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1.
In this work, investigations dealing with the determination of hydrocarbons in contaminated soil water are presented. The hydrocarbons under investigation range from low to high volatility compounds. A GC‐FID method was developed that due to its efficiency, routine suitability, relative rapidity, and low cost is suitable for the analysis of complex chemical mixtures of highly volatile hydrocarbons (with boiling points between 69 and 190°C). The standard used was a gasoline mixture with boiling points ranging from 100 to 190°C. For this standard, no supplementary preparation is needed and it is suitable for the whole range of hydrocarbons under investigation. The determination of the hydrocarbon content of the samples was performed applying univariate and multivariate statistical analysis to the experimental data. In the characterization of a contamination with highly volatile hydrocarbons of soil water originating from different depth layers from the chemistry location Leuna (Sachsen‐Anhalt, Germany), the advantages of a multivariate method are demonstrated in exemplary manner.  相似文献   

2.
This paper presents the results of the statistical analysis of a set of physico-chemical and biological water quality parameters, monthly collected from 2000 to 2007 in the Genoa Harbour area (Ligurian Sea). We applied multivariate methods, such as principal component analysis (PCA) and dynamic factor analysis (DFA) for investigating the spatial and temporal variability and for providing important background information on pollution problems in the region. PCA evidenced the role of the sewage and river discharges and of the exchanges with the open sea in determining the harbour water quality. DFA was used to estimate underlying common trends in the time series. The DFA results partly show a general improvement of water quality over the 8-years period. However, in other areas, we found inter-annual variations but no significant multi-annual trend. Furthermore, we included meteorological variables in our statistical analyses because of their potential influence on the water quality parameters. These natural forcings explain part of the variability in water quality parameters that are superimposed on the dominating anthropogenic pollution factors.  相似文献   

3.
In the study, multivariate statistical methods including principal component analysis (PCA)/factor analysis (FA) and cluster analysis (CA) were applied to analyze surface water quality data sets obtained from the Huaihe River segment of Bengbu (HRSB) and generated during 2 years (2011–2012) monitoring of 19 parameters at 7 sampling sites. The results of PCA for 7 sampling sites revealed that the first four components of PCA showed 94.89% of the total variance in the data sets of HRSB. The Principal components (Factors) obtained from FA indicated that the parameters for water quality variations were mainly related to heavy metals (Pb, Mn, Zn and Fe) and organic related parameters (COD, PI and DO). The results revealed that the major causes of water quality deterioration were related to inflow of industrial, domestic and agricultural effluents into the Huaihe River. Three significant sampling locations—(sites 2, 3 and 4), (sites 1 and 5) and (sites 6 and 7)—were detected on the basis of similarity of their water quality. Thus, these methods were believed to be valuable to help water resources managers understand complex nature of water quality issues and determine the priorities to improve water quality.  相似文献   

4.
Methods for the detection and estimation of trends which are suitable for the type of data sets available from water quality and atmospheric deposition monitoring programmes are considered. Parametric and non-parametric methods which are based on the assumption of monotonic trend and which account for seasonality through blocking on season are described. The topics included are heterogeneity of trend, missing data, covariates, censored data, serial dependence and multivariate extensions. The basis for the non-parametric methods being the method of choice for current large data sets of short to moderate length is reviewed. A more general definition of trend as the component of gradual change over time is consistent with another group of methods and some examples are given. Spatial temporal data sets and longer temporal records are also briefly considered. A broad overview of the topic of trend analysis is given, with technicalities left to the references cited. The necessity of defining what is meant by trend in the context of the design and objectives of the programme is emphasized, as is the need to model the variability in the data more generally.  相似文献   

