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1.
Cluster analysis (CA), discriminant analysis (DA) and principal component analysis (PCA) were comprehensively coupled to explore and identify the spatial and temporal variation and potential pollution sources in coastal water quality along Macau peninsula. The results show that the 12 months could be grouped into two periods, June–September and the remaining months, and the entire area divided into two clusters, one located at the western sides, and the other on the southeast and southern sides of the Macau peninsula. Through backward stepwise DA, pH, Cl−, TSS, Color and TP, Chloride, Color, NH4 +, DO, COD were discriminant variables of spatial and temporal variation, with 84.82 and 76.54% correct assignments, respectively. Fecal pollution, organic pollution and soil weathering are among the major sources for coastal water quality deterioration along Macau peninsula. This study illustrates that application of multivariate statistical techniques was beneficial to gain knowledge for further optimizing the monitoring network and controlling coastal water quality along Macau peninsula.  相似文献   

2.
This study analysed monthly physico-chemical and biological data collected from 18 marine monitoring stations in Victoria Harbour and its vicinity in Hong Kong, from 1988 to 1996. Cluster analysis based on all water quality parameters measured shows that the 18 monitoring stations can be grouped into four clusters: Cluster I consists of stations located in the Harbour proper; Cluster II consists of stations located west of the Harbour and along the Rambler Channel; Cluster III consists of stations located east of the Harbour near Junk Bay and Cluster IV consists of stations located west of the Harbour and near the Ma Wan, Kap Shui Mun and Western Fairways. Factor analysis shows high positive loadings for nutrients in the first two factors of the four clusters. This suggests that effluents from the 11 outfalls of sewage screening plants influence the water quality of Victoria Harbour and its vicinity. Other factors such as storm water runoff, marine traffic, construction and industrial activities and the Pearl River discharges also appear to play an important role in determining local water quality. Five stations located along an east–west transect across the Harbour were selected for trend analysis. The three stations located in the Harbour exhibit an increasing trend for temperature and levels of total phosphorus (TP), ortho-phosphate phosphorous (PO4-P) and faecal bacteria and a decreasing trend for pH and levels of total nitrogen (TN), total kjeldahl-nitrogen (TKN), 5-day biochemical oxygen demand (BOD5) and chlorophyll a. For the station located east of the Harbour, an increasing trend is observed for levels of TP, PO4-P, but no decreasing trend in TN and TKN is detected. For the station located west of the Harbour, no decreasing trend in TN, TKN and chlorophyll a is observed. Changes in levels of phosphorus and nitrogen in Victoria Harbour and the immediate vicinity have led to significant increases in the ratios of Total Silica (TSi) to TN, as well as a decrease in TN to TP and TSi to TP in most stations. Results of the present study show that Victoria Harbour and its immediate vicinity remain polluted.  相似文献   

3.
Eutrophication has become a crucial issue for water resource management in recent years. In addition, reservoir trophic states are varied with environmental and water quality variables. The objectives of this study were to apply the DFA model to examine which water quality variables significantly affect variations of trophic state index (TSI) factors (i.e. total phosphorus (TP), chlorophyll-a (Chl-a), and Secchi disk transparency (SD)) and use classification and regression tree (CART) to determine the trophic states of the Shinmen Reservoir based on the levels of TSI factors during spring 2001–winter 2009. Results showed that the optimal DFA model contained one common trend (the underlying processes influencing trophic states, which can be rainfall intensity or runoff volume) and 7 explanatory variables. Turbidity (TB), pH, and dissolved oxygen (DO) influence concentrations of TP, while ammonium nitrogen (NH3-N), organic nitrogen (O-N), and nitrate nitrogen (NO3-N) control variations of Chl-a, and TB is related to SD. The CART model can specify trophic states only using two dominant driving factors, i.e. TP and Chl-a. The results of the CART illustrated that eutrophication could be occurred in the Shihmen Reservoir if TP is greater than 31.65 μg/L or if Chl-a is greater than 5.95 μg/L while TP concentration is less than 31.65 μg/L. Runoff nonpoint source pollution resulted from heavy storms may be the important factor affecting reservoir trophic states. Establishing vegetative filter strips along the riparian zone may able to effectively reduce this pollution in a reservoir. The integrated DFA and CART serves as good-fit relationships among trophic states, TSI factors, and water quality variables and provide control strategies for managing water quality in the Shihmen Reservoir.  相似文献   

