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通过对2013年采自龙口湾的表层沉积物样品进行激光粒度分析和X-射线衍射(XRD)分析,根据其表层沉积物粒度及黏土矿物组成分布特征,来探讨大规模人工岛建设对龙口湾表层沉积物粒度分布及黏土矿物组成特征的影响。结果表明,龙口湾沉积物粒度以粉砂为主(62.90%),黏土(18.05%)和砂(19.05%)的质量分数相近。龙口湾表层沉积物的黏土矿物组成与莱州湾整体沉积物组成相近,其不同组分质量分数表现为伊利石蒙皂石绿泥石高岭石,但个别矿物的含量仍存在一定差异。表层沉积物粒度分布及黏土矿物的组合特征表明,尽管龙口湾的沉积物仍以沿岸河流输沙、风沙和岛岸侵蚀为主,但沿岸大规模人工岛建设已对其组合特征产生重要影响。粒度组成上黏土质量分数略有升高,砂质量分数略有下降;黏土矿物组成上表现为蒙皂石的最大质量分数升高24.55%,绿泥石和高岭石的最大质量分数均下降35%左右,而伊利石质量分数最高且变化不大。通过对龙口湾表层沉积物粒度分布及黏土矿物组成特征的研究,可在一定程度上揭示大规模人工岛建设对龙口湾的沉积环境的影响。 相似文献
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本文根据粒度分析资料,研究了长城湾、南阿德雷湾及长城站区周围表层沉积物的粒度特征、类型与分布,讨论了采样区的自然环境因素(如物质来源、地形地貌、风暴或极地气旋、海湾水动力条件、冰川与浮冰、冰冻与融冻现象等)对碎屑沉积物的性质与分布的影响,从而揭示了冰海沉积环境和沉积物的特殊性。 相似文献
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《应用海洋学学报》2015,(3)
本文利用福建省泉州湾海域采集的70个表层沉积物样品,分析了泉州湾表层沉积物粒度参数的平面分布特征及输运趋势.对沉积物的粒度参数进行了Q型聚类分析,开展了沉积物曲线特征在横向上的分布研究,并针对沉积物不同粒级组分对沉积物来源做了R型因子分析.粒度分析结果表明,不同粒度参数(平均粒径、分选系数、偏态、峰态)在横向上具有不同的变化特征,很大程度上受到潮汐水流的影响,同时入海河口、岛屿周边和局部凸凹岸都会成为其影响因素.沉积物输运趋势分析结果显示,沉积物主要来源于晋江和洛阳江的输入、研究区南侧海岸侵蚀物向北运移后的沉积及外海海流的带入;Q型聚类分析把沉积物分为两群四类,能很好地反应出沉积物粒度概率曲线的变化特征;R型因子分析进一步探讨了沉积物粒度特征可能的影响因素,以陆源碎屑特征和水动力变化影响为主,其次是生物碎屑沉积和人工采砂. 相似文献
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沉积物分布对河口海岸地区的地貌演变和岸线变化非常重要。本文收集了2008年9月厦门湾海域的230个表层沉积物样品的数据,研究其表层沉积物空间分布和运输特征。厦门湾海域表沉积物的粒度分布特征非常明显。同时在应用GSTA模型对沉积物进行输运趋势分析的基础上探讨该区域泥沙运移趋势。结果表明,该海域有八种沉积物类型,粘土质粉砂占有比例最高,为65.22%;而且在不同的分区,由于不同的沉积物源和水动力条件,粒度参数特征也有所不同。径流、潮汐和波浪是海床表层沉积物、滩涂变化的主要控制动力,泥沙运动趋势与水动力条件密切相关。 相似文献
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在苏北废黄河三角洲海域采集了266个表层沉积物样品,经粒度分析获得各样品粘土、粉砂和砂3种粒级组分的质量百分数,在此基础上运用地统计学方法和GIS软件分析了粘土、粉砂和砂3种粒级组分的空间变异特征,根据空间变异特征研究结果,用Kriging插值方法绘制了各粒级组分的空间分布图.结果表明：废黄河三角洲表层沉积物中砂组分具有较强的空间自相关性,其自相关距离为30.5 km;粘土和粉砂具有中等的空间自相关性,其自相关距离分别为40.3 km和13.8km.在大于17.0 km的尺度上,3种粒级组分的空间变异性表现出明显的各向异性特征,且以NE55°和SE145°两组相互垂直的方向上差异最为明显,这是由于波浪、潮流等因素作用所引起的沉积物离岸梯度变化造成的.制图结果显示,废黄河三角洲表层沉积物3种粒级组分的空间分布状况,粘土表现为近岸低、远岸高;砂表现为近岸高、远岸低,高值区主要在河口附近;粉砂表现为均匀性特征. 相似文献
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现代废黄河口表层沉积物的年代际空间分布与主控因素 总被引：1，自引：0，他引：1
基于现代废黄河口的不同年代表层沉积物粒度资料,研究了废河口区表层沉积物的年代际空间分布特征及变化趋势;结合水动力、地形地貌资料,探讨了影响表层沉积物空间格局的主控因素。研究结果表明,现代废黄河口表层沉积物空间分布存在限制的年代际变化特征,不同年代空间分布总体表现出近岸较粗、离岸变细的趋势。1992年研究区表层沉积物粒度总体较细;1992—2000年研究区表层沉积物显著粗化;2000—2007年大部分区域表层沉积物进一步粗化;2007—2015年研究区表层沉积物空间分布无明显变化。研究区表层沉积物的年代际空间分布特征受沉积动力环境及其导致的年代际冲—淤演变格局影响,随着研究区的抗侵蚀能力增强,其表层沉积物的空间分布基本无较大变化。 相似文献
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根据在现代黄河口南岸采集的45个表层沉积物样品与5个柱状沉积物样品的粒度测试结果,研究了现代黄河口南岸沉积物的类型与空间分布特征。通过粒度参数计算和聚类分析方法绘制了粒度概率累积曲线,探讨了沉积物粒度分布特征与物源和沉积动力环境间的关系。现代黄河口至广利河河口的沉积物颗粒呈"粗—细—粗"分布,表层沉积物分为粉砂质砂和砂质粉砂2种类型。通过分析对比柱状沉积物不同深度粒度频率曲线与概率累积曲线,结合对沉积环境和沉积速率的分析,认为黄河河道摆动是影响沉积环境的主导因素。通过对比典型潮滩剖面丰枯季节粒度概率累积曲线发现,广利河在局部区域对沉积环境产生一定的影响。研究表明:黄河改道是影响沉积环境的主导因素,同时,广利河等沿岸河流在河口局部区域对原有沉积环境有一定的改造作用,至莱州湾南岸,沿岸小清河、弥河等河流取代黄河成为影响沉积环境的主导因素。 相似文献
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《应用海洋学学报》2015,(1)
以东山乌礁湾为典型研究区,对海滩5条剖面表层沉积物进行样品采集(0~5 cm)和点位测量,综合应用激光法和筛析法进行粒度测定.结果表明秋季东山乌礁湾表层沉积物以粒径0.16~0.50 mm的砂为主,具有较好的分选性,符合岬湾砂质海滩表层沉积物的一般组分规律和分选特点;粒径分布表现出由南向北逐渐变细的区域差异性,主要是岬湾地形影响下的季节性风浪作用结果;从高潮带至中潮带站位主峰值粒径逐渐增大,粗粒含量增多,至低潮带主峰值粒径变小,粗粒含量降低,是近岸往复水动力作用和剖面地形作用的结果;总体看乌礁湾表层沉积物粒度分布主要受岬湾海岸地形特征和季风影响下的波浪、潮汐等水动力作用以及湾内局地物源输入的影响. 相似文献
