Spatial aspects of surface water quality in the Jakara Basin, Nigeria using chemometric analysis

Mustapha, Adamu; Aris, Ahmad Zaharin

doi:10.1080/10934529.2012.673305

Cited by 34 publications

(22 citation statements)

References 10 publications

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“…In addition, rapid urbanization is altering the patterns of consumption, causing the severe misuse of water resources. Rivers, streams, and their tributaries passing through cities receive many contaminants released from industrial, domestic/sewage, and agricultural effluents and thereby accelerate the degradation of fresh water ecosystem mainly by eutrophication (Qadir et al 2008;Zhang et al 2011;Mustapha and Aris 2012).…”

Section: Introductionmentioning

confidence: 99%

Spatial variation of water quality parameters in a mangrove estuary

Fatema

Maznah

Isa

2014

Int. J. Environ. Sci. Technol.

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Spatial variations of the water quality parameters of the Merbok estuary were interpreted by multivariate statistical techniques, such as cluster analysis (CA), principal component analysis (PCA), and factor analysis (FA). Data from January to December 2011 were collected to monitor 13 parameters at six sampling stations along the river stretch (two stations at each river section: upstream, midstream, and downstream). Cluster analysis results revealed two different groups between the sampling stations, reflecting different physicochemical properties and pollution levels in the study area. Factor analysis was used for the parameters of the surface and bottom water quality, yielding four factors that were responsible for 72.93 and 68.90 % of the total variance of data sets. PCA also found conductivity, salinity, dissolved oxygen, chlorophyll a, and NO 3 -to be the most important parameters contributing to the fluctuations of surface water and bottom water quality in the Merbok estuary. This study presents the usefulness of multivariate statistical techniques for assessing water quality data sets and for understanding spatial variations in water quality parameters to effectively manage water quality in estuaries.

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Section: Introductionmentioning

confidence: 99%

Spatial variation of water quality parameters in a mangrove estuary

Fatema

Maznah

Isa

2014

Int. J. Environ. Sci. Technol.

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“…Numerous applications concerning the identification of possible factors/sources that influence water system (Narany et al 2014;Kumari and Tripathi 2014;Bu et al 2014), data reduction (Cieszynska et al 2012;Mustapha et al 2013;Sharma et al 2013;Farmaki et al 2012), grouping and discrimination of variables (Juahir et al 2011;Mustapha and Aris 2012;Gatica et al 2012), and spatial and temporal variations (Bu et al 2010;Kannel et al 2011;Wang et al 2012;Li et al 2014) have been published. Ajorlo et al (2013) investigated the applicability of multivariate statistical techniques for the assessment of seasonal variations in the surface water quality of tropical pastures.…”

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confidence: 99%

Use of multivariate statistical techniques for the evaluation of temporal and spatial variations in water quality of the Kaduna River, Nigeria

Ogwueleka

2015

Environ Monit Assess

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Multivariate statistical techniques, such as cluster analysis (CA) and principal component analysis/factor analysis (PCA/FA), were used to investigate the temporal and spatial variations and to interpret large and complex water quality data sets collected from the Kaduna River. Kaduna River is the main tributary of Niger River in Nigeria and represents the common situation of most natural rivers including spatial patterns of pollutants. The water samples were collected monthly for 5 years (2008-2012) from eight sampling stations located along the river. In all samples, 17 parameters of water quality were determined: total dissolved solids (TDS), pH, Thard, dissolved oxygen (DO), 5-day biochemical oxygen demand (BOD5), chemical oxygen demand (COD), NH4-N, Cl, SO4, Ca, Mg, total coliform (TColi), turbidity, electrical conductivity (EC), HCO3 (-), NO3 (-), and temperature (T). Hierarchical CA grouped 12 months into two seasons (dry and wet seasons) and classified eight sampling stations into two groups (low- and high-pollution regions) based on seasonal differences and different levels of pollution, respectively. PCA/FA for each group formed by CA helped to identify spatiotemporal dynamics of water quality in Kaduna River. CA illustrated that water quality progressively deteriorated from headwater to downstream areas. The results of PCA/FA determined that 78.7 % of the total variance in low pollution region was explained by five factor, that is, natural and organic, mineral, microbial, organic, and nutrient, and 87.6 % of total variance in high pollution region was explained by six factors, that is, microbial, organic, mineral, natural, nutrient, and organic. Varifactors obtained from FA indicated that the parameters responsible for water quality variations are resulted from agricultural runoff, natural pollution, domestic, municipal, and industrial wastewater. Mann-Whitney U test results revealed that TDS, pH, DO, T, EC, TColi, turbidity, total hardness (THard), Mg, Ca, NO3 (-), COD, and BOD were identified as significant variables affecting temporal variation in river water, and TDS, EC, and TColi were identified as significant variables affecting spatial variation. In addition, box-whisker plots facilitated and supported multivariate analysis results. This study illustrates the usefulness of multivariate statistical techniques for classification and processing of large and complex data sets of water quality parameters, identification of latent pollution factors/sources and their spatial-temporal variations, and determination of the corresponding significant parameters in river water quality.

