共查询到20条相似文献，搜索用时 31 毫秒
1.
A procedure is proposed for geochemical mapping of the water area bottom based on the subdivision of raw data into two components, i.e., systematic (regional) and random (local). The former is used to determine regional characteristic of the spatial radionuclide distributions in bottom sediments to be utilized to identify large radiogeochemical regions, while the latter is used to identify local anomalies and evaluate their characteristics. The systematic component of the radiogeochemical field is determined by trend analysis. Next, cluster analysis, i.e., hierarchic clusterization of the results of trend analysis followed by associative classification, is used for radiochemical zoning of the water area. After that, maps are constructed, showing contour lines of the local component of radiogeochemical fields, represented by deviations of the value in the given point from the trend. The result is a single map showing the radiogeochemical regions with contour lines of normalized anomalous activities of the radionuclides under study. The practical application of the method is illustrated by radiogeochemical mapping of the bed in the Eastern Gulf of Finland. 相似文献
2.
This article presents the development of a relatively low cost and rapidly applicable methodology to simulate the spatio‐temporal occurrence of groundwater flooding in chalk catchments. In winter 2000/2001 extreme rainfall resulted in anomalously high groundwater levels and groundwater flooding in many chalk catchments of northern Europe and the southern United Kingdom. Groundwater flooding was extensive and prolonged, occurring in areas where it had not been recently observed and, in places, lasting for 6 months. In many of these catchments, the prediction of groundwater flooding is hindered by the lack of an appropriate tool, such as a distributed groundwater model, or the inability of models to simulate extremes adequately. A set of groundwater hydrographs is simulated using a simple lumped parameter groundwater model. The number of models required is minimized through the classification and grouping of groundwater level time‐series using principal component analysis and cluster analysis. One representative hydrograph is modelled then transposed to other observed hydrographs in the same group by the process of quantile mapping. Time‐variant groundwater level surfaces, generated using the discrete set of modelled hydrographs and river elevation data, are overlain on a digital terrain model to predict the spatial extent of groundwater flooding. The methodology is applied to the Pang and Lambourn catchments in southern England for which monthly groundwater level time‐series exist for 52 observation boreholes covering the period 1975–2004. The results are validated against observed groundwater flood extent data obtained from aerial surveys and field mapping. The method is shown to simulate the spatial and temporal occurrence of flooding during the 2000/2001 flood event accurately. British Geological Survey © NERC 2011. Hydrological Processes © 2011 John Wiley & Sons, Ltd. 相似文献
3.
Little research attention has been given to validating clusters obtained from the groundwater geochemistry of the waterworks' capture zone with a prevailing lake-groundwater exchange. To address this knowledge gap, we proposed a new scheme whereby Gaussian finite mixture modeling (GFMM) and Spike-and-Slab Bayesian (SSB) algorithms were utilized to cluster the groundwater geochemistry while quantifying the probability of the resulting cluster membership against each other. We applied GFMM and SSB to 13 geochemical parameters collected during different sampling periods at 13 observation points across the Barnim Highlands plateau located in the northeast of Berlin, Germany; this included 10 observation wells, two lakes, and a gallery of drinking production wells. The cluster analysis of GFMM yielded nine clusters, either with a probability ≥0.8, while the SSB produced three hierarchical clusters with a probability of cluster membership varying from <0.2 to >0.8. The findings demonstrated that the clustering results of GFMM were in good agreement with the classification as per the principal component analysis and Piper diagram. By superimposing the parameter clustering onto the observation clustering, we could identify discrepancies that exist among the parameters of a certain cluster. This enables the identification of different factors that may control the geochemistry of a certain cluster, although parameters of that cluster share a strong similarity. The GFMM results have shown that from 2002, there has been active groundwater inflow from the lakes towards the capture zone. This means that it is necessary to adopt appropriate measures to reverse the inflow towards the lakes. 相似文献
4.
