A multivariate analysis of water quality in Lake Naivasha, Kenya Jane Ndungu A,B,C,E , Denie C. M. Augustijn A , Suzanne J. M. H. Hulscher A , Bernard Fulanda D , Nzula Kitaka B and Jude M. Mathooko B A University of Twente, PO BOX 217, 7500 AE Enschede, The Netherlands. B Egerton University, PO Box 536, Njoro, Kenya. C Kenya Marine and Fisheries Research Institute, PO Box 81651-80100, Mombasa, Kenya. D Pwani University, PO BOX 195-80108, Kilifi, Kenya. E Corresponding author. Email: jandungu@gmail.com Abstract. 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. Additional keywords: cluster analysis, physico-chemical parameters, pollution, principal component analysis. Received 6 November 2013, accepted 9 May 2014, published online 31 October 2014 Introduction Lakes and reservoirs are important sources of surface water and livelihood for many rural and urban communities. However, declining water quality in freshwater lakes and reservoirs is an increasing problem that threatens the ecosystem services to the riparian communities, especially in developing countries. One of the major causes of the decline in the quality of water is nutrient enrichment; mainly phosphorus and nitrogen. As a result, massive algal blooms occur, causing a shift from clear to a turbid state in shallow lakes and reservoirs (Lung’Ayia et al. 2000; Kitaka et al. 2002; Mugidde et al. 2005). Consequently, significant changes in the biological structure of the lakes and reservoirs occur which are a major threat to the sources of livelihood of the riparian fisher folks (Harper 1992). Lake Naivasha is an important inland freshwater lake, especially within the Rift Valley because of the salty nature of the majority of the other water resources in the area. The lake harbours unique faunal and floral biodiversity, which led to it being declared a wetland of international importance in 1994 under the Ramsar convention (Lake Naivasha Riparian Association (LNRA) 1999). The lake is a source of liveli- hood and supports many socioeconomic activities such as a multimillion horticultural industry, tourism, fishing and domestic water sources (Becht and Harper 2002; Kundu et al. 2010). Though still artisanal, the fishing industry of the lake employs over 1000 fishermen and provides a source of protein for people living in the nearby towns (Kundu et al. 2010). However, myriad environmental perturbations in Lake Naivasha’s ecosystem have transformed the lake from clear to a muddy eutrophic turbid state, which has resulted in a decline in ecological quality, impacting heavily on fish populations and tourism (Hubble and Harper 2001; Mergeay 2004). Sustainable lake management calls for reliable data and infor- mation on water quality. However, the quality varies both temporally and spatially. The main causes of the variation include anthropogenic activities, seasonal fluctuations in inflow of nutrients and other substances, and natural variations attributed to biogeochemical processes. Therefore, the need for continuous assessment of water quality is inevitable and calls for continuous monitoring of the lake. This notwithstanding, monitoring programs often result in huge and complex data matrices consisting of many physico-chemical parameters, thus calling for multivariate approaches to the analysis and interpretation of the data. CSIRO PUBLISHING Marine and Freshwater Research http://dx.doi.org/10.1071/MF14031 Journal compilation Ó CSIRO 2014 www.publish.csiro.au/journals/mfr