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“…The analysis of water quality status in this research was conducted by comparing the observation results with the standard values [19], [11], [18]. Evaluation of water quality can be conducted with spatial and temporal approach [1][2][3][4][5], [12], [20], [21]. Therefore, the availability of periodic and regular (time series) data monitoring is the success key in performing the water quality evaluation [14][15][16][17], [8], [9].…”

Section: Introductionmentioning

confidence: 99%

“…Therefore, the availability of periodic and regular (time series) data monitoring is the success key in performing the water quality evaluation [14][15][16][17], [8], [9]. In addition to historical data series, the selection of appropriate water quality parameters is also a very important variable in evaluating the quality of water source [18], [20]. Based on this research, it was understood that the mainstay discharge of drinking water of Saguling Reservoir by using the R10 concept as dry (the discharge value is less in one time within 10 years period).…”

Section: Introductionmentioning

confidence: 99%

Alternative Intake Station in Saguling Reservoir for The Needs of Raw Water in Bandung Metropolitan Area

et al. 2018

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Abstract. Bandung Metropolitan Area (BMA) region is the upper watershed of Citarum with an area of ± 2338 km 2 . The status carried by BMA as a National Strategic Area from the perspective of economic encourage the increasing migration flows to BMA. These circumstances lead to an imbalance between supply and demand, in which on the one hand, demand for clean water is increasing. The potency of Saguling Reservoir as an alternative of raw water of BMA region in terms of quantity in this research was determined based on the determination of mainstay discharge. In this study, the intake site selection 11 monitoring posts will be carried out by reviewing the concentration of all parameters in Government Regulation No. 82 Year 2001 on any division of discharge grade using 5-grade Makov Discrete method (very dry, dry, normal, wet and very wet). In addition, the calculation of the value of Water Quality Index (WQI) was done at each monitoring station for each division of discharge grade that has been done. The series of data flow and concentration parameters used in this study start from the year 1999 to 2014. The allocation of raw water discharge calculation for Saguling Reservoir in order to fulfill the needs of raw water in Bandung Metropolitan Area is 46,92m 3 /second (R5 dry for irrigation raw water supply and 29,53 92 m 3 /second (R10 dry for drinking water supply). Based on the assessment of the concentration of measured parameters and determination of Water Quality Index, it can be found that around Muara Ciminyak location is the most qualified location to be used as drinking raw water intake for Bandung Metropolitan Area. Based on this study, it also notes that the determination of the concentration of pollutant parameters needs to be done on the each division of discharge grade occurred.

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Spatial aspects of surface water quality in the Jakara Basin, Nigeria using chemometric analysis

Cited by 34 publications

References 10 publications

Spatial variation of water quality parameters in a mangrove estuary

Spatial variation of water quality parameters in a mangrove estuary

Use of multivariate statistical techniques for the evaluation of temporal and spatial variations in water quality of the Kaduna River, Nigeria

Alternative Intake Station in Saguling Reservoir for The Needs of Raw Water in Bandung Metropolitan Area

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