西太平洋海山磷酸盐的常量、微量和稀土元素地球化学研究

本文对主要取自于西太平洋我国调查区内不同海山、不同水深、不同产状的13个磷酸盐样品进行了常量、微量和稀土元素测定,以探讨与大洋富钴结壳密切伴生的磷酸盐的常、微量和稀土元素地球化学的特征。分析结果表明,调查区磷酸盐中主要氧化物的平均值与赤道太平洋的相近,暗示两者可能有相似的形成环境和形成机制。磷酸盐中微量元素Sr、Ba、Co、Cu、Ni及U丰度分别变化于862×10~(-6)～2181×10~(-6)、29×10~(-6)～3429×10~(-6)、6.3×10~(-6)～115×10~(-6)、23×10~(-6)～263×10~(-6)、12×10~(-6)～825×10~(-6)及4×10~(-6)～11×10~(-6),丰度多数低于泥质岩平均值,其CaO/P_2O_5、F/CO_2、Sr/P_2O_5值及常量、微量元素间的相关关系,清晰地显示了磷酸盐的种类、成分与结构、形成的地质背景和元素的主要组合特征。磷酸盐的稀土丰度为136.50×10~(-6)～853.70×10~(-6);Ce~*变化于0.01～0.18之间;(Ce/Yb)_N值变化于0.01～0.21之间。研究证实,不同产状磷酸盐的稀土元素配分模式基本一致,曲线相互平行,基本不呈现交叉现象,均呈Ce强烈亏损,轻、重稀土分馏程度大及重稀土富集的型式。调查区、赤道太平洋、中太平洋磷酸盐的稀土元素丰度、Ce~*、Ce/Yb值以及它们与海水稀土元素配分模式相似的特征,也进一步显     

A unified C-band and Ku-band geophysical model function determined by neural network approach

The geophysical model function （GMF） describes the relationship between backscattering and sea surface wind, so that wind vec- tors can be retrieved from backscattering measurement. The GMF plays an important role in ocean wind vector retrievals, its performance will directly influence the accuracy of the retrieved wind vector. Neural network （NN） approach is used to develop a unified GMF for C-band and Ku-band （NN-GMF）. Empirical GMF CMOIM and QSCAT-1 are used to generate the simulated training data-set, and Gaussian noise at a signal noise ratio of 30 dB is added to the data-set to simulate the noise in the backscat- tering measurement. The NN-GMF employs radio frequency as an additional parameter, so it can be applied for both C-band and Ku-band. Analyses show that the %predicted by the NN-GMF is comparable with the σpredicted by CMOIM and QSCAT-1. Also the wind vectors retrieved from the NN-GMF and empirical GMF CMOIM and QSCAT-1 are comparable, indicating that the NN-GMF is as effective as the empirical GMF, and has the advantages of the universal form.     

Distribution and sources of heavy metals in the sediment of Xiangshan Bay

Heavy metals in the surface sediments and sediment core from the Xiangshan Bay, a mariculture base on the coast of the East China Sea, were determined by inductively coupled plasma mass spectrometry(ICP–MS) in order to evaluate their levels and sources. The results showed that the levels of Cu, Pb, Zn, and Cr in the sediments of the bay have been generally influenced by anthropogenic inputs since the founding of the People's Republic of China. In particular, Cu and Zn were polluted to some extent, as evidenced by high enrichment factors. Organic matter, grain size, wastewater discharge, and low energy hydrodynamic environment played dominant roles in the heavy metal enrichment in the sediments. The ratio of terrigenous source to marine biogenic deposit of trace metals in the sediments was calculated, revealing that terrigenous inputs were the main source of Cu, Pb, and Zn, while biological pellets contributed much more to the enrichment of Cr and Cd. Considering the influence of biological sources on the enrichment of Cd and Cr, and the fact that the sediment has been polluted by Cu and Zn, the development of mariculture and discharge of wastewater into the Bay should be restricted.     

GA-BP神经网络在罗源湾口波浪模拟研究中的应用

由于BP神经网络存在收敛速度慢和易于陷入极小值等缺点,引入遗传算法(GA)对网络的权值和阈值加以优化,并采用不同组合的输入因子和样本数,对福建省罗源湾口的波浪进行模拟研究.对输入因子的分析结果表明,研究区域的波浪主要受台湾海峡波浪传播影响,与局地气象因子(风速、风向、海气温差)的相关性较弱.训练样本试验表明,30 d以上的波浪历史数据可使GA-BP神经网络充分学习研究区域的波浪特征,从而实现对波浪要素的高精度模拟.模拟结果显示,对春、夏季实测波浪数据的模拟效果均很好,其中相关性分别为0.967和0.938,均方根误差分别为0.112 m和0.107 m,表明GA-BP神经网络在近岸波浪模拟预报中有较广阔的应用前景.     

