Geochemical tracers of northern Portuguese estuarine sediments on the shelf

The northern Portuguese coastal zone is drained by large Iberian rivers, along which there is intensive industrial, agricultural and urban activity. Offshore of the two main river basins of the Douro and Minho, two fine-grained sedimentary formations can be characterised. A geochemical study of this sediment cover has been performed focussing in particular on the fine deposits and the adjacent estuaries. The chemical composition of superficial sediments collected from the northern Portuguese shelf and from the river basins of the Minho and Douro rivers was determined for major, minor and trace elements; the rare earth elements (REE) composition was also determined in selected samples. Statistical analyses of these data for the shelf sediments allow us to identify elements with similar behaviours and the different sediment types along the shelf, and to evaluate of their origins. Downcore profiles of the chemical composition of the fine sediments reveal no evidence for changes induced by recent human activities. To assess the influence of the rivers on the fine sedimentary formations, the elemental distribution patterns of selected sediments have been compared with the estuarine sediments. Lithogenic elements composition normalised to Al and the shale normalised REE distributions showed there are similarities between the Douro River sediments and the sediment composition of the Douro and Galicia mud patches. However, the Galicia mud field showed no relationship in its chemical composition to sediments derived from the Minho River. Nor was any evidence for heavy metal contamination originating from the Douro estuary detected in anthropogenic element/Al ratios in the shelf sediments. This may be because of processes associated with resuspension, complexation and bioturbation that occur during sediment transport and deposition. Nevertheless, the Douro River seems to be the main continental source of fine sediments being deposited on the northern Portuguese shelf.     

一种新的多变量时间序列数据异常检测方法

介绍了一种通过建立多变量时间序列数据相似度矩阵,对相似度矩阵进行转换以最大化数据之间的相关性,并采用随机游走模型计算数据点之间的连接系数来检测数据点上异常的方法。该方法充分利用了数据之间的相关性,有效减少了数据中不同程度噪声对异常检测的影响,检测过程中的漏报率和误报率明显减少,通过仿真实验验证了该方法的有效性。     

Discharge variability in Romania using Palmer indices and a simple atmospheric index of large-scale circulation

ABSTRACT

The aim of this study is to analyse the seasonal characteristics of four Palmer indices calculated on the basis of data from 27 meteorological stations in Romania, and the impact of these indices on river discharges in the period 1931–1998. Our research also tests the influence of large-scale atmospheric circulation on these indices and on discharge. For each season, developments in the empirical orthogonal functions (EOF) and multivariate EOF (MEOF) are achieved. The MEOF representation highlights the overall characteristics of the four Palmer indices. It maximizes specific information for each season compared with individual information of each Palmer index. We then identify geographical areas with homogeneous distribution, taking into account both the discharge distribution and the rotated EOF components of each Palmer index. Finally, we analysed the impact of large-scale atmospheric circulation on hydro-climatic events in Romania by means of the Greenland-Balkan Oscillation Index (GBOI), which is shown to have a greater influence on southeastern Europe than the North Atlantic Oscillation Index (NAOI).     

Multivariate interpolation and information entropy for optimizing raingauge network in the Mekong River Basin

ABSTRACT

The applicability of multivariate interpolation and information entropy to optimize the raingauge network in the Mekong River Basin (MRB) is investigated. Three different spatial interpolation methods are tested: inverse distance squared (IDS), ordinary kriging (OK) and gradient plus inverse distance squared (GIDS). The validated results confirm that the GIDS method outperformed IDS and OK. The application of information entropy together with GIDS on a network of 57 gauges provided the same information content (7.34 nat) as could be obtained using all 6788 gauges in the MRB. Combining this result with meteorological and hydrological indicators revealed that the number of gauges for the optimum raingauge network could be reduced to 40. The results imply good applicability of the proposed method, which may be used to help prioritize efforts and funds to maintain the raingauge network in a given river basin.     

Trivariate generalized extreme value distribution in flood frequency analysis

Abstract

The multivariate extension of the logistic model with generalized extreme value (GEV) marginals is applied to provide a regional at-site flood estimate. The maximum likelihood estimators of the parameters were obtained numerically by using a multivariable constrained optimization algorithm. The asymptotic results were checked by distribution sampling techniques in order to establish whether or not those results can be utilized for small samples. A region in northern Mexico with 21 gauging stations was selected to apply the model. Results were compared with those obtained by the most popular univariate distributions, the bivariate approach of the logistic model and three regional methods: station-year, index flood and L-moments. These show that there is a reduction in the standard error of fit when estimating the parameters of the marginal distribution with the trivariate distribution instead of its univariate and bivariate counterpart, and differences between at-site and regional at-site design events can be significant as return period increases.     