In this study, a methodology for clustering 18 lakes in Alberta, Canada using the data of 19 water quality parameters for a period of 11 years (1988–2002) is presented. The methods consist of (i) principal component analysis (PCA) to determine the dominant water quality parameters, (ii) cluster analysis techniques to develop the characteristics of the clusters, and (iii) pattern‐match lakes to determine the appropriate cluster for each of the lakes. The PCA revealed that three principal components (PCs) were able to explain ～88% of the variability and the dominant water quality parameters were total dissolved solids, total phosphorus, and chlorophyll‐a. We obtained five clusters for the period 1994–1997 by using the dominant parameters with water quality deteriorating as the cluster number increased from 1 to 5. Upon matching cluster patterns with the entire dataset, it was observed that some of the lakes belonged to the same cluster all the time (e.g., cluster 1 for lakes Elkwater, Gregg, and Jarvis; cluster 3 for Sturgeon; cluster 4 for Moonshine; and cluster 5 for Saskatoon), while others changed with time. This methodology could be applied in other regions of the world to identify the most suitable source waters and prioritize their management. It could be helpful to analyze the natural controlling processes, pollution types, impact of seasonal changes and overall quality of source waters. This methodology could be used for monitoring water bodies in a cost effective and efficient way by sampling only less number of dominant parameters instead of using a large set of parameters. 相似文献
5.
基于主成分的时间域航空电磁数据神经网络反演仿真研究(英文) 总被引：5，自引：0，他引：5
传统上,时间域航空电磁数据通过拟合迭代反演计算得到大地模型,然而,由于航空电磁数据道间的较强相关性,导致病态反演,并引起超定问题;同时电磁数据的相关性使其与模型参数的映射关系复杂,增加了反演的复杂度。采用主成分分析法将航空电磁数据变换为正交的较少数量的主成分,不仅降低了数据道间的相关性,减小了数据量,同时压制了数据的不相关噪声。本文利用人工神经网络(ANN)逼近主成分与大地模型参数间的映射关系,避免了传统反演算法中雅克比矩阵的复杂计算。层状模型的主成分神经网络与数据神经网络的反演结果对比显示,主成分神经网络反演方法网络结构简单,训练步数少,反演结果好,特别是对于含噪数据。准二维模型的主成分ANN、数据ANN以及Zhody方法的反演结果显示了主成分神经网络具有更接近真实模型的反演效果,进一步证明了主成分神经网络反演方法适合海量航空电磁探测数据反演。 相似文献
6.
A. G. Brown 《地球表面变化过程与地形》1985,10(3):281-291
The vertical and horizontal variation of sedimentary fades is the raw data for the interpretation of flood plain history from which palaeohydrological inferences are frequently drawn. Mixed and fine floodplain sediments present problems of interpretation because of a large grain size range and frequent polymodality caused by the mixing of process-associated grain size components. This paper discusses the use of traditional grain size statistics and the use of the mode and multivariate statistics. The mode, although much neglected, is indicative of up-profile grain size changes and has practical advantages over the mean for mixed and fine floodplain sediments. Constrained cluster analysis and principal components analysis are used directly on Coulter counter results. These techniques can rapidly divide a floodplain profile into grain size units and indicate the principal vectors of grain size variation which will be related to the changing processes of deposition. Principal components analysis reveals the importance of the medium to fine silt category in accounting for grain size variations, suggesting that a critical factor in determining the type of alluvial unit deposited is the degree to which it has received fine suspended material. Grain size data from the Lower Severn are used to construct a CM diagram which is compared with a texture triangle. From both the CM and multivariate analysis a generalized backswamp profile is constructed which shows the existence of a coarser top unit caused by the addition of a fine to medium sand component to the underlying sediment during the Late Holocene. 相似文献
7.
Inverse modeling is widely used to assist with forecasting problems in the subsurface. However, full inverse modeling can be time-consuming requiring iteration over a high dimensional parameter space with computationally expensive forward models and complex spatial priors. In this paper, we investigate a prediction-focused approach (PFA) that aims at building a statistical relationship between data variables and forecast variables, avoiding the inversion of model parameters altogether. The statistical relationship is built by first applying the forward model related to the data variables and the forward model related to the prediction variables on a limited set of spatial prior models realizations, typically generated through geostatistical methods. The relationship observed between data and prediction is highly non-linear for many forecasting problems in the subsurface. In this paper we propose a Canonical Functional Component Analysis (CFCA) to map the data and forecast variables into a low-dimensional space where, if successful, the relationship is linear. CFCA consists of (1) functional principal component analysis (FPCA) for dimension reduction of time-series data and (2) canonical correlation analysis (CCA); the latter aiming to establish a linear relationship between data and forecast components. If such mapping is successful, then we illustrate with several cases that (1) simple regression techniques with a multi-Gaussian framework can be used to directly quantify uncertainty on the forecast without any model inversion and that (2) such uncertainty is a good approximation of uncertainty obtained from full posterior sampling with rejection sampling. 相似文献
8.