鳗弧菌(Vibrio anguillarum)对青蛤(Cyclina sinensis)的毒性及半致死浓度研究

利用不同浓度的鳗弧菌对青蛤进行了急性毒性实验,观察青蛤在菌液胁迫下的存活情况,进一步统计得到鳗弧菌对青蛤的半致死浓度。结果表明,青蛤在鳗弧菌液浓度OD600为1.0—2.2范围内,胁迫96h以内死亡率呈逐渐上升趋势,并且在OD600=2.2时所有受试个体全部死亡。在相同的胁迫时间内,受试个体死亡率与胁迫浓度均呈正相关。经SPSS16.0软件分析后,最终得到鳗弧菌对青蛤的半致死浓度(LC50)为OD600=1.57,说明鳗弧菌对青蛤有明显的毒害作用。     

The algorithms of chlorophyll-a concentration for CMODIS

The algorithms of extracting chlorophyll-a(Chl-a) concentration have been established for Chinese moderate resolution imaging spectrometer(CMODIS) mounted on Shenzhou-3 spaceship launched on 25 March 2002.The CMODIS is an ocean color sensor with 30 visible channels and 4 infrared channels,much different from other ocean color satellites and needs new algorithms to process data.Three models of Chl-a concentration were established based on Chl-a data retrieved from sea-viewing wide field-of-view sensor(SeaWiFS),with the average relative errors of 26.6%,24%.0% and 33.5%,respectively.This practical and economic approach can be used for developing the algorithms of Chinese ocean color and temperature sensor(COCTS) on the satellite Haiyang-1 to derive the Chl-a concentration concentration distribution.The applicability of the algorithms was analyzed using some in situ measurements.Suspended sediment is the main factor influencing the accuracy of the spectral ratio algorithms of Chl-a concentration.The algorithms are suitable to using in the regions where suspended sediment concentrations(SSC) are less than 5 g/m3 under the condition of relative error of Chl-a concentration retrieval within 35%.High concentration of suspended sediment leads to the overestimate remote sensing retrieval of concentration of Chl-a,while low-middle SSCs lead to the low Chl-a concentration values using the spectral ratio algorithms.Since the accuracy of Chl-a concentration by the spectral ratio algorithms is limited to waters of Case 2,it is necessary to develop semi-analytical models to improve the performance of satellite ocean color remote sensing in turbid coastal waters.     

地面核磁共振信号相位求取电阻率

椭圆极化现象是电磁场在导电介质中传播时产生的,为得到准确的相位信息,在计算激发磁场时应考虑椭圆极化。本文研究了地面核磁共振(SNMR)信号相位求取电阻率的基本方法,利用SNMR信号通过广义逆反演法得到电阻率未知情况下的含水率及层位分布,作为相位反演电阻率的先验值,通过模拟退火法实现对电阻率的反演。对SNMR的研究解决了通过相位对电阻率的求取,有利于进一步利用相位信息提高含水层和含水率反演的精度。     

云南小江流域典型泥石流沟中底栖动物群落特征及其对河流地貌的响应

云南小江流域为典型干热河谷区,该区域干热少雨,流域内泥石流沟众多,生态环境十分脆弱.2017年4月和9月对小江流域的吊嘎河、蒋家沟、蓝泥坪沟、清水沟、陶家小河5条泥石流沟及小江干流开展了系统调查,旨在摸清5条泥石流沟及小江干流河流地貌、水环境及底栖动物群落现状,分析不同河床结构发育程度的泥石流沟间的底栖动物群落差异,揭示底栖动物对反映河床结构发育程度的河流地貌特征参数凹凸度的响应关系.调查期间于5条泥石流沟及小江干流中共采集到底栖动物70种,隶属于4门6纲38科69属,其中环节动物6种,软体动物2种,节肢动物61种,扁形动物1种.从种类类群来看,5条泥石流沟及小江干流的底栖动物物种数、密度、生物量上均以节肢动物占绝对优势,分别占总量的78.0%~92.5%、98.7%~100%、65.0%~100%.从功能摄食类群上来看,5条泥石流沟及小江干流底栖动物密度上均以直接收集者为主,占总量的74.3%~96.3%.回归分析表明,5条泥石流沟中底栖动物物种数、密度及生物量均与河流地貌特征参数凹凸度呈正相关关系,由此可见,发育良好的河床结构在维持河流地貌稳定和改善河流生态方面起着举足轻重的作用.本研究结果可为小江流域山区河流泥石流沟河床结构重建及生态修复提供科学依据.     

基于深度学习的地震速度谱自动拾取研究

在常规的地震数据处理工作流程中,人工拾取地震速度谱中的叠加速度存在耗时长、效率低的问题,且容易受到人为经验的影响.本文基于目标检测的方法,应用改进后的FCOS（Fully Convolutional One-Stage Object Detection）神经网络模型实现速度谱中叠加速度的自动拾取.该方法将速度谱图像作为输入,经模型训练后输出"时间-速度"对序列.在处理低信噪比工区数据时,针对速度谱能量团聚焦特征较差的特点加入基于深度神经网络（Deep Neural Network,DNN）的线性回归模型以拟合出全局速度曲线.Marmousi模型数据和实际工区数据测试结果表明,本文所设计的地震速度谱自动拾取模型准确性较高、鲁棒性强,有效地缓解了人工拾取的负担,在保证速度拾取精度的同时显著地提高了效率.     

松辽盆地南部上白垩统中部组合层序界面的识别标志及高分辨率层序地层格架

系统总结了松辽盆地南部中部组合层序界面的岩心、测井、生物、地震等识别方法;统计了盆地短轴方向不同相带层序界面及短期基准面旋回的分布特征,并分析了层序界面和短期旋回模式在不同相带的分布规律。中部组合青山口组和姚家组共划分为4个长期旋回和10个中期旋回。在层序地层序、沉积学原理的指导下,采用岩心、测井、地震三位一体,点、线、面紧密结合,以岩心、测井层序划分为基础,以地震技术为手段进行层序地层的立体拓展,建立层序地层格架,为下一步勘探提供了重要的依据。