5.
Kil Seong Lee  Sang Ug Kim 《水文研究》2008,22(12):1949-1964
This study employs the Bayesian Markov Chain Monte Carlo (MCMC) method with the Metropolis–Hastings algorithm and maximum likelihood estimation (MLE) using a quadratic approximation of the likelihood function for the evaluation of uncertainties in low flow frequency analysis using a two‐parameter Weibull distribution. The two types of prior distributions, a non‐data‐based distribution and a data‐based distribution using regional information collected from neighbouring stations, are used to establish a posterior distribution. Eight case studies using the synthetic data with a sample size of 100, generated from two‐parameter Weibull distribution, are performed to compare with results of analysis using MLE and Bayesian MCMC. Also, Bayesian MCMC and MLE are applied to 36 years of gauged data to validate the efficiency of the developed scheme. These examples illustrate the advantages of Bayesian MCMC and the limitations of MLE based on a quadratic approximation. From the point of view of uncertainty analysis, Bayesian MCMC is more effective than MLE using a quadratic approximation when the sample size is small. In particular, Bayesian MCMC method is more attractive than MLE based on a quadratic approximation because the sample size of low flow at the site of interest is mostly not enough to perform the low flow frequency analysis. Copyright © 2007 John Wiley & Sons, Ltd.  相似文献   

6.
Data on 13 median leachate qualities at 56 landfills show a multivariate character, A simulation technique is used to include this multivariate character of leachate quality in assessing false negative error rates for statistical tests of ground-water quality. Although the technique makes gross simplifying assumptions regarding the conservative mixing of leachate and ground water, the technique is more appropriate than traditional statistical methods for simulating false negative error rates that neglect correlations among water quality parameters. The technique is applied to the simple case of a control chart, intrawell statistical test of ground-water contamination. Simulation results show that both the false positive and false negative errors of statistical tests can be reduced when tests include more parameters and a higher confidence level; thus, the technique can provide a “win-win” situation for regulators and the regulated.  相似文献   

7.
In [50] and [51] a theory has been developed relating formation factor, permeability and porosity of porous sedimentary rock by means of statistical parameters of the pore system, and further, tying those statistical parameters to other macroscopically measurable quantities like capillarity, capillary retention, flow dispersion etc. This paper deals with experimental methods and apparatus for checking the theoretically derived relations using columns of packed loose or artificially consolidated sands or other granular matter. Some initial experiments, mainly intended for checking out equipment and methods are reported. The discussion of the results so far shows good agreement with the theory in most cases, except for the irreducible water saturation. However, for a definite statement on the general validity of the theory more data must be accumulated.  相似文献   

8.
This paper is intended to compare the hazard rate from the Bayesian approach with the hazard rate from the maximum likelihood estimate (MLE) method. The MLE of a parameter is appropriate as long as there are sufficient data. For various reasons, however, sufficient data may not be available, which may make the result of the MLE method unreliable. In order to resolve the problem, it is necessary to rely on judgment about unknown parameters. This is done by adopting the Bayesian approach. The hazard rate of a mixture model can be inferred from a method called Bayesian estimation. For eliciting a prior distribution which can be used in deriving a Bayesian estimate, a computerized-simulation method is introduced. Finally, a numerical example is given to illustrate the potential benefits of the Bayesian approach.  相似文献   

9.
In the water resources field, there are emerging problems such as temporal changes of data and new additions of water sources. Non-mixture models are not efficient in analyzing these data because these models are developed under the assumption that data do not change and come from one source. Mixture models could successfully analyze these data because mixture models contain more than one modal. The expectation maximization (EM) algorithm has been widely used to estimate parameters of the mixture normal distribution for describing the statistical characteristics of hydro meteorological data. Unfortunately, the EM algorithm has some disadvantages, such as divergence, derivation of information matrices, local maximization, and poor accuracy. To overcome these disadvantages, this study proposes a new parameter estimation approach for the mixture normal distribution. The developed model estimates parameters of the mixture normal distribution by maximizing the log likelihood function using a meta-heuristic algorithm—genetic algorithm (GA). To verify the performance of the developed model, simulation experiments and practical applications are implemented. From the results of experiments and practical applications, the developed model presents some advantages, such as (1) the proposed model more accurately estimates the parameters even with small sample sizes compared to the EM algorithm; (2) not diverging in all application; and (3) showing smaller root mean squared error and larger log likelihood than those of the EM algorithm. We conclude that the proposed model is a good alternative in estimating the parameters of the mixture normal distribution for kutotic and bimodal hydrometeorological data.  相似文献   