Jelena S. Kiurski Ivana B. Oros Nebojsa M. Ralevic Jasmina Stefanov 《Stochastic Environmental Research and Risk Assessment (SERRA)》2015,29(6):1709-1720
This study presents the application of different chemometric approaches on the dataset obtained during the monitoring of offset printing wastewater quality in Pozarevac, Serbia. Collecting of wastewaters was performed during a working week, five working days, in five offset printing facilities. Twenty five physico-chemical parameters were analyzed in wastewaters using the standard analytical and instrumental methods. The obtained dataset were subjected to cluster analysis and principal component analysis. Cluster analysis showed four groups of similarity between the printing facilities reflecting the different physico-chemical characteristics and pollution levels of studied wastewaters. Principal component analysis identified two principal components responsible for the data structure explaining 86 % of total variance of offset printing wastewaters. The obtained principal components indicate the parameters that are the most responsible for variation of offset printing wastewaters. This study clearly demonstrates the usefulness of chemometric methods in analysis of printing wastewater quality, identification of the main sources and understanding of spatial variations in wastewater quality. Also, it could be useful for the selection of an appropriate wastewater treatment plant. 相似文献
9.
The concentration levels of 12 priority volatile organic compounds (VOCs) were determined in two species of vertebrates and four species of invertebrates from sampling stations in the southern North Sea, using a modified Tekmar LSC 2000 purge and trap system coupled to gas chromatograph–mass spectrometer (GC–MS). In general, concentration levels of VOCs found in this study were of the same order of magnitude as those previously reported in the literature. The concentrations of the chlorinated hydrocarbons (CHCs), with the exception of chloroform, tended to be lower than those of the monocyclic aromatic hydrocarbons (MAHs). The experimental data were statistically evaluated using both cluster analysis and principal component analysis (PCA). From the results of cluster analysis and PCA, no specific groups could be distinguished on the basis of geographical, temporal or biological parameters. However, based on the cluster analysis and the PCA, the VOCs could be divided into three groups, C2-substituted benzenes, CHCs and benzene plus toluene. This division could be related to different types of sources. Finally, it was shown that organisms can be used to monitor the presence of VOCs in the marine environment and the observed concentrations levels were compared with proposed safety levels. 相似文献
10.
A multivariate spatial sampling design that uses spatial vine copulas is presented that aims to simultaneously reduce the prediction uncertainty of multiple variables by selecting additional sampling locations based on the multivariate relationship between variables, the spatial configuration of existing locations and the values of the observations at those locations. Novel aspects of the methodology include the development of optimal designs that use spatial vine copulas to estimate prediction uncertainty and, additionally, use transformation methods for dimension reduction to model multivariate spatial dependence. Spatial vine copulas capture non-linear spatial dependence within variables, whilst a chained transformation that uses non-linear principal component analysis captures the non-linear multivariate dependence between variables. The proposed design methodology is applied to two environmental case studies. Performance of the proposed methodology is evaluated through partial redesigns of the original spatial designs. The first application is a soil contamination example that demonstrates the ability of the proposed methodology to address spatial non-linearity in the data. The second application is a forest biomass study that highlights the strength of the methodology in incorporating non-linear multivariate dependence into the design. 相似文献
11.
基于光子计数探测器的能谱CT,可以同时采集多个能谱通道的投影数据,并获得相应能量范围内物质的吸收特征,可以有效应用于物质识别与材料分解。主成分分析是一种很好的多元数据分析技术,可以用于处理多能谱CT数据。本文分别在投影域和图像域对能谱CT数据进行主成分分析,并对分析结果做出系统比较。为了减少噪声的影响,提高能谱CT图像的彩色表征性能,提出双域滤波与像素值平方相结合的方法,用于含噪声的主成分图像去噪,然后将所选取的主成分图像映射到RGB颜色通道。实验结果表明,无论是在投影域还是图像域进行主成分分析,都可以获取清晰的CT图像,识别出物质的不同成分。相较于在图像域的主成分分析方法,在投影域进行主成分分析能够保留物质的更多细节,获取更清晰的彩色CT图像。 相似文献
12.
