A multivariate analysis of water quality in Lake Naivasha, Kenya

被引:16
|
作者
Ndungu, Jane [1 ,2 ,3 ]
Augustijn, Denie C. M. [1 ]
Hulscher, Suzanne J. M. H. [1 ]
Fulanda, Bernard [4 ]
Kitaka, Nzula [2 ]
Mathooko, Jude M. [2 ]
机构
[1] Univ Twente, NL-7500 AE Enschede, Netherlands
[2] Egerton Univ, Njoro, Kenya
[3] Kenya Marine & Fisheries Res Inst, Mombasa, Kenya
[4] Pwani Univ, Kilifi, Kenya
关键词
cluster analysis; physico-chemical parameters; pollution; principal component analysis; RIFT-VALLEY LAKES; STATISTICAL TECHNIQUES; HEAVY-METALS; SPATIOTEMPORAL VARIATIONS; PRINCIPAL COMPONENT; TEMPORAL VARIATIONS; RIVER-BASIN; COMMUNITY; CHEMISTRY; NUTRIENTS;
D O I
10.1071/MF14031
中图分类号
S9 [水产、渔业];
学科分类号
0908 ;
摘要
Water quality information in aquatic ecosystems is crucial in setting up guidelines for resource management. This study explores the water quality status and pollution sources in Lake Naivasha, Kenya. Analysis of water quality parameters at seven sampling sites was carried out from water samples collected weekly from January to June and biweekly from July to November in 2011. Principal component analysis (PCA) and cluster analysis (CA) were used to analyse the dataset. Principal component analysis showed that four principal components (PCA-1 to PCA-4) explained 94.2% of the water quality variability. PCA-1 and PCA-2 bi-plot suggested that turbidity in the lake correlated directly to nutrients and iron with close association with the sampling site close to the mouth of Malewa River. Three distinct clusters were discerned from the CA analysis: Crescent Lake, a more or less isolated crater lake, the northern region of the lake, and the main lake. The pollution threat in Lake Naivasha includes agricultural and domestic sources. This study provides a valuable dataset on the current water quality status of Lake Naivasha, which is useful for formulating effective management strategies to safeguard ecosystem services and secure the livelihoods of the riparian communities around Lake Naivasha, Kenya.
引用
收藏
页码:177 / 186
页数:10
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