Middle Jurassic–Early Cretaceous tectonic evolution of the Bayanhushuo area,southern Great Xing’an Range,NE China: constraints from zircon U–Pb geochronological and geochemical data of volcanic and subvolcanic rocks

This study presents new zircon U–Pb geochronology, geochemistry, and zircon Hf isotopic data of volcanic and subvolcanic rocks that crop out in the Bayanhushuo area of the southern Great Xing’an Range (GXR) of NE China. These data provide insights into the tectonic evolution of this area during the late Mesozoic and constrain the evolution of the Mongol–Okhotsk Ocean. Combining these new ages with previously published data suggests that the late Mesozoic volcanism occurred in two distinct episodes: Early–Middle Jurassic (176–173 Ma) and Late Jurassic–Early Cretaceous (151–138 Ma). The Early–Middle Jurassic dacite porphyry belongs to high-K calc-alkaline series, showing the features of I-type igneous rock. This unit has zircon ε_Hf(t) values from +4.06 to +11.62 that yield two-stage model ages (T_DM2) from 959 to 481 Ma. The geochemistry of the dacite porphyry is indicative of formation in a volcanic arc tectonic setting, and it is derived from a primary magma generated by the partial melting of juvenile mafic crustal material. The Late Jurassic–Early Cretaceous volcanic rocks belong to high-K calc-alkaline or shoshonite series and have A₂-type affinities. These volcanics have ε_Hf(t) and T_DM2 values from +5.00 to +8.93 and from 879 to 627 Ma, respectively. The geochemistry of these Late Jurassic–Early Cretaceous volcanic rocks is indicative of formation in a post-collisional extensional environment, and they formed from primary magmas generated by the partial melting of juvenile mafic lower crust. The discovery of late Mesozoic volcanic and subvolcanic rocks within the southern GXR indicates that this region was in volcanic arc and extensional tectonic settings during the Early–Middle Jurassic and the Late Jurassic–Early Cretaceous, respectively. This indicates that the Mongol–Okhotsk oceanic plate was undergoing subduction during the Early–Middle Jurassic, and this ocean adjacent to the GXR may have closed by the Late Middle Jurassic–Early Late Jurassic.     

Using climate to relate water discharge and area in modern and ancient catchments

Models relating sediment supply to catchment properties are important in order to use the geological record to deduce landscape evolution and interplay between tectonics and climate. Water discharge (Q _w) is an important factor in the widely used ‘BQART ’ model, which relates sediment load to a set of measurable catchment parameters. Although many of the factors in this equation may be independently estimated with some degree of certainty in ancient systems, water discharge (Q _w) certainly cannot. An analysis of a world database of modern catchments with 1255 entries shows that the commonly applied equation relating catchment area (A ) to water discharge (Q _w = 0·075A^0·8) does not predict water discharge from catchment area well in many cases (R ² = 0·5 and an error spanning about three orders of magnitude). This is because the method does not incorporate the effect of arid and wet climate on river water discharge. The inclusion of climate data into such estimations is an opportunity to refine these estimates, because generalized estimates of palaeoclimate can often be deduced on the basis of sedimentological data such as palaeosol types, mineralogy and palaeohydraulics. This paper investigates how the relationship between catchment area and river discharge varies with four runoff categories (arid, semi‐arid, humid and wet), which are recognizable in the geological record, and modifies the coefficient and exponent of the above‐mentioned equation according to these classes. This modified model yields improved results in relating discharge to catchment area (R ² = 0·95 and error spanning one order of magnitude) when core, outcrop or regional palaeoclimate reconstruction data are available in non‐arid systems. Arid systems have an inherently variable water discharge, and catchment area is less important as a control due to downstream losses. The model here is sufficient for many geological applications and makes it possible to include variations in catchment humidity in mass‐flux estimates in ancient settings.     

渝东南地区下寒武统牛蹄塘组页岩孔径分布测试方法研究

低温氮气吸附法已普遍用于评价页岩的孔隙结构,但是文献中报道的脱气温度和脱气时间等测试条件不尽相同,此外测试结果中经常出现滞后环不闭合的情况,严重影响了孔径分布等结构参数测试的准确性。为了评价和探索有效的页岩孔径分布测试方法,本文选取渝科1井下寒武统牛蹄塘组黑色页岩,重点研究应用低温氮气吸附法分析其孔径分布的测试条件,系统探讨了样品质量、脱气温度、升温速率和脱气时间对测试结果的影响,通过进一步优化参数建立了可靠的孔径分布测试方法,并成功用于测定其他页岩样品。结果表明:吸附-脱附等温线呈反C型,属于Brunauer等提出的BDDT等温吸附曲线分类中的V型,滞后环完全闭合,属于IUPAC分类中的H4型,对应狭窄的狭缝型孔隙,说明此类页岩中除了含有峰值孔径主要集中在3.5~4.5 nm的中孔和一定数量的大孔外,还存在大量微孔。研究认为脱气温度是影响测试结果的主要因素。该研究是页岩孔径分布测试方法的一项补充,为我国页岩气的深入研究提供了关键参数支持。     