4.
太湖水质的动态变化及影响因子的多元分析   总被引：27，自引：11，他引：16  
利用１９９１～１９９２年监测资料,分析了太湖梅梁湾和局面西太湖水域水质的动态变化。用主成分分析方法揭示出各因子间的相互关系。结果表明,水质主要因子有明显的时空变化特征,沿南北方向从湾内向湾外,ＴＰ、ＴＮ、ＣＯＤ、Ｃｈｌ－ａ和电导率明显递减,且ＴＰ和ＴＮ含量季节变化,冬季高于夏季,梁溪河口更是如此,Ｃｈｌ－ａ含量与ＴＰ、ＴＮ含量密切相关,其变化基本与水温同步,时间上略后滞。主成分分析说明,ＴＰ、ＴＮ  相似文献   

5.
李未  秦伯强 《湖泊科学》2012,24(6):865-874
采用太湖湖泊生态系统研究站太湖梅梁湾富营养化四种主要驱动因子叶绿素a(Chl.a)、水温、总磷(TP)、总氮浓度1992-2010年的监测数据,利用小波变换方法,分析了四种因子不同时间尺度上的时间格局特征.结果表明,四种驱动因子在年际和年代际尺度上都具有清晰的多时间尺度特征,主周期各不相同,但Chl.a和TP浓度的小波实部变化趋势具有较高的一致性.本文分析了各因子在不同时间尺度上的强弱分布以及高低交替,并在此基础上从时间尺度的角度预测出在未来3~5年内,太湖梅梁湾湖区的富营养化程度将保持在一个比较平稳的水平,为太湖富营养化的认识和治理提供更加可靠的科学依据.  相似文献   

6.
Various chemometric methods were used to analyze data sets of marine water quality for 19 parameters measured at 16 different sites of southern Hong Kong from 2000 to 2004 (18,240 observations), to determine temporal and spatial variations in marine water quality and identify pollution sources. Hierarchical cluster analysis (CA) grouped the 12 months into three periods (January-April, May-August and September-December) and the 16 sampling sites into two groups (A and B) based on similarities in marine water-quality characteristics. Discriminant analysis (DA) was important in data reduction because it used only eight parameters (TEMP, TURB, Si, NO(3)(-)-N, NH(4)(+)-N, NO(2)(-)-N, DO, and Chl-a) to correctly assign about 86% of the cases, and five parameters (SD, NH(4)(+)-N, TP, NO(2)(-)-N, and BOD(5)) to correctly assign >81.15% of the cases. In addition, principal component analysis (PCA) identified four latent pollution sources for groups A and B: organic/eutrophication pollution, natural pollution, mineral pollution, and nutrient/fecal pollution. Furthermore, during the second and third periods, all sites received more organic/eutrophication pollution and natural pollution than in the first period. SM5, SM6, SM17, SM10, SM11, SM12, and SM13 (second period) were affected by organic and eutrophication pollution, whereas SM3 (third period) and SM9 (second period) were influenced by natural pollution. However, differences between mineral pollution and nutrient/fecal pollution were not significant among the three periods. SM17 and SM10 were affected by mineral pollution, whereas SM4 and SM9 were highly polluted by nitrogenous nutrient/fecal pollution.  相似文献   

7.
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   

8.
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9.
入库河流与水库存在空间上的连续性,河流污染物输入是水库水质恶化的主要原因,对大伙房水库及其入库支流61个采样点的水质状况进行调查,并运用聚类分析和主成分分析对大伙房水库及入库支流的水质空间特性和主要污染物进行分析.聚类分析显示,按照水质相似性将大伙房水库及入库支流水质可分为上游区、下游区和库区3个典型空间区域.分别对3个区域进行主成分分析,结果显示:入库支流上游区和下游区水质主要影响因素为氨氮、总氮和化学需氧量,库区影响水质的主要因素为温度、p H值、浊度、溶解氧、电导率、氨氮和总氮.对上游、下游和库区水质均有显著影响的因子为氨氮和总氮,上游区、下游区和库区氨氮浓度均值分别为0.06、0.10和0.19 mg/L,总氮浓度均值分别为0.13、0.16和0.26 mg/L.入库河流下游区对水库水质影响较大,受社河和浑河污染物输入的影响,大伙房水库水质在空间上呈现社河入库区水质优于浑河入库区水质.并且库区氨氮和总氮浓度均与距岸边距离呈负相关,溶解氧和p H值均与距入库口距离呈负相关,表明入库河流污染物输入和环库区面源污染均对大伙房水库水质产生一定影响.  相似文献   

