Geochemical Features of the Hubin Spring Gases from the Northern Caldera Lake of the Tianchi Volcano,Changbai Mountains

This paper deals with geochemical features of gas emitted from the Hubin Springs.The Hubin Springs zone,a strong thermal emission zone,is are locatedd at the north edge of the Tianchi caldera lake.Very young deposits with uncertain eruption date are found on the top area of the Tianwenfeng,which might have been formed in one of the recent eruptions or the Millennium Eruption.It is of significance to study the geochemistry features of the emitting gas from the Hubin Springs to understand the activities of the Tianchi Volcano.This paper systematically sampled and analyzed the gases emitted from the Hubin Springs and discussed their geochemistry features.The results show that there is a high content of deep derived gases,such as CO2,He,CH4 and Ar in Hubin Springs zone.The isotopic ratio of He lies between 4.18 and 5.95 Ra.The averaged mantle derived gas content calculated from the 4He/20Ne ratio and He content reaches 67.1%.All these show that the Hubin Springs are located on a special belt of deep gases released in high intensity and large scale.The spatial distribution of Helium isotope is characterized by concavity,showing that this special area may be related to the volcanic edifice.It is highly possible that the released gases represent the residual gas samples of the latest eruptions from the Tianchi Volcano.However more detailed studies are demanded.     

The glacier area changes in the Qangtang Plateau based on the multi-temporal grid method and its sensitivity to climate change

Glacier area changes in the Qangtang Plateau are analyzed during 1970-2000 using air photos,relevant photogrammetric maps and satellite images based on the multi-temporal grid method.The results indicate that the melting of glaciers accelerated,only a few of glaciers in an advancing state during 1970-2000 in the whole Qangtang Plateau.However,the glaciers seemed still more stable in the study area than in most areas of western China.We estimate that glacier retreat was likely due to air temperature warming during 1970-2000 in the Qangtang Plateau.Furthermore,the functional model of glacier system is applied to study climate sensitivity of glacier area changes,which indicates that glacier lifespan mainly depends on the heating rate,secondly the precipitation,and precipitation increasing can slow down glacier retreat and make glacier lifespan prolonged.     

灰色系统理论在地下水水质预报中的应用

本文论述了“灰色系统”理论,模型建立步骤以及计算、检验、精度分析方法,并用郑州市地下水中氯离子浓度随时间变化作为实例进行了具体的预报。     

地下水VOCs污染修复技术探讨

污染物事故性排放、工矿企业搬迁后遗留的污染场地修复面临各种问题,给地下水资源的使用带来严重威胁。地下水VOCs污染,具有易扩散迁移、毒性高、风险大的特点,修复难度较高。本文结合典型深层地下水修复案例,充分分析场地地质背景、水文地质条件等,根据污染物的特性、污染范围和分布特征,探讨各种修复技术的修复机理、修复对象和技术特点,针对VOCs污染修复进行性能比较及适用性分析。同时通过两个阶段的试验综合研究,原位和异位技术相结合,为开展类似地下水VOCs污染修复实践和管理提供了依据和思路。     

基于卷积神经网的CCTV视频中排水管道缺陷的智能检测

作为地下空间信息测绘工作的一个重要部分,基于排水管道内部测绘信息的管道缺陷检测越来越受到人们的重视。CCTV技术是一种广泛使用的排水管道内部测绘与缺陷检测技术。近些年基于卷积神经网的人工智能技术在图像识别中取得了巨大成功,受此启发,提出了一种基于卷积神经网络的排水管道缺陷的检测方法,以提高CCTV视频中的管道缺陷检测的自动化和智能化。试验证明了该方法的有效性,其在缺陷识别的准确率和召回率及识别速度上均满足了排水管道缺陷智能检测的需要;同时该方法也已经在深圳市的排水管道检测中得到广泛的应用。     

广州地区稻田甲烷排放及中国稻田甲烷排放的空间变化

１９９３年在广州地区采用中国科学院大气物理研究所研制的自动采集和分析系统测量了稻田甲烷的排放率，首次获得了占我国２０－２５％左右水稻收获面积的华南地区稻田甲烷排放特征值。从而宏观地使我国五个主要水稻生态区的甲烷排放率都有了实测资料。稻田甲烷排放率的季节变化主要与气温及灌溉水状态的变化的较大关系，日变化规律以下午出现极大为主。本实验田的甲烷排放率低。     

中国火山温泉气体地球化学特征及其在火山监测中的应用

中国火山温泉主要分布在吉林长白山、云南腾冲和黑龙江五大连池等火山区。这些火山虽然处于休眠状态,但大面积的温泉分布指示着岩浆房存在的可能性。本文总结了前人研究成果,分析了中国主要火山区温泉气体地球化学特征,并探讨了温泉气体在火山监测中的应用。长白山、腾冲和五大连池火山区温泉气体地球化学性质类似,都以CO₂为主要气体,含量在80%以上,最高可达99%以上,其它气体组分包括CH₄、N₂、O₂、SO₂、H₂S、He和H₂等。长白山火山温泉气体中氦同位素比值（3He/4He）最高,约为4—6R_A,CO₂中碳同位素比值（δ13C）为-7.9‰—-1.3‰,CH₄中碳同位素为-48.0‰—-28.7‰;腾冲火山温泉气体氦同位素比值为3—5.5R_A,CO₂中的碳同位素为-6.49‰—-2.07‰,CH₄中碳同位素为-23.5‰—-9.3‰;五大连池火山温泉气体氦同位素比值约为3R_A,CO₂中的碳同位素比值为-9.6‰—-3.1‰,CH₄中碳同位素为-47.2‰—-44.4‰。3个火山区的温泉气体均显示地幔来源的岩浆气体特征,并在上升运移过程中受地壳或古俯冲物质的影响。     