A methodology for characterizing the hydrogeology of watersheds using hydrochemical data that combine statistical, geochemical, and spatial techniques is presented. Surface water and ground water base flow and spring runoff samples (180 total) from a single watershed are first classified using hierarchical cluster analysis. The statistical clusters are analyzed for spatial coherence confirming that the clusters have a geological basis corresponding to topographic flowpaths and showing that the fractured rock aquifer behaves as an equivalent porous medium on the watershed scale. Then principal component analysis (PCA) is used to determine the sources of variation between parameters. PCA analysis shows that the variations within the dataset are related to variations in calcium, magnesium, SO4, and HCO3, which are derived from natural weathering reactions, and pH, NO3, and chlorine, which indicate anthropogenic impact. PHREEQC modeling is used to quantitatively describe the natural hydrochemical evolution for the watershed and aid in discrimination of samples that have an anthropogenic component. Finally, the seasonal changes in the water chemistry of individual sites were analyzed to better characterize the spatial variability of vertical hydraulic conductivity. The integrated result provides a method to characterize the hydrogeology of the watershed that fully utilizes traditional data. 相似文献
13.
The primary purpose of this study is to develop the regional flow duration curves for southern Taiwan. To define homogeneous regions for developing regional flow duration curves, multivariate statistical analysis (principal component and cluster analysis) was applied to daily flow data from 34 stream-gauged stations in southern Taiwan. Two kinds of clustering variables, the dimensionless flow duration curve and specific flow duration curve, were compared in this study. It was found that three homogeneous regions delineated by specific flow duration curves as clustering variables have more reasonable results. The three homogeneous regions not only have well-defined geographical boundaries, but also correspond to the rainfall and geology characteristics of the regions. It seems that the technique of cluster analysis can reasonably define the homogeneous regions. In each homogeneous region, the synthetic regional flow duration curves were developed by a family of parametric duration curves. This approach has the advantage of being simple and needing only the basin area as an index. The performance of the regional flow duration curve was verified by the comparison of areas under the actual and synthetic flow duration curves; the latter were generated from the regional flow duration curve. Almost all the 34 stream-gauged stations had less than 25% absolute error. 相似文献
14.
时间域航空电磁数据往往在测量过程中受到天然和人文噪声的干扰.如果不能很好滤除这些电磁噪声,那么将会降低资料质量、影响反演的精度,甚至获得错误的解释结果.本文提出了一种基于核主成分分析的去噪方法,通过核主成分分析提取叠加后衰减曲线的主成分,然后使用能量占比方法分离反映地下介质的有效信号和噪声,最后使用反映地下介质的特定成分进行重构.本文所推荐的去噪方法不仅能剔除天然噪声,例如天电产生的尖脉冲或者振荡,而且能有效地抑制人文噪声.分别使用基于核主成分分析的去噪方法,以及AeroTEM软件的处理方法对同样的吊舱式时间域直升机航空电磁勘查系统实测数据进行处理,并比较其结果.处理结果表明：所推荐的去噪方法要优于AeroTEM软件. 相似文献
15.
The spatial and temporal patterns of water quality in Kuwait Bay have been investigated using data from six stations between 2009 and 2011. The results showed that most of water quality parameters such as phosphorus (PO4), nitrate (NO3), dissolved oxygen (DO), and Total Suspended Solids (TSS) fluctuated over time and space. Based on Water Quality Index (WQI) data, six stations were significantly clustered into two main classes using cluster analysis, one group located in western side of the Bay, and other in eastern side. Three principal components are responsible for water quality variations in the Bay. The first component included DO and pH. The second included PO4, TSS and NO3, and the last component contained seawater temperature and turbidity. The spatial and temporal patterns of water quality in Kuwait Bay are mainly controlled by seasonal variations and discharges from point sources of pollution along Kuwait Bay’s coast as well as from Shatt Al-Arab River. 相似文献
16.