10.
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11.
This paper presents novel methods for robust statistical testing of particle shape data. Shape (the relative lengths of three orthogonal axes) is a key property of sedimentary particles, providing information on provenance, transport history and depositional environment. However, the usefulness of shape data, including the ability to make robust comparisons between samples, has been constrained by the absence of a satisfactory definition of the mean shape for a sample of particles. Such a definition is proposed and used to develop confidence regions for the population mean shape using both parametric (theoretical) and computational (bootstrap) methods. These techniques are based on a transform that permits multivariate statistical methods for the analysis of compositional data to be extended to shape. These techniques are validated with reference to a dataset of 169 clast samples and found to perform well. A statistical test on the mean – using the multivariate extension of Student's t-test, Hotelling's T2 – is presented. The benefits of the methods presented are demonstrated with reference to a case study. © 2019 John Wiley & Sons, Ltd.  相似文献   

12.
湖泊富营养化响应与流域优化调控决策的模型研究进展   总被引：2，自引：0，他引：2  
湖泊富营养化是全球水环境领域面临的长期挑战,富营养化响应与流域优化决策模型是制定经济和高效调控方案的关键.然而已有的模型研究综述主要集中于模型开发、案例应用、敏感性分析、不确定性分析等单一方面,而缺少针对非线性响应、生态系统长期演变等最新湖泊治理挑战的研究总结.本文对数据驱动的统计模型、因果驱动的机理模型和决策导向的优化模型进行了综述.其中,统计模型包含经典统计、贝叶斯统计和机器学习模型,常用于建立响应关系、时间序列特征分析以及预报预警;机理模型包含流域的水文与污染物输移模拟以及湖泊的水文、水动力、水质、水生态等过程的模拟,用于不同时空尺度的变化过程模拟,其中复杂机理模型的敏感性分析、参数校验、模型不确定性等需要较高的计算成本;优化模型结合机理模型形成“模拟优化”体系,在不确定性条件下衍生出随机、区间优化等多种方法,通过并行计算、简化与替代模型可一定程度上解决计算时间成本的瓶颈.本文识别了湖泊治理面临的挑战,包括:①如何定量表征外源输入的非线性叠加和湖泊氮、磷、藻变化的非均匀性?②如何提高优化调控决策和水质目标的关联与精准性?③如何揭示湖泊生态系统的长期变化轨迹与驱动因素?最后,本文针对这些挑战提出研究展望,主要包括:①基于多源数据融合与机器学习算法以提升湖泊的短期水质预测精度;②以生物量为基础的机理模型与行为驱动的个体模型的升尺度或降尺度耦合以表达多种尺度的物质交互过程;③机器学习算法与机理模型的直接耦合或数据同化以降低模拟误差;④时空尺度各异的多介质模拟模型融合以实现精准和动态的优化调控.  相似文献   

13.
ABSTRACT

A new deep extreme learning machine (ELM) model is developed to predict water temperature and conductivity at a virtual monitoring station. Based on previous research, a modified ELM auto-encoder is developed to extract more robust invariance among the water quality data. A weighted ELM that takes seasonal variation as the basis of weighting is used to predict the actual value of water quality parameters at sites which only have historical data and no longer generate new data. The performance of the proposed model is validated against the monthly data from eight monitoring stations on the Zengwen River, Taiwan (2002–2017). Based on root mean square error, mean absolute error, mean absolute percentage error and correlation coefficient, the experimental results show that the new model is better than the other classical spatial interpolation methods.  相似文献   

14.
The geochemical analysis of fumarolic gases collected at quiescent and active volcanic systems over time is one of the main tools to understand changes in the state of activity for surveillance and risk assessment. The continuous output of chemical species through fumarolic activity, which characterizes the inter-eruptive intervals, has also a major and general influence on the environment. The mobilization of chemical species due to weathering of volcanic rocks, or the input of gaseous components from fumarolic activity, results in some kind of modification of the environment affecting, in particular, water, soils, and the consequent growth of the plants present in these areas. In this paper, an investigation on the chemical composition of fumarolic gases collected at Vulcano island (Sicily, southern Italy) is performed, with the aim to discover how data changes during the monitored period of time, and to design a strategy for the environmental surveillance of volcanic systems taking into account the nature of the analyzed data. In order to summarize the contribution of all the components that can affect the chemical composition of volcanic gases, a multivariate statistical approach appears to be suitable. Since many of those methods assume independent observations, the possible presence of time-dependent structures should be carefully verified. In this framework, given the compositional nature of geochemical data, we have applied recent theoretical and practical developments in the field of compositional data analysis to work in the correct sample space and to isolate groups of parts responsible for significant changes in the gas chemistry. The proposed approach can be generalized to the investigation of complex environmental systems.  相似文献   