10.
基于2011—2020年乌梁素海水质监测数据,将综合营养指数法、PCA排序法和ArcGIS克里金插值法有机结合,综合评价2011—2020年乌梁素海水体富营养化程度年际时空变化特征,厘清引起水体富营养化发生变化的关键性驱动因子。研究结果表明:(1)乌梁素海水体总磷和总氮的峰值出现在平水期,氨氮的峰值在枯水期,CODMn的峰值在丰水期,水质整体以地表Ⅲ类水为主。(2)2011—2020年湖体水质经历了由轻度富营养-中营养-轻度富营养-中营养的变化过程,综合营养状态指数在60～70(中度富营养)的湖区面积占比由21.49%逐渐消失,综合营养状态指数在30～50(中营养)的湖区面积占比由23.84%扩增到44.87%。(3)乌梁素海生态补水量与总氮、总磷、CODMn和综合营养状态指数呈负相关,是影响湖泊水体营养化的另一个关键性驱动因子。  相似文献   

11.
云贵高原湖泊水质现状及演变   总被引：16，自引：6，他引：10  
利用2008年云贵高原13个湖泊丰水期的全面水质调查数据,系统分析云贵高原湖泊水质现状,通过与历史资料对比,揭示20年来的水质变化,并分析水质变化的原因.同时利用主成分分析将23个水质参数概括为6个主要成分,除程海外所有湖泊水质均与第一主成分密切相关.人类活动影响下的水体富营养化、有机污染以及农业面源污染等是除程海外湖泊污染的主要驱动因子,程海水质变化主要受水体的矿化度增加所驱动.另外,根据各主成分得分,本文也对13个湖泊水质进行了综合评价,并在评价的基础上就湖泊的保护和治理提出建议.  相似文献   

12.
Port Blair is the capital city of Andaman & Nicobar Islands, the union territory of India. More than 50% of the population of these islands lives around Port Blair Bay. Therefore the anthropogenic effects in the bay water were studied for monitoring purpose from seven stations. Physico-chemical parameters of seawater were analyzed in samples collected once in every 3 months for 2 years from seven sampling stations located in Port Blair Bay, South Andaman Island to evaluate the spatial and tidal variation. Cluster analysis and factor analysis were applied to the experimental data in an attempt to understand the sources of variation of physico-chemical parameters. In cluster analysis, the stations Junglighat Bay and Phoenix Bay having high anthropogenic influence formed a separate group. The factors obtained from factor analysis indicated that the parameters responsible for physico-chemical variations are mainly related to land run-off, sewage outfall and tidal flow.  相似文献   

13.
An objective classification analysis was performed on a water quality data set from 25 sites collected monthly during 1994-2003. The water quality parameters measured included: TN, TON, DIN, NH4+, NO3-, NO2-, TP, SRP, TN:TP ratio, TOC, DO, CHL A, turbidity, salinity and temperature. Based on this spatial analysis, Biscayne Bay was divided into five zones having similar water quality characteristics. A robust nutrient gradient, driven mostly by dissolved inorganic nitrogen, from alongshore to offshore in the main Bay, was a large determinant in the spatial clustering. Two of these zones (Alongshore and Inshore) were heavily influenced by freshwater input from four canals which drain the South Dade agricultural area, Black Point Landfill, and sewage treatment plant. The North Bay zone, with high turbidity, phytoplankton biomass, total phosphorus, and low DO, was affected by runoff from five canals, the Munisport Landfill, and the urban landscape. The South Bay zone, an embayment surrounded by mangrove wetlands with little urban development, was high in dissolved organic constituents but low in inorganic nutrients. The Main Bay was the area most influenced by water exchange with the Atlantic Ocean and showed the lowest nutrient concentrations. The water quality in Biscayne Bay is therefore highly dependent of the land use and influence from the watershed.  相似文献   

14.
An expert system is proposed for the assessment of characteristic and the trophic status of lakes for which little or no direct observational data are available. The system is based on the mathematical apparatus of fuzzy logic and applied to the best studied in Russia Karelian lake region. The created database on the morphometry, hydrology, hydrochemistry, and hydrobiology for 100 best studied lakes is described. The lakes are classified by methods of multidimensional statistics, factor, cluster, and logical-information analysis with the use of multidimensional scaling technique. Serious drawbacks of different classifications are demonstrated, in particular, because of the lack of a constructive algorithm for the recovery of unknown characteristics of a lake once it is referred to a certain class. In such cases, the mathematical apparatus of fuzzy sets and fussy logic should be used.  相似文献   

15.
In the German State Brandenburg, water clarity and the concentrations of the water quality components chlorophyll a, seston and gelbstoff were measured in 27 lakes. Correlation analysis showed, that spectral beam attenuation at 662 and 514 nm was mainly dependent on changes in chlorophyll a concentrations. In the UV-channel at 360 nm, beam attenuation depended mostly on gelbstoff.