粤东鸿沟山金矿区流纹斑岩锆石SHRIMP U-Pb定年、Lu-Hf同位素组成及其地质意义

鸿沟山矿区位于华南粤东莲花山钨矿床的中部,是近年来通过地质矿产调查新发现具有找寻金矿潜力的矿床之一。本文以与鸿沟山金等多金属矿化关系密切的流纹斑岩为研究对象,开展了锆石SHRIMP U-Pb定年、流纹斑岩和矿石岩石地球化学、锆石Lu-Hf同位素组成特征研究。获得流纹斑岩锆石206Pb/238U加权平均年龄为169.1±1.5Ma,说明岩体形成于中侏罗世。在微量元素特征方面,流纹斑岩都表现为相对亏损大离子亲石元素Ba、Sr和高强场元素Nb、P、Zr、Hf,富集大离子亲石元素Rb,高强场元素U、Ce、Sm和轻稀土元素La、Nd,流纹斑岩与矿石稀土元素特征基本相似,Eu具中等负异常,但随着矿化强度的增强稀土元素更加富集。流纹斑岩εHf(t)(-15.0~2.2)分布范围宽,二阶段模式年龄TDM2主要变化范围为0.82~0.93 Ga,表明成岩物质主要来源于新元古代古老地壳变质泥岩和变质砂岩部分熔融,并有幔源物质的加入。因此,围绕着该时间段的流纹斑岩岩体,对于找寻W、Cu、Pb、Zn、Bi、Au、稀土、稀有和稀散元素矿产具有重要意义。     

松辽盆地大陆深部科学钻探2号井完井暨学术研讨现场会召开

正2018年5月26日,自然资源部中国地质调查局在黑龙江省安达市松科二井工程现场召开大陆科学钻探工程(松科二井)完井暨学术研讨现场会。中国地质学会常务副理事长兼秘书长、自然资源部中国地质调查局副局长、松科二井工程领导小组组长李金发宣布松辽盆地大陆深部科学钻探工     

大兴安岭十八站—韩家园地区中酸性侵入岩LA-ICP-MS锆石U-Pb年龄、地球化学特征及其地质意义

大兴安岭北部塔河县十八站—呼玛县韩家园地区发育早古生代中酸性侵入岩。文章选取二长闪长岩和二长花岗岩开展岩石年代学与地球化学研究。二长闪长岩LA-ICP-MS锆石U-Pb年龄为512.4±3.5 Ma,为早—中寒武世岩浆作用的产物。岩石地球化学分析表明,中酸性侵入岩归属于准铝质—弱过铝质(A/CNK=0.77~1.04)钙碱性—高钾钙碱性系列。岩石稀土总量∑REE=69.51×10~(-6)~275.83×10~(-6),轻重稀土分异明显(La/Yb)_N=9.11~26.64。在稀土元素配分图上,显示为LREE富集、HREE相对平缓的右倾型,Eu异常不显著(δEu=0.90~1.35)。微量元素组成具明显富集大离子亲石元素Ba、Sr,显著亏损高场强元素Nb、Ta、Ti的特征。结合区域资料和本文研究,初步分析认为早古生代侵入体形成于活动大陆边缘或岛弧环境,为前古亚洲洋闭合背景下萨拉伊尔造山作用的产物。     

基于高分二号卫星数据的煤矿区地质灾害信息提取研究

随着遥感数据获取技术和能力的全面提高,遥感数据呈现出明显的大数据特征。发展适应于遥感大数据的智能分析和信息挖掘技术,成为当前遥感技术研究的前沿。高分二号（GF-2）卫星数据是我国首颗自主研发的亚米级高分辨率卫星数据,具有观测幅宽、重访周期短、高辐射精度、高定位精度等优势,为未来我国地质灾害的长期、动态地监测和研究提供了高精度、稳定可靠的数据源。本文选取安徽谢桥煤矿2015年1月8日的GF-2卫星影像为研究数据,在对煤矿区主要地质灾害遥感地学分析的基础上,采用面向对象的影像分析方法对研究区由采煤活动所诱发的地质灾害信息进行自动提取。结果表明：利用GF-2卫星数据能够有效地识别地质灾害体的位置、范围、形态等空间分布特征;面向对象的自动提取方法对于煤矿区大面积的积水塌陷盆地、小规模的塌陷坑和线性的地裂缝都有很高的提取精度,识别精度达90% 以上;基于逐层剔除的思路构建的提取规则,为GF-2数据在地质灾害调查和大数据分析中的应用提供了很好的技术支持,也为其它地物目标的提取提供了参考,但在特征的选择和阈值的设定上需要具体分析。     