15.
Sustaining the human ecological benefits of surface water requires carefully planned strategies for reducing the cumulative risks posed by diverse human activities. Municipal governments in Izmir City play a key role in developing solutions to surface water management and protection. Therefore, several methodologies are carried out to develop new solutions for protecting available water resources. In the present study, the major chemical loads of surface water at the Tahtal? dam reservoir were evaluated statistically by using monthly averaged values of the measured parameters. Here, the SPSS and NCSS statistical programs were applied during the statistical analyses. Analyses were carried out in two stages. In the first part of the statistical analyses, the mean, median, minimum, maximum, 25th and 75th quartiles were calculated. In second part, the data were investigated by using statistical median test, normality test, parametric and non-parametric correlation and regression analyses. These methods were performed on water quality data taken from four sample sites representing the recharge and discharge areas at the Tahtal? dam. The Median test is applied to check if medians of water quality data from four sample sites (Derebo?az?, Bulgurca, Menderes and Gölcükler) are equal or not. Commonly a non-parametric test (distribution-free test) is used to compare two independent groups of sampled data. Since there are more than two groups in independent group comparison, Kruskal–Wallis test is applied instead of Mann–Whitney U test. Finally, the main objective of using statistical analyses in third research is to estimate the types of pollution sources, the level of pollution and its environmental impacts on the Tahtal? dam reservoir by means of statistical methodology.  相似文献   

16.
Seasonal forecasting can be highly valuable for water resources management. Hydrological models (either lumped conceptual rainfall-runoff models or physically based distributed models) can be used to simulate streamflows and update catchment conditions (e.g. soil moisture status) using rainfall records and other catchment data. However, in order to use any hydrological model for skillful seasonal forecasting, rainfall forecast at relevant spatial and/or temporal scales is required. Together with downscaling, general circulation models are probably the only tools for making such seasonal predictions. The Predictive Ocean Atmosphere Model for Australia (POAMA) is a state-of-the-art seasonal climate forecast system developed by the Australian Bureau of Meteorology. Based on the preliminary assessment on the performance of existing statistical downscaling methods used in Australia, this paper is devoted to develop an analogue downscaling method by modifying the Euclidian distance in the selection of similar weather pattern. Such a modification consists of multivariate Box–Cox transformation and then standardization to make the resulted POAMA and observed climate pattern more similar. For the predictors used in Timbal and Fernadez (CAWCR Technical Report No. 004, 2008), we also considered whether the POAMA precipitation provides useful information in the analogue method. Using the high quality station data in the Murray Darling Basin of Australia, we found that the modified analogue method has potential to improve the seasonal precipitation forecast using POAMA outputs. Finally, we found that in the analogue method, the precipitation from POAMA should not be used in the calculation of similarity. The findings would then help to improve the seasonal forecast of streamflows in Australia.  相似文献   

17.
太湖流域上游平原河网区水质空间差异与季节变化特征   总被引：4，自引：2，他引：2  
张涛  陈求稳  易齐涛  王敏  黄蔚  冯然然 《湖泊科学》2017,29(6):1300-1311
在太湖流域上游的宜溧—洮滆水系主要河道设置67个监测点,分别于2014年1月(冬季)、4月(春季)、8月(夏季)、11月(秋季)进行水质监测,采用多元统计方法分析了水质的空间差异性和季节性变化,并利用水质标识指数法对水环境质量进行评价.结果表明,宜溧—洮滆水系污染程度较严重,总氮(TN)、总磷(TP)和高锰酸盐指数(CODMn)浓度年均值分别为4.93、0.26和7.63 mg/L;单因素多元方差分析和聚类分析显示污染物浓度具有显著时空差异性,时间上冬、春季污染程度较高而夏、秋季较低,空间上无锡和常州氮、磷污染较为严重,宜兴和溧阳市有机污染程度较高;水质标识评价结果显示流域内水质基本为IV类或V类,其中TN、TP及CODMn是关键污染指标.  相似文献   