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通过对胶州湾44个表层沉积物样品粒度组分进行分析,探讨了该区表层沉积物粒度特征和沉积物类型;并以沉积物组分分布和粒度特征为依据对沉积物进行聚类分析,结合其周边河流以及海底地貌分布,对其沉积环境进行了划分。结果表明,研究区沉积物类型主要有砂质粉砂、粉砂、粉砂质砂和泥;沉积物主要粒级为1.1Φ~7.1Φ,优势粒级为5Φ~7Φ,平均值为5.7Φ,粉砂的平均含量达到58.6%,砂、黏土的平均含量为23.6%和17.3%。将研究区沉积环境划为4类:湾顶及东部近岸浅水区域(I),大沽河—洋河水下三角洲区域(Ⅱ),湾西南部及中部深水区域(Ⅲ)和沧口砂脊周边及湾口区域(Ⅳ)。 相似文献
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黄海渔业资源密度空间插值方法的比较研究 总被引：2，自引：0，他引：2
空间插值是渔业生态学研究,特别是海洋生态系统模型构建中的常用工具。为找到适合黄海渔业资源密度的插值方法,本文对四种常用的空间插值方法进行了比较研究。四种插值方法分别为反距离加权（Inverse distance weighted,IDW）、全局多项式（global polynomial interpolation,GPI）、局部多项式（local polynomial interpolation,LPI）和普通克里格（ordinary kriging,OK）。采用交叉验证分析（cross-validation diagnostic）确定不同插值方法的准确度。同时,结合渔业资源密度空间分布的可视化表达,比较不同插值方法结果的优劣。结果表明,原始的生物学数据具有典型的非正态分布特征,对数转化方法能让其显著地接近或符合正态分布。四个调查阶段中,指数模型在2014年8月和10月为最佳半方差函数,2015年1月和5月数据具有明显的纯块金效应。配对样本T检验表明,预测数据和实测数据之间没有显著差异（P>0.05）。交叉验证结果表明,OK在2014年10月插值效果最好,IDW在剩余的三个航次表现最佳,GPI和LPI表现效果不佳。OK在空间分布的可视化表达方面效果最好,既不像IDW一样有较多的“牛眼”效应,也不像GPI和LPI一样具有过多的平滑效果。然而,纯块金效应的存在有时会影响OK的应用。综上所述,我们推荐操作简单且处理快速的IDW作为黄海渔业资源密度常规的插值方法。 相似文献
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This article evaluates different spatial interpolation methods for mapping submerged aquatic vegetation (SAV) in the Caloosahatchee Estuary, Florida. Data used for interpolation were collected by the Submersed Aquatic Vegetation Early Warning System (SAVEWS). The system consists of hydro-acoustic equipment, which operates from a slow-moving boat and records bottom depth, seagrass height, and seagrass density. This information is coupled with geographic location coordinates from a Global Positioning System (GPS) and stored together in digital files, representing SAV status at points along transect lines. Adequate spatial interpolation is needed to present the SAV information, including density, height, and water depth, as spatially continuous data for mapping and for comparison between seasons and years. Interpolation methods examined in this study include ordinary kriging with five different semivariance models combined with a variable number of neighboring points, the inverse distance weighted (IDW) method with different parameters, and the triangulated irregular network (TIN) method with linear and quintic options. Interpolation results were compared with survey data at selected calibration transects to examine the suitability of different interpolation methods. Suitability was quantified by the determination coefficient (R2) and the root-mean-square error (RMSE) between interpolated and observed values. The most suitable interpolation method was identified as the one yielding the highest R2 value and/or the lowest RMSE value. For different geographic conditions, seasons, and SAV parameters, different interpolation methods were recommended. This study identified that kriging was more suitable than the IDW or TIN method for spatial interpolation of all SAV parameters measured. It also suggested that transect data with irregular spatial distribution patterns such as SAV parameters are sensitive to interpolation methods. An inappropriate interpolation method such as TIN can lead to erroneous spatial representation of the SAV status. With a functional geographic system and adequate computing power, the evaluation and selection of interpolation methods can be automated and quantitative, leading to a more efficient and accurate decision. 相似文献
