the FFA-GBM model can be used as a powerful and precise soft computing tool that can be applied to practical engineering cases aiming to improve the quality of blasting and rock fragmentation.     

中学地理科学实验的六大类型及其案例分析

依据实验的根本目的,为拓展学生对地理过程的理解,体验真实的地理原理,笔者将中学地理科学实验划分为经典实验室实验、时间变化模型实验、类比实验、空间变化模型实验、物理模型实验以及计算机模型实验六大类型,并对每一类型实验进行举例分析,希望以此深化地理科学实验的理论研究、丰富地理科学实验的实践案例、培养学生的地理核心素养,为地理科学实验教学研究提供新的视角。