Determination of ultimate capacity of driven piles in cohesionless soil: A Multivariate Adaptive Regression Spline approach

The determination of ultimate capacity (Q) of driven piles in cohesionless soil is an important task in geotechnical engineering. This article adopts Multivariate Adaptive Regression Spline (MARS) for prediction Q of driven piles in cohesionless soil. MARS uses length (L), angle of shear resistance of the soil around the shaft (?_shaft), angle of shear resistance of the soil at the tip of the pile (?_tip), area (A), and effective vertical stress at the tip of the pile as input variables. Q is the output of MARS. The results of MARS are compared with that of the Generalized Regression Neural Network model. An equation has been also presented based on the developed MARS. The results show the strong potential of MARS to be applied to geotechnical engineering as a regression tool. Copyright © 2011 John Wiley & Sons, Ltd.     

A Note on Seasonal Variation in Radiolarian Abundance

A statistical analysis of two consecutive sequences of observations on radiolarian abundances in the western North Pacific, by methods appropriate to data on the simplex (i.e., compositional data), show that although the overall graphical presentations of the frequencies appear similar, there are substantial differences in the earlier part of each of the series. The results of the multivariate analyses are used for identifying those species that contribute most to the analysis. A brief guide to the mathematical properties of compositional data is given.     

A temperate,tidal lake‐wetland complex 2. Water quality and implications for zooplankton community structure

Lakes Waihola and Waipori are shallow, coastal, tidal lakes that experience wind‐induced sediment resuspension, saline intrusions, and high inputs of nutrients. To determine the influence of externally‐driven, physical factors on spatial and temporal patterns of water quality in the two lakes, meteorological, hydrological, and water quality data were collected over 1 year. Multivariate analyses indicated that wind energy was driving the main water quality gradient in the lakes, which was primarily related to wind‐induced resuspension of lake sediments. The major, seasonally regulated, non‐tidal freshwater inflow was important in determining nutrient and salinity gradients in the lakes. The main nutrient inputs to the system were identified as the regulated, non‐tidal inflow (the upper Waipori River) and the tidal inflow (lower Waipori River). The impact of water quality gradients on zooplankton community structure in the lakes was assessed by canonical multivariate methods. Salinity gradients, caused by seasonal saltwater intrusions, were strongly related to zooplankton community structure in the lakes. Nutrient gradients (indicative of trophic state) were also related to zooplankton community structure. Although wind‐induced sediment resuspension had the largest impact on water quality in the lakes, it had little impact on the zooplankton community structure in either lake. The relationships between water quality and zooplankton community structure were confounded in Lake Waipori because of its very short hydraulic residence time (annual mean =1.9 days). Zooplankton community structure was resilient to short‐term changes in suspended particulate matter concentrations but not to seasonal changes in salinity. The results of this study support others which have shown impacts of even relatively small variations in salinity on the structure of zooplankton communities. This highlights the vulnerability of zooplankton communities in coastal lakes and wetlands to increasing salinity resulting from sea level rise and global climate change.     

Discrimination of the phenotypic sardine Sardina pilchardus stocks off the Moroccan Atlantic coast using a morphometric analysis

Morphometric variation can be very useful for discriminating ‘phenotypic stocks’ as groups with similar life-history traits. Such groups are of great importance for accurate population-dynamics modelling for purposes of fishery stock assessment and management, independent of their genetic differences or similarities. This study is a contribution to the stock identification of the sardine Sardina pilchardus off the Moroccan Atlantic coast. The objectives were to (i) assess whether specimens from stocks defined by the FAO correspond to different morphotypes, and (ii) compare the obtained results with those recently published on the genetic variability of the studied populations. Morphometric analyses, using truss variables and landmarks data from sardine sampled from four widely spaced ports of landing along the Moroccan Atlantic coast (from north to south: Larache, Safi, Tantan and Dakhla), were carried out using multivariate and geometric approaches. Principal components analysis of truss variables and cluster analysis of the average shape of the sardine revealed the existence of three distinct morphotypes: ‘Larache,’ ‘Safi–Tantan’ and ‘Dakhla.’ These correspond well with the FAO’s stock subdivision. The morphometric variation might be related to the mesoscale hydrodynamic characteristics of the study area. However, these morphometric results do not fully accord with recently published data on genetic variability of the species. Those data indicated the genetic singularity of the Safi population, which could have led to the historical collapse of that sardine stock in the 1970s. Additional work is needed to validate the obtained results by taking into account seasonal variations and transitional areas between stocks.     

A multivariate Bernstein copula model for permeability stochastic simulation

This paper introduces a general nonparametric method for joint stochastic simulation of petrophysical properties using the Bernstein copula. This method consists basically in generating stochastic simulations of a given petrophysical property (primary variable) modeling the underlying empirical dependence with other petrophysical properties (secondary variables) while reproducing the spatial dependence of the first one.This multivariate approach provides a very flexible tool to model the complex dependence relationships of petrophysical properties. It has several advantages over other traditional methods, since it is not restricted to the case of linear dependence among variables, it does not require the assumption of normality and/or existence of moments.In this paper this method is applied to simulate rock permeability using Vugular Porosity and Shear Wave Velocity (S-Waves) as covariates in a carbonate double-porosity formation at well log scale. Simulated permeability values show a high degree of accuracy compared to the actual values.