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1.
2.
由中国地质科学院矿产资源所编制出版的《南岭成矿带成矿规律图(1∶80万)》,是迄今为止矿种最全、资料最新、信息量最大的全面反映我国南岭勘查成果与成矿规律的区带级别(Ⅲ级成矿单元)成矿规律图。该图件研编实现了4大创新点:① 涵盖了南岭已发现的2903处独立矿产地,包括能源、金属、非金属和水气矿产等4大类的76个矿种,实现了南岭成矿带矿种与矿产地的全覆盖;② 归并了地质底图的地层并淡化显示,突出华南岩体、隐伏岩体的特色,使得不同构造—建造层地质单元的分布格局一目了然;③ 实现了矿产地、规模、类型、时代、成矿系列五位一体的综合图例设计,矿产地表达更简洁、直观;④ 综合成矿系列图、表、成矿体系图、剖面图等,以区域规律图编制的新思路和新方法,更集中反映和彰显南岭成矿带最新科研成果。该图件的研编有助于直观展示南岭成矿带矿产的时空分布格局,深入总结成矿规律,科学圈定重要找矿远景区,对于全面指导南岭的地质找矿工作具有重要的意义。 相似文献
3.
对湖泊总磷的变化预测和来源识别对水资源调度和流域生态治理有着重要的意义,然而复杂的生化反应和水动力条件导致的非平稳性给湖泊总磷浓度的准确预测带来极大的困难。为克服这一挑战,本文引入了基于加权回归的季节趋势分解(seasonal and trend decomposition using Loess,STL)技术和夏普利加法(SHapley additive exPlanations,SHAP)结合长短期记忆网络(long short-term memory neural network,LSTM)和门控循环单元(gated recurrent unit,GRU)构建了一个可解释的预测框架,以增强对湖泊总磷浓度演变的预测并提高其可解释性。研究表明:(1)在骆马湖总磷浓度的预测中,该框架拥有较好的预报精度(R2=0.878),优于LSTM和卷积长短期记忆模型(convolutional neural networks and long short term memory network,CNN-LSTM)。当预测时间步长增加到8 h时,该框架有效提高了总磷浓度的预测精度,平均相对误差和均方根误差分别降低了47.1%和33.3%。从预测趋势来看,骆马湖在汛期的总磷平均浓度为0.158 mg/L,相较于非汛期的平均浓度,增加了202.1%。(2)运河来水是骆马湖总磷浓度最重要的影响因素,贡献权重为60.0%,并且不同断面(三湾、三场)的污染源受水动力、气象等因素的影响存在显著的时空差异。本文凸显了神经网络模型在预警水体污染方面的可实施性,并且为提高传统神经网络的学习能力和可解释性的开发与验证提供了重要方向。 相似文献
4.
An advanced one-dimensional radiative-convective model (RCM) is used to estimate the past, present and fu-ture climatic forcings induced by greenhouse gases of anthropogenic origin, such as CO2, CH4, N2O and CFCs, in this paper. The results show that the decadal climatic forcing for the last decade is one-order bigger than that prior to the year 1900, and in the case of no control on the emission of the greenhouse gases the climatic forcing for the year 2100 will be almost 4 times as much as now. 相似文献
5.
The characteristics of the response of equatorial Pacific upper ocean current to westerly wind bursts(WWB)were analyzed in the frequency domain by using wind and ADCP data collected by the Shiyan3 during TOGA-COARE IOP,1992-1993.The preliminary results showed that the response consistedof an eastward surface jet at shallower than 60m depth,a westward counter current centering near100m and a shear layer between them,with the variations of all three being nonlinear and nearlysynchronous.The oceanic responses in the frequency domain were characterized by occurrences of a remotely forced mixed Rossby-gravity wave with period of 8-10 days in the surface jet andcountercurrent at shallower than 110 m depth,and two locally forced waves with periods of 24 daysand 4-5 days limited in shallower than 70m depth.These fluctuations of the responses depended much more on zonal wind than meridional wind.The results also revealed that the oceanic response toWWB resulted from momentum transport and energy propagation assoc 相似文献
6.
自20世纪60年代初以来,地理信息系统引领了地理信息的分析与服务。然而,由于地理学家对于地理过程开展多维模拟的需求,同时许多大型工程需要对于不同方案的后果事先开展模拟评估,为此中国学者们在世纪相交之际开始了对于虚拟地理环境的探索。本文从地理信息系统到虚拟地理环境的认识上的转变着手,分析了虚拟地理环境的演进过程、当前的阶段定位与挑战,着重探讨了虚拟地理环境研究的新态势:基于虚拟地理环境的地理空间认知研究、虚拟地理环境与实验地理学新方向、大数据背景下的虚拟地理认知实验方法和虚拟地理环境与地理知识工程,并给出最新研究思路。 相似文献
7.