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This article evaluates different spatial interpolation methods for mapping submerged aquatic vegetation (SAV) in the Caloosahatchee Estuary, Florida. Data used for interpolation were collected by the Submersed Aquatic Vegetation Early Warning System (SAVEWS). The system consists of hydro-acoustic equipment, which operates from a slow-moving boat and records bottom depth, seagrass height, and seagrass density. This information is coupled with geographic location coordinates from a Global Positioning System (GPS) and stored together in digital files, representing SAV status at points along transect lines. Adequate spatial interpolation is needed to present the SAV information, including density, height, and water depth, as spatially continuous data for mapping and for comparison between seasons and years. Interpolation methods examined in this study include ordinary kriging with five different semivariance models combined with a variable number of neighboring points, the inverse distance weighted (IDW) method with different parameters, and the triangulated irregular network (TIN) method with linear and quintic options. Interpolation results were compared with survey data at selected calibration transects to examine the suitability of different interpolation methods. Suitability was quantified by the determination coefficient (R2) and the root-mean-square error (RMSE) between interpolated and observed values. The most suitable interpolation method was identified as the one yielding the highest R2 value and/or the lowest RMSE value. For different geographic conditions, seasons, and SAV parameters, different interpolation methods were recommended. This study identified that kriging was more suitable than the IDW or TIN method for spatial interpolation of all SAV parameters measured. It also suggested that transect data with irregular spatial distribution patterns such as SAV parameters are sensitive to interpolation methods. An inappropriate interpolation method such as TIN can lead to erroneous spatial representation of the SAV status. With a functional geographic system and adequate computing power, the evaluation and selection of interpolation methods can be automated and quantitative, leading to a more efficient and accurate decision. 相似文献
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以废黄河三角洲表层粒度分析数据为基础,探讨了对数比转换和kriging插值相结合方法在沉积物粒级组分空间预测和底质类型制图中的应用。结果表明,基于沉积物粒级组分原始数据的kriging预测方法难以保证各组分预测结果的非负和定和要求,因而预测结果的可信度低;而对数比转换kriging方法不但满足非负和定和要求,而且还有着更优的组分预测结果和较高的底质类型制图精度。新方法对于开展定量化的沉积物粒级组分预测和底质类型制图具有参考价值。 相似文献
