中国-老挝古近纪钾盐矿对比

云南江城勐野井钾盐矿的探明，填补了我国无固体钾盐矿的史例。时代属古近系古新统（E1），与老挝万象钾镁盐矿属同时代、同构造带。勐野井钾盐矿赋存在勐野井组上部（E1me^3），属氯化钾（KCl）类；老挝万象钾镁盐矿属光卤石类，地层为古新统塔贡组下部（E1tg^1）。     

Stratigraphy and ammonite fauna of the upper Shemshak Formation (Toarcian–Aalenian) at Tazareh, eastern Alborz, Iran

With a thickness of 3900 m, the Tazareh section is one of the thickest developments of the Shemshak Formation in the Alborz range. It overlies with sharp and disconformable contact the limestones and dolomites of the Lower–Middle Triassic Elikah Formation and is topped, again with a disconformable contact, by the marls and limestones of the Middle Jurassic Dalichai Formation. The nearly exclusively siliciclastic succession represents a range of environments, from fluvial channels, flood plains, swamps and lake systems to storm-dominated shelf, and a comparatively deep marine and partly dysoxic basin. The segment of the section between 2300 and 3500 m is exclusively marine and contains a moderately diverse ammonite fauna, ranging from the Middle Toarcian to the Upper Aalenian. The ammonite fauna comprises 21 taxa, among them the new genus Shahrudites with two new species, Shahrudites asseretoi and S. stoecklini from the Middle Aalenian Bradfordensis Zone. The other ammonites from the Shemshak Formation at Tazareh (as elsewhere in North and Central Iran) are exclusively Tethyan in character and closely related to faunas from western and central Europe. An ammonite-based correlation of Toarcian–Aalenian successions of the eastern Alborz with time-equivalent strata of the Lut Block, part of the Central-East Iranian Microcontinent (ca. 500 km to the south), suggests a strong influence of synsedimentary tectonics during the deposition of the upper Shemshak Formation.     

Performance of Multi Model Canonical Correlation Analysis (MMCCA) for prediction of Indian summer monsoon rainfall using GCMs output

The emerging advances in the field of dynamical prediction of monsoon using state-of-the-art General Circulation Models (GCMs) have led to the development of various multi model ensemble techniques (MMEs). In the present study, the concept of Canonical Correlation Analysis is used for making MME (referred as Multi Model Canonical Correlation Analysis or MMCCA) for the prediction of Indian summer monsoon rainfall (ISMR) during June-July-August-September (JJAS). This method has been employed on the rainfall outputs of six different GCMs for the period 1982 to 2008. The prediction skill of ISMR by MMCCA is compared with the simple composite method (SCM) (i.e. arithmetic mean of all GCMs), which is taken as a benchmark. After a rigorous analysis through different skill metrics such as correlation coefficient and index of agreement, the superiority of MMCCA over SCM is illustrated. Performance of both models is also evaluated during six typical monsoon years and the results indicate the potential of MMCCA over SCM in capturing the spatial pattern during extreme years.     

Hydrodynamic characteristics of a typical karst spring system based on time series analysis in northern China

In order to study the hydrodynamic characteristics of the karst aquifers in northern China, time series analyses (correlation and spectral analysis in addition with hydrograph recession analysis) are applied on Baotu Spring and Heihu Spring in Jinan karst spring system, a typical karst spring system in northern China. Results show that the auto-correlation coefficient of spring water level reaches the value of 0.2 after 123 days and 117 days for Baotu Spring and Heihu Spring, respectively. The regulation time obtained from the simple spectral density function in the same period is 187 days and 175 days for Baotu Spring and Heihu Spring. The auto-correlation coefficient of spring water level reaches the value of 0.2 in 34–82 days, and regulation time ranges among 40–59 days for every single hydrological year. The delay time between precipitation and spring water level obtained from cross correlation function is around 56 days for the period of 2012–2019, and varies among 30–79 days for every single hydrological year. In addition, the spectral bands in cross amplitude functions and gain functions are small with 0.02, and the values in the coherence functions are small. All these behaviors illustrate that Jinan karst spring system has a strong memory effect, large storage capacity, noticeable regulation effect, and time series analysis is a useful tool for studying the hydrodynamic characteristics of karst spring system in northern China.© 2021 China Geology Editorial Office.     