Multiple linear regression provided a direct model of beam attenuation at 514 nm with the inputs of inorganic seston, chlorophyll a and gelbstoff. The specific beam attenuation coefficients were comparable to other natural waters around the world. An inverse model is presented, from which gelbstoff and chlorophyll a could be predicted with some accuracy from the inputs of beam attenuation coefficients at 514 and 360 nm. However, it became obvious that biological variability put major constraints on the predictive capacity of both the direct and the inverse model.

Furthermore, we observed a good correspondence of Secchi depth and the inverse of beam attenuation at 514 nm. The predictions of Secchi depth and chlorophyll a concentration from the inverse model were assessed in perspective of using this instrument instead of laborious chemical analysis for future trophic status classification according to LAWA (Länderarbeitsgemeinschaft Wasser). Predictions of trophic status were principally good when using calibrated models, however, quality of classification critically depended on predictions of chlorophyll a.  相似文献   


16.
Data for major, minor and trace elements in groundwaters from Mt. Etna volcano collected in 1994, 1995 and 1997 were analyzed using Cluster Analysis (CA). Two groups of sampling sites were identified (named clusters A and B), mainly on the basis of their different salinity and content of dissolved CO2. The highest levels of both of these parameters were observed in the sites of cluster A, located in the lower south-western and central eastern flanks of the volcano. For both of the statistical groups CA was repeated, taking into account the mean values of each parameter in time, and the results allowed us to recognize four distinct groups of parameters for each group of sites on the basis of their temporal patterns. Four different types of temporal patterns were recognized: concave, convex, increasing, decreasing. The observed changes were basically interpreted as a result of the different response of dissolved chemical elements to changes in the aqueous environment and/or in their solubility/mobility in water due to different rates of input of magmatic gases to Etna’s aquifers. The main changes occurred in 1995, when Etna’s volcanic activity resumed after a two-year period of rest. The temporal changes of the majority of the studied parameters (water temperature, water conductivity, Eh, pH, Al, Mg, B, Ca, Cl−, Hg, Mn, Mo, Na, Ni, Se, Si, Sr, Cr Zn and pCO2) were not cluster-dependent, therefore they were not apparently affected by differences in water salinity between the two groups of sampling sites. A limited number of parameters (Ti, K, Li, HCO3−, As, Fe, SO42−, Cu and V), however, manifested different behaviors, depending on the cluster of sites to which they belonged, thus suggesting their apparent dependency on water salinity.  相似文献   

17.
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   

18.
This study employed three chemometric data mining techniques (factor analysis (FA), cluster analysis (CA), and discriminant analysis (DA)) to identify the latent structure of a water quality (WQ) dataset pertaining to Kinta River (Malaysia) and to classify eight WQ monitoring stations along the river into groups of similar WQ characteristics. FA identified the WQ parameters responsible for variations in Kinta River's WQ and accentuated the roles of weathering and surface runoff in determining the river's WQ. CA grouped the monitoring locations into a cluster of low levels of water pollution (the two uppermost monitoring stations) and another of relatively high levels of river pollution (the mid-, and down-stream stations). DA confirmed these clusters and produced a discriminant function which can predict the cluster membership of new and/or unknown samples. These chemometric techniques highlight the potential for reasonably reducing the number of WQVs and monitoring stations for long-term monitoring purposes.  相似文献   

19.
长春市南湖富营养化高光谱遥感监测模型   总被引：16，自引：4，他引：12  
通过对长春市南湖水质参数和高光谱反射率的相关分析,建立两者间的一元回归模型;同时利用日本学者相崎守弘等人提出的修正营养状态指数(TSIM)模型,分别针对水质参数实验室数据和高光谱数据,对长春市南湖富营养化程度进行评价和监测.结果表明:1)利用高光谱遥感监测模型进行湖泊富营养化监测和评价,能够获取较为准确的评价结果,相对于传统监测方法具有省时省力的特点;2)用实验室数据得出的TSIM修正营养状态指数,各点数据起伏比较大,而高光谱遥感监测模型模拟营养状态指数相对平缓,这表明监测模型对各点数据进行了不同程度的同化,相对缩小了同期各点数据和异期同点数据之间的差异,这与实验室化学分析数据监测结果相比是一个不足之处;3)长春市南湖水体呈现较为严重的富营养化状态,需要采取措施防止南湖水质进一步恶化.  相似文献   

20.
对太湖梅梁湾T0905岩芯摇蚊幼虫亚化石组合进行了分析,探讨了自1940年以来梅梁湾湖区摇蚊幼虫对营养盐演化的响应.结果表明,梅梁湾湖区摇蚊组合变化以1970年为分界点,经历了由Tanytarsus为优势属种向富营养属种Chironomus plumosus-type和Microchironomus为优势组合转变的过程...  相似文献   

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