辽东湾红沿河附近海域2017—2018年冬季气温-水温-冰情关系研究

辽东湾是我国冰情最严重海域,每年冬季都会受到海冰的显著影响,冰情预测评估可为辽东湾涉海活动提供防冰抗冰的技术依据。建立气温-水温-冰情的相关性,结合便于获取的现场高精度连续气象数据和高精度冰情预测模型,可实现局地小尺度的冰情快速预测评估。基于2017—2018年冬季辽东湾东岸红沿河附近海域实测气象-水温-冰情同步观测数据,结合辽东湾大尺度整体冰情（浮冰面积）,推演局地气温、水温与不同尺度冰情评价参数（浮冰范围与冰厚）的相关关系,提出基于不同气温区间的气温变化规律的冰底热通量选取方法,进而建立适用于辽东湾的气温-水温-冰情评估方法。相关性分析结果显示：观测点气温与水温存在明显相关性;浮冰范围与气象数据存在明显相关性,临界温度为 -5 ℃的累计负气温能很好拟合本年度盛冰期浮冰范围。基于HIGHTSI进行数值模拟后发现：水温与块体积法计算冰底热通量时,冰水间的热传递系数取2.2×10^-5是可行的;水温对冰情的影响表现在海冰冰厚最大值与冰期长短。为弥补辽东湾其他海域因缺少实测海水温度观测数据欠缺、冰底热通量选取不准选取导致的冰情模拟预测评估困难的问题,本文依据水温与气温的相关性,将水温随气温变化划分为结冰区（气温小于-10 ℃时水温维持冰点附近）、过渡区（气温为-10~-5 ℃时水温处于-1.4~-0.4 ℃）、融冰区（气温高于-5 ℃时水温随气温的增大逐渐增大）,进而提出适用于辽东湾所有海域的冰底热通量计算方法和冰情评估方法。     

北方某废弃矿区地下水污染帷幕注浆应急处置研究

随着我国煤炭资源的枯竭,大量矿山关闭,遗留了广大的地下采空区场地。不少化工企业向废弃矿井内倾倒化学废液等导致了矿区地下水污染事故,威胁地下水水源地的水源安全。针对此类复杂场地条件下污染事故的应急处置案例和经验都非常少,本文以北方某废弃矿区地下水污染注浆帷幕应急处置为例,通过对矿区地质条件的分析、地下空间结构和地下水流场的刻画,构建三维地质模型,以模型为基础设计帷幕注浆工程并实施,研究复杂场地条件下开展帷幕注浆应急处置的重要内容和决定因素,并利用场地地下水样品监测结果,分析研究帷幕内外污染物浓度分布特征及差异,找出地下水运移规律,评价注浆帷幕效果。研究表明：在事故井周边100 m范围实施的帷幕注浆工程,对污染物运移的封堵效果显著,帷幕注浆内外污染物含量差距明显。一期检测结果显示帷幕注浆范围内地下水中二氯甲烷浓度最高1390 μg/L,帷幕范围外最高浓度仅为8. 07 μg/L;二期检测结果为污染物检出浓度大于5 μg/L的区域全部位于帷幕范围内,帷幕范围外均未检出。同时污染物的分布特征指示着地下水沿巷道运移成为最主要的形式,对地下空间结构的精准刻画是决定帷幕注浆工程成效的重要因素。     

Using data‐driven methods to explore the predictability of surface soil moisture with FLUXNET site data

Soil moisture (SM) is a key variable of land surface‐atmosphere interactions. Data‐driven methods have been used to predict SM, but the predictability of SM has not been well evaluated. This study investigated what variables and methods can be used to better predict SM for leading times of 7 days or longer with a global coverage of FLUXNET site data for the first time. Three machine‐learning models, that is, Bayesian linear regression, random forest, and gradient boosting regression tree, are used for the prediction. Variables including atmospheric forcing, surface soil temperature, time variables (year, day of year, and hour), the Fourier transformation of time variables, and lagged SM (7‐ to 14‐day lagged) were sequentially added into models. A framework with five experiments is designed for factorial exploration of SM predictability. A stepwise method was used to build the best models for each site. The performance of regression models became better when adding more explaining variables in most cases. The results showed that from 50 to 95% of variation of the best models can be explained. The important explaining variables are lagged surface SM, followed by day of year, year, soil temperature, and atmospheric forcing. The predictability of SM depends highly on SM memory characteristics and the persistence of seasonality. The effect of SM memory characteristics on SM prediction as an initial condition question has been widely discussed in this paper. Our results also provide an insight that mechanisms of seasonality effects on SM should be also paid more attention to.