Assessment of Seasonal and Spatial Variations of Coastal Water Quality Using Multivariate Statistical Techniques

This study investigates the seasonal and spatial trends in Kuwait’s coastal water’s physical, chemical, and biological parameters by applying multivariate statistical techniques, including cluster analysis (CA), principal component/factor analysis (PCA/FA), and the Pearson correlation (PC) method to...

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Autores principales:	Mohamad Alkhalidi, Abdalrahman Alsulaili, Badreyah Almarshed, Majed Bouresly, Sarah Alshawish
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	water quality principal component analysis cluster analysis environmental assessment Pearson correlation Kuwait Bay Naval architecture. Shipbuilding. Marine engineering VM1-989 Oceanography GC1-1581
Acceso en línea:	https://doaj.org/article/d6f9fc45da194d22a5c8576de335b26f
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spelling	oai:doaj.org-article:d6f9fc45da194d22a5c8576de335b26f2021-11-25T18:05:09ZAssessment of Seasonal and Spatial Variations of Coastal Water Quality Using Multivariate Statistical Techniques10.3390/jmse91112922077-1312https://doaj.org/article/d6f9fc45da194d22a5c8576de335b26f2021-11-01T00:00:00Zhttps://www.mdpi.com/2077-1312/9/11/1292https://doaj.org/toc/2077-1312This study investigates the seasonal and spatial trends in Kuwait’s coastal water’s physical, chemical, and biological parameters by applying multivariate statistical techniques, including cluster analysis (CA), principal component/factor analysis (PCA/FA), and the Pearson correlation (PC) method to the average daily reading of water quality parameters from fifteen stations over one year. The investigated parameters are pH, turbidity, chlorophyll-a, conductivity, dissolved oxygen (DO), phycoerythrin, salinity, and temperature. The results show that the coastal water of Kuwait is subjected to high environmental pressure due to natural and human interferences. During 2017, the DO levels were below the threshold limit, and at the same time, the water temperature and salinity were very high, causing a series of fish death events. CA resulted in three different regions based on the turbidity, including high, moderate, and low regions, and three seasons (winter, summer, and autumn). Spring is very short and overlaps with winter and summer. PCA/FA applied on the datasets assisted in extracting and identifying parameters responsible for the variations in the seasons and regions obtained from CA. Additionally, Pearson’s correlation resulted in a strong positive relation between chlorophyll and phycoerythrin in 7 out of the 15 stations. However, at high turbidity regions (stations 1 and 2), chlorophyll concentration was low. Additionally, the negative correlation between DO and temperature was observed at stations with rare human activities.Mohamad AlkhalidiAbdalrahman AlsulailiBadreyah AlmarshedMajed BoureslySarah AlshawishMDPI AGarticlewater qualityprincipal component analysiscluster analysisenvironmental assessmentPearson correlationKuwait BayNaval architecture. Shipbuilding. Marine engineeringVM1-989OceanographyGC1-1581ENJournal of Marine Science and Engineering, Vol 9, Iss 1292, p 1292 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	water quality principal component analysis cluster analysis environmental assessment Pearson correlation Kuwait Bay Naval architecture. Shipbuilding. Marine engineering VM1-989 Oceanography GC1-1581
spellingShingle	water quality principal component analysis cluster analysis environmental assessment Pearson correlation Kuwait Bay Naval architecture. Shipbuilding. Marine engineering VM1-989 Oceanography GC1-1581 Mohamad Alkhalidi Abdalrahman Alsulaili Badreyah Almarshed Majed Bouresly Sarah Alshawish Assessment of Seasonal and Spatial Variations of Coastal Water Quality Using Multivariate Statistical Techniques
description	This study investigates the seasonal and spatial trends in Kuwait’s coastal water’s physical, chemical, and biological parameters by applying multivariate statistical techniques, including cluster analysis (CA), principal component/factor analysis (PCA/FA), and the Pearson correlation (PC) method to the average daily reading of water quality parameters from fifteen stations over one year. The investigated parameters are pH, turbidity, chlorophyll-a, conductivity, dissolved oxygen (DO), phycoerythrin, salinity, and temperature. The results show that the coastal water of Kuwait is subjected to high environmental pressure due to natural and human interferences. During 2017, the DO levels were below the threshold limit, and at the same time, the water temperature and salinity were very high, causing a series of fish death events. CA resulted in three different regions based on the turbidity, including high, moderate, and low regions, and three seasons (winter, summer, and autumn). Spring is very short and overlaps with winter and summer. PCA/FA applied on the datasets assisted in extracting and identifying parameters responsible for the variations in the seasons and regions obtained from CA. Additionally, Pearson’s correlation resulted in a strong positive relation between chlorophyll and phycoerythrin in 7 out of the 15 stations. However, at high turbidity regions (stations 1 and 2), chlorophyll concentration was low. Additionally, the negative correlation between DO and temperature was observed at stations with rare human activities.
format	article
author	Mohamad Alkhalidi Abdalrahman Alsulaili Badreyah Almarshed Majed Bouresly Sarah Alshawish
author_facet	Mohamad Alkhalidi Abdalrahman Alsulaili Badreyah Almarshed Majed Bouresly Sarah Alshawish
author_sort	Mohamad Alkhalidi
title	Assessment of Seasonal and Spatial Variations of Coastal Water Quality Using Multivariate Statistical Techniques
title_short	Assessment of Seasonal and Spatial Variations of Coastal Water Quality Using Multivariate Statistical Techniques
title_full	Assessment of Seasonal and Spatial Variations of Coastal Water Quality Using Multivariate Statistical Techniques
title_fullStr	Assessment of Seasonal and Spatial Variations of Coastal Water Quality Using Multivariate Statistical Techniques
title_full_unstemmed	Assessment of Seasonal and Spatial Variations of Coastal Water Quality Using Multivariate Statistical Techniques
title_sort	assessment of seasonal and spatial variations of coastal water quality using multivariate statistical techniques
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/d6f9fc45da194d22a5c8576de335b26f
work_keys_str_mv	AT mohamadalkhalidi assessmentofseasonalandspatialvariationsofcoastalwaterqualityusingmultivariatestatisticaltechniques AT abdalrahmanalsulaili assessmentofseasonalandspatialvariationsofcoastalwaterqualityusingmultivariatestatisticaltechniques AT badreyahalmarshed assessmentofseasonalandspatialvariationsofcoastalwaterqualityusingmultivariatestatisticaltechniques AT majedbouresly assessmentofseasonalandspatialvariationsofcoastalwaterqualityusingmultivariatestatisticaltechniques AT sarahalshawish assessmentofseasonalandspatialvariationsofcoastalwaterqualityusingmultivariatestatisticaltechniques
_version_	1718411647937150976

Assessment of Seasonal and Spatial Variations of Coastal Water Quality Using Multivariate Statistical Techniques

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