基于GIPL2模型的青藏高原活动层土壤热状况模拟研究

青藏高原活动层土壤热状况,对深入了解高原活动层的厚度变化特征、下垫面的热力作用以及对气候变化预测均有重要意义。利用GIPL2模型模拟青藏高原多年冻土区不同植被状况下活动层土壤热状况。模拟结果表明：模型在高寒草原（QT06）试验点模拟效果较好,高寒沼泽草甸（QT03）试验点的模拟效果较差,高寒草甸（QT01）、高寒荒漠草原（QT05）和高寒草原化草甸（QT04）试验点的模拟效果介于高寒草原试验点和高寒沼泽草甸试验点之间。QT01、QT03、QT04、QT05和QT06的土壤温度模拟值与观测值相比,均方根误差分别为0.67、1.29、0.73、0.7和0.56℃;相关系数分别为0.99、0.87、0.98、0.98和0.96;平均误差分别为0.37、0.61、0.31、0.45和0.16℃。QT06模拟结果较好,原因在于此点土壤质地变化不大,模型的分层与所取的参数更加接近此点的实际状况。QT03模拟结果较差,可能由于此地区土壤中存在砾石,在导热率参数化方案中没有考虑砾石含量,导致模拟结果偏差较大。总体而言,GIPL2模型对青藏高原活动层土壤热状况的模拟具有一定的优势,是一种模拟多年冻土区活动层土壤热状况较为理想的模型。     

张广才岭南段两个侏罗纪花岗岩体的地球化学特征及其地质意义

通过LA-ICP-MS锆石U-Pb定年和岩石化学分析,研究了张广才岭南段上营北岩体和帽儿山岩体的形成年代,地球化学特征和形成环境。上营北岩体为中粗粒钾长花岗岩,帽儿山岩体为中细粒黑云母钾长花岗岩。上营北岩体的加权平均年龄为178.9±2.7 Ma,帽儿山岩体为183.7±2.4 Ma,均为早侏罗世侵入岩。上营北岩体和帽儿山岩体主量元素都具有Si O_2和K_2O含量较高,Ti O_2、Mg O、Ca O含量较低,TFe O/Mg O值较高的特点;上营北岩体A/CNK=0.98~1.08,里特曼指数σ=1.51~2.66;帽儿山岩体含铝指数A/CNK=1.00~1.01,里特曼指数σ=2.12~2.36。上营北岩体稀土元素配分模式为海鸥型,轻重稀土分馏不明显;帽儿山岩体稀土元素配分模式为右倾型,轻稀土较重稀土富集;两个岩体均富集Rb、K,Ba、Nb、Ta、Sr、Ti、P、Ho、Er、U、Eu等元素出现不同程度的亏损。地球化学特征分析显示上营北岩体和帽儿山岩体均为A_2型花岗岩,为后造山型花岗岩,形成于兴蒙造山带后造山的伸展环境。     

Assessing soil salinity using WorldView-2 multispectral images in Timpaki,Crete, Greece

Salinization is one of the major soil degradation threats occurring worldwide. This study evaluates the feasibility of operational surface soil salinity mapping based on state-of-the-art Earth Observation (EO) products captured by sensors on-board WorldView-2 (WV2) and Landsat 8 satellites. The proposed methods are tested in Timpaki, south-central Crete,Greece, where brackish water irrigation puts soil health at risk of soil salinization. In all cases, EO products are calibrated against soil samples collected from bare soil locations. Results indicate a moderate correlation of observed EC_e values with the investigated remote sensing parameters. Regarding sensitivity to saline soil, the yellow band displays higher values. Comparison between methods used in the literature shows that those developed specifically for soil salinity, and especially index S5, perform better. The proposed ‘detection index’ and 3D PCA transformation methodology perform reasonably well in detecting areas with high EC_e values and provide a simple and effective operational alternative for saline topsoil detection and mapping.