西北太平洋海陆相互作用强烈,受黑潮和亚洲大陆风尘输入影响显著,是研究海洋沉积物中有机碳埋藏与陆源输入、海洋初级生产力和海洋环境演化关系的理想靶区。本研究基于采自九州-帕劳海脊北部的重力活塞647 cm长的KPR12岩芯,分析了总有机碳(TOC)、总氮(TN)、有机碳稳定碳同位素组成(δ13CTOC)、蛋白石(Opal)以及粒度等指标,初步探讨了近40万年来轨道尺度沉积有机碳的来源、埋藏特征及其影响机制。岩芯的TOC含量平均值为0.214%,呈冰期较高、间冰期较低的旋回特征。岩芯沉积物粒度的不同端元反映了研究区风尘输入大致呈冰期较高的趋势。岩芯的δ13CTOC(-25.24‰~-21.04‰,平均值为-22.59‰)显示有机质以海源为主(约62%),海源有机碳含量趋势与TOC的变化一致。研究区不同时期陆源物质的输入受风尘输送和黑潮的综合控制,黑潮增强可能对该区间冰期陆源有机碳贡献的升高有一定影响。岩芯中TOC与Opal含量的相关性分析表明,海洋初级生产力可能不是控制该岩芯有机碳含量变化的主要原因。冰期-间冰期旋回中的深层水通风条件、黑潮和北太平洋中层水的发育以及陆源细颗粒物质输入可能共同影响着本区沉积有机碳的降解与埋藏保存。
相似文献8.
Silicon limitation on primary production and its destiny in Jiaozhou Bay, China——Ⅳ:Study on cross-bay transect from estuary to ocean 总被引:1,自引:0,他引:1
The authors analyzed the data collected in the Ecological Station Jiaozhou Bay from May 1991 to November 1994, including 12
seasonal investigations, to determine the characteristics, dynamic cycles and variation trends of the silicate in the bay.
The results indicated that the rivers around Jiaozhou Bay provided abundant supply of silicate to the bay. The silicate concentration
there depended on river flow variation. The horizontal variation of silicate concentration on the transect showed that the
silicate concentration decreased with distance from shorelines. The vertical variation of it showed that silicate sank and
deposited on the sea bottom by phytoplankton uptake and death, and zooplankton excretion. In this way, silicon would endlessly
be transferred from terrestrial sources to the sea bottom. The silicon took up by phytoplankton and by other biogeochemical
processes led to insufficient silicon supply for phytoplankton growth. In this paper, a 2D dynamic model of river flow versus
silicate concentration was established by which silicate concentrations of 0.028–0.062 μmol/L in seawater was yielded by inputting
certain seasonal unit river flows (m3/s), or in other words, the silicate supply rate; and when the unit river flow was set to zero, meaning no river input, the
silicate concentrations were between 0.05–0.69 μmol/L in the bay. In terms of the silicate supply rate, Jiaozhou Bay was divided
into three parts. The division shows a given river flow could generate several different silicon levels in corresponding regions,
so as to the silicon-limitation levels to the phytoplankton in these regions. Another dynamic model of river flow versus primary
production was set up by which the phytoplankton primary production of 5.21–15.55 (mgC/m2·d)/(m3/s) were obtained in our case at unit river flow values via silicate concentration or primary production conversion rate.
Similarly, the values of primary production of 121.98–195.33 (mgC/m2·d) were achieved at zero unit river flow condition. A primary production conversion rate reflects the sensitivity to silicon
depletion so as to different phytoplankton primary production and silicon requirements by different phytoplankton assemblages
in different marine areas. In addition, the authors differentiated two equations (Eqs. 1 and 2) in the models to obtain the
river flow variation that determines the silicate concentration variation, and in turn, the variation of primary production.
These results proved further that nutrient silicon is a limiting factor for phytoplankton growth.
This study was funded by NSFC (No. 40036010), and the Director's Fund of the Beihai Sea Monitoring Center, the State Oceanic
Administration. 相似文献
9.
为实现矿产资源储量管理网络实时查询功能,在目前国土资源部金土工程的储量管理软件的基础上,开发出了"基于C/S的矿产资源开发储量管理信息系统".该系统采用了结构化的程序设计方法,操作系统平台采用了MS Windows系统,程序开发平台采用了Borland公司Delphi,数据库的查询语言采用标准SQL查询语言,主要实现了矿产资源开发和储量数据的综合查询和汇总功能. 相似文献
10.
ECOLOGICAL SERIES OF SOIL ANIMALS IN DARLIDAI MOUNTAIN 总被引:1,自引:0,他引:1
HOUWei-ling FANHong 《中国地理科学(英文版)》2002,12(4):378-382
The ecological series of soil animals under the broad-leaved and pine mixed forest in Darlidai Mountainwas studied. Seven sample plots were selected according to different altitude gradients, which belong to different vegeta-tion types. By investigating and analyzing soil animals in every sample plot it is found that there are 45 groups and 1956individuals, which axe involved in 3 phylums, 7 classes, 16 orders, respectively. The altitude is a key factor which af-fects ecological series of soil animals. Both the groups and individuals of soil animals increase with altitude increasingunder certain conditions, which contrastes with ordinary cases, resulting from special micro-climate in studied area. Thegroups and individuls of soil animals are the most under the broad-leaved and pine forest on the top of the mountain, andthe least under Picea-Abies forest in the foot of the mountain. 相似文献