基于海岛生态指数的2019年海岛生态状况评价及影响因素分析

海岛是我国社会经济发展的重要战略空间,也是生态安全的重要屏障,评价海岛的生态状况是海岛合理利用和保护管理的基础。文章选取77个海岛为研究对象,根据海岛生态指数评价方法,对2019年各海岛生态状况进行评价。结果表明:评价海岛以生态状况优良海岛为主,乡镇级有居民海岛和无居民海岛生态状况显著好于村级有居民海岛,渤黄海区和东海区海岛生态指数分布相似,优良海岛比例高于南海区海岛。植被覆盖率、自然岸线保有率和污水处理率是影响海岛2019年生态状况的主要因素。重视和加强村级有居民海岛的生态保护与建设投入力度,合理利用海岛资源,优化保护与开发空间布局,尽可能地保留自然岸线,提高海岛污水处理能力,将有助于改善海岛生态状况,推动实现海岛的可持续发展。     

陆面热力因子应用于中国夏季降水预测的初步试验

基于对中国东部夏季降水与欧亚大陆土壤温度和全球海表温度的相关分析,选取不同关键区的土壤温度和海表温度作为夏季降水的预测因子。利用1961-1990年的资料,分别以土壤温度作为第1组预测因子,海表温度作为第2组预测因子,综合海表温度与土壤温度因子作为第3组预测因子,使用改进的典型相关分析和集合典型相关分析法对中国东部夏季降水场进行预测,建立了相应的预测模型。然后,利用1991—2010年的资料进行了独立样本预测试验。在独立样本预测试验中,综合海表温度与土壤温度因子建立的模型比只用海表温度进行预测的各项预测评分高,说明加入土壤温度因子后预测效果有所提高。基于陆面热力因子的预测模型对夏季降水有一定的技巧,而综合海温与陆面热力因子的预测模型对中国东部夏季降水有较高的预测能力。     

联合GNSS和GRACE数据分析南极跟踪站的径向形变

利用南极大陆12个累积观测数据超过3年的GNSS跟踪站的监测序列,比较分析了其径向的形变趋势与GIA(Glacial Isostatic Adjustment)模型预测形变,并且与GRACE(Gravity Recovery and Climate Experiment)估计的径向位移结果进行相关性分析。GNSS结果显示跟踪站的径向形变多呈现上升趋势,少量出现下降的跟踪站多分布在东南极沿海区域,下降速度较小。与GRACE计算结果相比,两者的相关系数在0.241—0.663之间,表明两种观测手段得到的结果总体呈现较强的相关性。GNSS形变趋势与最新的GIA模型(W12a)预测形变趋势有一定的偏差,但总体吻合。     

山西夏县中心地震台断层逸出气氡、溶解水氡测值干扰因素分析

山西夏县中心震台断层逸出气氡及溶解水氡分别观测中条山山前断裂土壤逸出气氡及热水井的水中溶解氡值。观测灵敏度高、信息量大,但易受其他因素的干扰。通过对观测值进行分析,发现,夏县台断层逸出气氡测值与气温呈正相关,与气压呈负相关;气温、气压对夏县台热水井溶解水氡测值几乎没有影响,但受水位的影响较明显。     

提高光谱分析微量钽铌结果准确度研究

发射光谱法简单、快速测定矿样中微量钽铌时,主要伴生元素锡对准确测定微量钽铌有辅助作用。改进在钨、铁等元素干扰存在时,钽铌分析线对选择。与化学分析测试结果比对验证后,发现光谱分析微量钽铌准确度得到很大提高,可满足地质找矿品位0.01%的需要。     

红鳍东方鲀(Takifugu rubripes)形态性状对体重的影响效果

采用通径分析方法,对红鳍东方鲀表型形态性状对体重的影响效果进行研究.结果表明,所测各表型性状与体重之间的相关系数均达到显著水平(P＜0.05)或极显著水平(P＜0.01);体周长1对体重的直接影响(0.533)最大,对体重的决定程度(28.41％)最高,是影响体重的主要因素;全长对体重的直接作用(0.369)较大,间接作用(0.259)最小;体高、尾柄高对体重的直接作用(0.228,0.145)相对较小,主要通过体周长1的间接作用(0.363,0.296)影响体重.所选表型性状对体重的复相关指数R2=0.950,表明所选性状是影响体重的主要性状.利用逐步回归分析方法建立以体周长1、体高、尾柄高为自变量估计体重的多元回归回归方程为:y =-2154.095+42.072x1+33.936x2+72.687x3+50.538x4.