18.
This research explains the background processes responsible for the spatial distribution of hydrochemical properties of the picturesque eutrophic Himalayan Lake, Dal, located in Kashmir valley, India. Univariate and multivariate statistical analyses were used to understand the spatiotemporal variability of 18 hydrochemical parameters comprising of 12,960 observations collected from 30 sampling sites well distributed within the lake at a grid spacing of 1 km2 from March 2014 to February 2016. Hierarchical cluster analysis (HCA) grouped all the sampled data into three clusters based on the hydrochemical similarities, Discriminant analysis also revealed the same clusters and patterns in the data, validating the results of HCA. Wilk’s λ quotient distribution revealed the contribution of ions, nutrients, secchi disk transparency, dissolved oxygen and pH in the formation of clusters. The results are in consonance with the Principal Component Analysis of the whole lake data and individual clusters, which showed that the variance is maximally explained by the ionic component (46.82%) followed by dissolved oxygen and pH (9.36%), nitrates and phosphates (7.33%) and Secchi disk transparency (5.98%). Spatial variability of the hydrochemistry of the lake is due to the variations in water depth, lake water dynamics, flushing rate of water, organic matter decomposition, and anthropogenic pressures within and around the Dal lake ecosystem. Overall, the water quality of the lake is unfit for drinking due to the presence of coliform bacteria in the lake waters.  相似文献   

19.
We simulated the effects of irrigation on groundwater flow dynamics in the North China Plain by coupling the NIES Integrated Catchment‐based Ecohydrology (NICE) model with DSSAT‐wheat and DSSAT‐maize, two agricultural models. This combined model (NICE‐AGR) was applied to the Hai River catchment and the lower reach of the Yellow River (530 km wide by 840 km long) at a resolution of 5 km. It reproduced excellently the soil moisture, evapotranspiration and crop production of summer maize and winter wheat, correctly estimating crop water use. So, the spatial distribution of crop water use was reasonably estimated at daily steps in the simulation area. In particular, NICE‐AGR reproduced groundwater levels better than the use of statistical water use data. This indicates that NICE‐AGR does not need detailed statistical data on water use, making it very powerful for evaluating and estimating the water dynamics of catchments with little statistical data on seasonal water use. Furthermore, the simulation reproduced the spatial distribution of groundwater level in 1987 and 1988 in the Hebei Plain, showing a major reduction of groundwater level due mainly to overpumping for irrigation. Copyright © 2006 John Wiley & Sons, Ltd.  相似文献   

20.
梯级筑坝对黑河水质时空分布特征的影响   总被引：1，自引：0，他引：1  
为探究梯级大坝建设对河流水质变化规律的影响,将黑河上中游划分为坝上河段、坝下河段及自然河段,于2017年12月-2018年8月选取了24个主要控制断面进行水质调查,并采用多元统计的方法对比分析了不同时空尺度上的水质分布特征.结果表明:黑河上中游水质时空变化的主要影响因子为水温(WT)、pH值、溶解氧(DO)、电导率(EC)、总氮(TN)、总磷(TP)和五日生化需氧量(BOD_5).空间尺度上,WT、EC、BOD_5、高锰酸盐指数(CODMn)、TN等指标具有显著性差异,其中坝上河段受BOD_5、CODMn影响较大,自然河段WT、EC和TN为关键指标,而各个因子对坝下河段水质影响较小.时间尺度上,WT、EC、BOD_5、氨氮与季节变化存在明显相关性,是不同河段水质时间变化的控制因子,且大多数水质因子在非汛期变化最明显.降水、温度、水文条件等季节性影响因素和梯级水库联合运用模式是该区域水质时间差异的主要原因;空间差异主要受祁连、张掖地区外源性污染物排放以及筑坝环境下水动力条件改变而产生的沉积滞留效应和沿程累积效应影响.研究表明,外源性污染源依然是导致水质变差的主要因素,梯级筑坝则是导致水质变差的间接因素.因此控制该区域人类活动所造成的外源性污染源,并针对不同种类污染物的季节变化特征实施合理的水库运行方式是改善水电梯级开发河段水质状况的关键.  相似文献   

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