本文提出了将主成分分析方法和地磁日变分析方法相结合以从较强干扰背景中提取相对较弱地震地磁信息的一种新思路.具体以1998年日本岩手县北部6.1级地震为例,选用三个地磁观测台资料进行研究.利用调和分析方法得到了各台基于多次谐波拟合的地磁日变曲线,在此基础上对各台的地磁日变形态进行了研究,发现距震中最近地磁台的日变形态在地震前大约两周出现了明显的异常,而其他两个距离震中相对较远的观测台日变形态基本正常.最后,将主成分分析方法应用于上述拟合地磁日变结果,得到了各主成分及其所占能量比的时间变化,结果表明在地震前两周左右第二主成分所占能量比显著增加,而且距离震中最近的台站的上述变化明显高于另两个较远的台站.上述结果表明地震前两周左右检测到的地磁日变异常可能与震中附近地下电阻率的变化或孕震过程中产生的电磁信号存在一定关系,相关研究结果有助于加深对地震电磁现象的认识和理解. 相似文献
17.
Annadasankar Roy Hemant Mohokar Diksha Pant Uday Kumar Sinha G. N. Mendhekar 《水文科学杂志》2020,65(6):951-968
ABSTRACTMultivariate statistical analysis and inverse geochemical modelling techniques were employed to deduce the mechanism of groundwater evolution in the hard-rock terrain of Telangana, South India. Q-mode hierarchical cluster analysis (HCA) and principal component analysis (PCA) were used to extract the hydrogeochemical characteristics and classify the groundwater samples into three principal groups. Use of thermodynamic stability diagrams and inverse geochemical modelling in PHREEQC identified the chemical reactions controlling hydrogeochemistry of each of the groups obtained from statistical analysis. The model output showed that a few phases are governing the water chemistry in this area and the geochemical reactions responsible for evolution of groundwater chemistry along the flow path are (i) dissolution of evaporite minerals (dolomite, halite); (ii) dissolution of primary silicate minerals (albite, anorthite, K-feldspar, biotite); (iii) precipitation of secondary silicate minerals (kaolinite, quartz, gibbsite, Ca-montmorillonite) along with anhydrite and calcite; and (iv) reverse ion exchange processes. 相似文献
18.
The aim of this study was to display distribution and relationships of heavy elements in the unconfined, shallow alluvial aquifers of the lower Jia Bharali catchment and adjoining areas in central part of North Brahmaputra Plain (NBP), India using hydrochemical as well as multivariate statistical techniques such as principal component analysis (PCA) and cluster analysis. The original matrix was made up of 10 trace elements (As, Cd, Cu, Co, Cr, Fe, Mn, Pb, Ni and Zn) estimated from 50 shallow alluvial dug wells in both the wet and the dry season for a duration of 3 hydrological years (2008–2011). Except As, Cu and Zn all the other toxic metals in the shallow aquifers were found exceeding the WHO maximum permissible limits for drinking water. PCA extracted five varimax factors as geogenic, agricultural and anthropogenic explaining about 71.2% of the total variance in the wet season and 69.3% total variance in the dry season. Hierarchical cluster analysis classified the dug wells into two groups in the wet season and three groups in the dry season with respect to the heavy elements. The results emphasized the need for routine monitoring and management in order to avoid contamination of groundwater sources in the NBP with respect to the dissolved trace elements. 相似文献
19.
Khouloud Gader Ahlem Gara Marnik Vanclooster Slaheddine Khlifi Mohamed Slimani 《水文科学杂志》2020,65(8):1300-1315
ABSTRACT Predicting the impacts of climate change on water resources remains a challenging task and requires a good understanding of the dynamics of the forcing terms in the past. In this study, the variability of precipitation and drought patterns is studied over the Mediterranean catchment of the Medjerda in Tunisia based on an observed rainfall dataset collected at 41 raingauges during the period 1973–2012. The standardized precipitation index and the aridity index were used to characterize drought variability. Multivariate and geostatistical techniques were further employed to identify the spatial variability of annual rainfall. The results show that the Medjerda is marked by a significant spatio-temporal variability of drought, with varying extreme wet and dry events. Four regions with distinct rainfall regimes are identified by utilizing the K-means cluster analysis. A principal component analysis identifies the variables that are responsible for the relationships between precipitation and drought variability. 相似文献
20.
The method of conformal mapping is applied to the analysis of transient flow toward parallel periodic drains in a semi-infinite aquifer taking into consideration the non-linear boundary conditions on the free surface. The mapping function is expressed as a power series in time and the seepage domain is mapped onto a domain of an auxiliary complex variable. Mapping is performed in such a manner that the free surface will always remain the real axis. Calculations are carried out for different ratios of drain depth to drain spacing using various drain diameter to depth ratios. 相似文献