Quality assessment of pollution indicators in marine water at critical locations of the Gulf of Mannar Biosphere Reserve, Tuticorin

Viji, R.; D, Shrinithivihahshini Nirmaladevi; Balakrishnan, S.; Rengaraj, Chithradevi; Sheelamary, Mariyaselvam

doi:10.1016/j.marpolbul.2017.10.091

Cited by 23 publications

(10 citation statements)

References 23 publications

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“…Dissolved oxygen was generally negatively correlated with water temperature, i.e., high temperature and abundant sunshine are likely to cause lower concentrations of dissolved oxygen in summer than in winter [54]. Since dissolved oxygen is an important indicator to maintain biological survival in water and to measure the classifications of water quality [55], the interactions between dissolved oxygen and other water quality factors in this project need further study. In addition, some stations that detected dissolved oxygen concentrations increased abnormally in some seasons, therefore, there is a need to focus on algae density monitoring.…”

Section: Resultsmentioning

confidence: 99%

Spatio-Temporal Characterization Analysis and Water Quality Assessment of the South-to-North Water Diversion Project of China

Nong

Shao

Xiao

et al. 2019

IJERPH

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In this article, a data matrix of 20 indicators (6960 observations) was obtained from 29 water quality monitoring stations of the Middle Route (MR) of the South-to-North Water Diversion Project of China (SNWDPC). Multivariate statistical techniques including analysis of variance (ANOVA), correlation analysis (CA), and principal component analysis (PCA) were applied to understand and identify the interrelationships between the different indicators and the most contributive sources of anthropogenic and natural impacts on water quality. The water quality index (WQI) was used to assess the classification and variation of water quality. The distributions of the indicators revealed that six heavy-metal indicators including arsenic (As), mercury (Hg), cadmium (Cd), chromium (Cr), selenium (Se), and lead (Pb) were within the Class I standard, while the As, Pb, and Cd displayed spatial variation. Moreover, some physicochemical indicators such as dissolved oxygen, 5-day biochemical oxygen demand (as BOD5), and total phosphorus (TP) had spatio-temporal variability. The correlation analysis result demonstrated that As, Hg, Cd, Cr, Se, Pb, copper (Cu), and zinc (Zn) had high correlation coefficients. The PCA result extracted three principal components (PC) accounting for 82.67% of the total variance, while the first PC was indicative of the mixed sources of anthropogenic and natural contributions, the second and the third PCs were mainly controlled by human activities and natural sources, respectively. The calculation results of the WQI showed an excellent water quality of the MR of the SNWDPC where the values of the stations ranged from 10.49 to 17.93, while Hg was the key indicator to determine the WQI > 20 of six stations, which indicated that the Hg can be the main potential threat to water quality and human health in this project. The result suggests that special attention should be paid to the monitoring of Hg, and the investigation and supervision within the areas of high-density human activities in this project should be taken to control the impacts of urban and industrial production and risk sources on water quality.

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Section: Resultsmentioning

confidence: 99%

Spatio-Temporal Characterization Analysis and Water Quality Assessment of the South-to-North Water Diversion Project of China

Nong

Shao

Xiao

et al. 2019

IJERPH

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“…In general, One-way ANOVA is used to test interaction effects on multivariate data, using (approximate) permutation tests to avoid grossly unrealistic normality assumptions (Clarke et al 2006). Statistical approaches like ANOVA were used by many researchers to ascertain signi cant differences between months and stations for physicochemical parameters (Jha et al 2014, 2015a andRajendran et al 2018). PCA is a common but one of the most powerful techniques applied for minimizing the dimensionality of large data sets without redundancy of information.…”

Section: Statistical Analysesmentioning

confidence: 99%

Statistical Elucidations of The Seasonal Ambience of Physicochemical Characteristics of Coastal Waters Around South Andaman, India

Shankar¹,

Purti²,

Dharanirajan

et al. 2021

Preprint

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The coastal areas of Port Blair in Andaman are threatened by severe water pollution due to the human settlements in these regions. The objective of this study was to determine the level of pollution in ten different anthropogenically dynamic coastal regions by assessing the seasonal variations of various physicochemical characteristics. The regions selected for this study were Burmanallah (BA), Carbyn's Cove (CC), Chattam (CH), Flat Bay (FB), HADDO Harbour (HH), Junglighat Bay (JB), Minne Bay (MB), Phoenix Bay (PB), Sisostris Bay (SB) and Wandur (WA) in South Andaman. The study was carried out from January 2018 to December 2018 to investigate seasonal variations in the physicochemical parameters such as pH, temperature, salinity, dissolved oxygen, nitrite, nitrate, ammonia, silicate, phosphate, and chlorophyll-α using multivariate statistical analysis. Statistical analyses suggest that the regions of JB and MB were highly polluted while, BA, CC, FB, and WA were the least polluted. Landuse and land cover analysis of the study area further facilitated and supported the multivariate statistical results.

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“…3). The dynamic equation is given by (1) and the kinematic transformation between earth-fixed and body-fixed frames is expressed by (2), respectively:…”

Section: Alba Asc Modelingmentioning

confidence: 99%

“…Water, the most precious resource for human being, is being vulnerable to contamination at present since there is enough evidence [1]. The Mar de Grau is the Peruvian sea with abundant marine species, presents a littoral of 3079.50 km and a breadth extension of 370.4 km (200 nmi).…”

Section: Introductionmentioning

confidence: 99%

Parameter Estimation of the ALBA Autonomous Surface Craft

Valdivia-Fernandez

Monroy-Ochoa

Yanyachi

et al. 2020

IJACSA

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Arequipa region holds the largest extension of the Peruvian littoral at the Pacific sea, has also fresh water resources composed of rivers and lagoons from the coast to the Andes highland. The ALBA vehicle is a low-cost autonomous surface vessel with open source architecture that is being developed to support water monitoring tasks in the region. This article deals with the nonlinear identification problem for an autonomous surface craft and the maximum likelihood estimation approach is used to estimate its parameters. The parametric nonlinear model is considered with simulated and experimental data. The results shows good fitting values when two, three and a maximum four parameters are estimated.

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Quality assessment of pollution indicators in marine water at critical locations of the Gulf of Mannar Biosphere Reserve, Tuticorin

Cited by 23 publications

References 23 publications

Spatio-Temporal Characterization Analysis and Water Quality Assessment of the South-to-North Water Diversion Project of China

Spatio-Temporal Characterization Analysis and Water Quality Assessment of the South-to-North Water Diversion Project of China

Statistical Elucidations of The Seasonal Ambience of Physicochemical Characteristics of Coastal Waters Around South Andaman, India

Parameter Estimation of the ALBA Autonomous Surface Craft

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