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为了研究近岸海带养殖活动对水体光学特性的影响,本文选取山东半岛黑泥湾海域为典型研究区,利用2021年4月和8月在该区的9站同步观测数据,分析其总悬浮颗粒物、藻类颗粒物、非藻类颗粒物以及有色溶解有机物的吸收特性,并计算各组分对总吸收系数的贡献率,同时采用Quasi-analytical algorithm (QAA)算法借助MODIS影像反演了水体总吸收系数,结合实测数据获得了黑泥湾水体吸收特性的季节变化情况。结果表明,有海带养殖季节表层水体藻类颗粒物、非藻类颗粒物、总颗粒物和有色溶解有机物的吸收系数明显大于无海带养殖季节,且春季海带养殖区水体的总吸收系数大于无海带养殖区;海底表层沉积物的再悬浮造成底层吸收系数较大,而在春季成熟期的海带汇聚较大量的有机物质导致中层藻类颗粒物吸收系数相对较高;参考波长向红波移动,QAA_v5算法能够较好地估算该区表层水体吸收系数,且在海带养殖季节水体组分会影响到更长的波段特征。本研究可为深入了解海带养殖对水体各组分浓度和分布、碳循环以及水生生态系统的结构和功能的影响提供参照,并有助于提高近岸水体组分的遥感反演精度。 相似文献
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针对近海表层沉积物粒度组分空间变异的尺度差异性,提出了基于广义回归神经网络残余kriging的沉积物粒度组分空间预测方法,并以海州湾沉积物粒度数据为基础,分析了其在沉积物粒度组分空间预测和底质类型制图中的应用效果。结果表明,广义回归神经网络残余kriging方法能够获得比普通kriging方法更高的沉积物粒度组分空间预测精度,并且其底质类型的总体空间预测精度达到85%以上,相应的Kappa系数也在0.8以上,显示底质制图的预测类型与样本的实测类型具有较高的一致性。新方法对于开展定量化的沉积物粒度组分空间预测和底质类型制图具有参考价值。 相似文献
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Shaoyuan Pan Siquan Tian Xuefang Wang Libin Dai Chunxia Gao Jianfeng Tong 《海洋学报(英文版)》2021,40(8):119-132
Spatial-temporal distribution of marine fishes is strongly influenced by environmental factors. To obtain a more continuous distribution of these variables usually measured by stationary sampling designs, spatial interpolation methods(SIMs) is usually used. However, different SIMs may obtain varied estimation values with significant differences, thus affecting the prediction of fish spatial distribution. In this study, different SIMs were used to obtain continuous environmental variables(water depth, water temperature, salinity, dissolved oxygen(DO), p H,chlorophyll a and chemical oxygen demand(COD)) in the Changjiang River Estuary(CRE), including inverse distance weighted(IDW) interpolation, ordinary Kriging(OK)(semivariogram model: exponential(OKE),Gaussian(OKG) and spherical(OKS)) and radial basis function(RBF)(regularized spline function(RS) and tension spline function(TS)). The accuracy and effect of SIMs were cross-validated, and two-stage generalized additive model(GAM) was used to predict the distribution of Coilia nasus from 2012 to 2014 in CRE. DO and COD were removed before model prediction due to their autocorrelation coefficient based on variance inflation factors analysis. Results showed that the estimated values of environmental variables obtained by the different SIMs differed(i.e., mean values, range etc.). Cross-validation revealed that the most suitable SIMs of water depth and chlorophyll a was IDW, water temperature and salinity was RS, and p H was OKG. Further, different interpolation results affected the predicted spatial distribution of Coilia nasus in the CRE. The mean values of the predicted abundance were similar, but the differences between and among the maximum value were large. Studies showed that different SIMs can affect estimated values of the environmental variables in the CRE(especially salinity).These variations further suggest that the most applicable SIMs to each variable will also differ. Thus, it is necessary to take these potential impacts into consideration when studying the relationship between the spatial distribution of fishes and environmental changes in the CRE. 相似文献
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