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FOREST C.GARNER MARTIN A.STAPANIAN KIRK E.FITZGERALD Lockheed Engineering Sciences Co. E.Flamingo R Las Vegas NV U.S.A. 《地理学报(英文版)》1991,(3)
Multivariate outliers in environmental data sets are often caused by atypical measurement error in a singlevariable.From a quality assurance perspective it is important to identify these variables efficiently so thatcorrective actions may be performed.We demonstrate a procedure for using two multivariate tests toidentify which variable‘caused’each outlier.The procedure is tested with simulated data sets that havethe same correlation structure as selected water chemistry variables from a survey of lakes in the WesternUnited States.The success rates are evaluated for three of the variables for sample sizes of 50 and 100,significance levels of 0.01 and 0.05 and various amounts of mean shift.The procedure works best forhighly correlated variables. 相似文献
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The Andaman and Nicobar Islands are one of the Union Territories of India, located in the eastern part of the Bay of Bengal. In 2010 summer, the increment in sea surface water temperature (up to 34℃) resulted in the bleaching of about 74% to 77% of corals in the South Andaman. During this event, coral species such as Acropora cerealis, A. humilis, Montipora sp., Favia pallida, Diploastrea sp., Goniopora sp. Fungia concinna, Gardineroseries sp., Porites sp., Favites abdita and Lobophyllia robusta were severely affected. This study is to assess the recovery status of the reef ecosystem by estimating the percentage of Live Coral cover, Bleached coral cover, Dead coral with algae, Rubble, Sandy flat, Algal assemblage and other associated organisms. The sedimentation rate (mg cm-2 d-1) and coral coverage (%) were assessed during this study period. The average sedimentation rate was ranged between 0.27 and 0.89 mg cm-2 d-1 . The observed post bleaching recovery of coral cover was 21.1% at Port Blair Bay and 13.29% at Havelock Island. The mortality rate of coral cover due to this bleaching was estimated as 2.05% at Port Blair Bay and 9.82% at Havelock Island. Once the sea water temperature resumed back to the normal condition, most of the corals were found recovered. 相似文献
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Biraja Kumar Sahu Mehmuna Begum M.K. Khadanga Dilip Kr Jha N.V. Vinithkumar R. Kirubagaran 《Marine pollution bulletin》2013,66(1-2):246-251
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
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A 1.2 m snow pit was recovered on July 29th, 2009 from the Bogda Glacier, eastern Tianshan (天山). The sample site temperature of -9.6 ℃ indicates that the unique glaciochemical re-cord was well preserved and suitable for the reconstruction of air pollution levels in this previously un-explored region. Samples were analyzed for major ions (Na+, K+, Ca2+, Mg2+, NH4+, Cl-, SO42-, NO3-, HCOO-, and CH3COO-). NO3- and SO42- were characterized by significant high levels of pollution con-centration. Most air masses ... 相似文献
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Multivariate statistical approach to identify significant sources influencing the physico-chemical variables in Aerial Bay,North Andaman,India 总被引：1，自引：0，他引：1
Dilip Kumar Jha N.V. Vinithkumar Biraja Kumar Sahu Apurba Kumar Das P.S. Dheenan P. Venkateshwaran Mehmuna Begum T. Ganesh M. Prashanthi Devi R. Kirubagaran 《Marine pollution bulletin》2014
Aerial Bay is one of the harbor towns of Andaman and Nicobar Islands, the union territory of India. Nevertheless, it is least studied marine environment, particularly for physico-chemical assessment. Therefore, to evaluate the annual spatiotemporal variations of physico-chemical parameters, seawater samples collected from 20 sampling stations covering three seasons were analyzed. Multivariate statistics is applied to the investigated data in an attempt to understand the causes of variation in physico-chemical parameters. Cluster analysis distinguished mangrove and open sea stations from other areas by considering distinctive physico-chemical characteristics. Factor analysis revealed 79.5% of total variance in physico-chemical parameters. Strong loading included transparency, TSS, DO, BOD, salinity, nitrate, nitrite, inorganic phosphate, total phosphorus and silicate. In addition, box-whisker plots and Geographical Information System based land use data further facilitated and supported multivariate results. 相似文献
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E.A.YFANTIS Computer Science Department University of Neva Las Vegas NV U.S.A.G.T.FLATMAN U.S.Environmental Protection Agency E.Harmon Las Vegas NV U.S.A. 《地理学报(英文版)》1991,(3)
In many environmental applications,such as exposure assessment and risk modelling,the desiredestimate is a random variable computed as the product of three independently distributed randomvariables.These variables may not necessarily have the same mean and variance.The method for findingthe 100(1-α)% confidence interval for the mean of the product random variable has been proposed bysome practitioners as the product of the 100(1-α)% confidence interval of the three means.In this paperwe show that the distribution of the product of three independent normal random variables is not normal.We find the mean and variance of the product distribution.Further,we show that although the meanof the product is equal to the product of the means,the product of the three confidence intervals is nota good approximation of the confidence intervals for the mean of the product variable.The confidenceinterval of the mean of the product variable may be estimated by computer simulation.An algorithmfor estimating the confidence interval for the mean of the product random variable is given.The programimplementing this algorithm is given as an appendix. 相似文献
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