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
+ Author Affiliations
- Author Affiliations
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
Marine and Freshwater Research 66(2) 177-186 https://doi.org/10.1071/MF14031
Submitted: 6 November 2013 Accepted: 9 May 2014 Published: 31 October 2014
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.
References
Alberto, W. D., María del Pilar, D., María Valeria, A., Fabiana, P. S., Cecilia, H. A., and María de los Ángeles, B. (2001). Pattern recognition techniques for the evaluation of spatial and temporal variations in water quality. A case study: Suquía River Basin (Córdoba–Argentina). Water Research 35, 2881–2894.| Pattern recognition techniques for the evaluation of spatial and temporal variations in water quality. A case study: Suquía River Basin (Córdoba–Argentina).Crossref | GoogleScholarGoogle Scholar | 1:STN:280:DC%2BD38%2FisV2qtg%3D%3D&md5=6a8188ff3ce7ca18323351d06046a81dCAS | 11471688PubMed |
APHA (2005). ‘Standard Methods, 21st Edition.’ (American Public Health Association: Washington, DC.)
Åse, L.-E. (1987). A note on the water budget of Lake Naivasha, Kenya. Especially the role of Salvinia molesta Mitch and Cyperus papyrus L. Geografiska Annaler. Series A. Physical Geography 69, 415–429.
| A note on the water budget of Lake Naivasha, Kenya. Especially the role of Salvinia molesta Mitch and Cyperus papyrus L.Crossref | GoogleScholarGoogle Scholar |
Ayenew, T. (2005). Major ions composition of the groundwater and surface water systems and their geological and geochemical controls in the Ethiopian volcanic terrain. SINET: Ethiopian Journal of Science 28, 171–188.
Ballot, A., Kotut, K., Novelo, E., and Krienitz, L. (2009). Changes of phytoplankton communities in Lakes Naivasha and Oloidien, examples of degradation and salinization of lakes in the Kenyan Rift Valley. Hydrobiologia 632, 359–363.
| Changes of phytoplankton communities in Lakes Naivasha and Oloidien, examples of degradation and salinization of lakes in the Kenyan Rift Valley.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD1MXovVSgtLY%3D&md5=2e12459bc11a6fe0f2b3c836e07ea7dfCAS |
Becht, R., and Harper, D. M. (2002). Towards an understanding of human impact upon the hydrology of Lake Naivasha, Kenya. Hydrobiologia 488, 1–11.
| Towards an understanding of human impact upon the hydrology of Lake Naivasha, Kenya.Crossref | GoogleScholarGoogle Scholar |
Chernet, T., Travi, Y., and Valles, V. (2001). Mechanism of degradation of the quality of natural water in the lakes region of the Ethiopian rift valley. Water Research 35, 2819–2832.
| Mechanism of degradation of the quality of natural water in the lakes region of the Ethiopian rift valley.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD3MXkvVWmtrs%3D&md5=e2ff7ee86540f47ac0011eb692c30f70CAS | 11471682PubMed |
Childress, R. B., Bennun, L. A., and Harper, D. M. (2002). Population changes in sympatric great and long-tailed cormorants (Phalacrocorax carbo and P. africanus): the effects of niche overlap or environmental change? Hydrobiologia 488, 163–170.
| Population changes in sympatric great and long-tailed cormorants (Phalacrocorax carbo and P. africanus): the effects of niche overlap or environmental change?Crossref | GoogleScholarGoogle Scholar |
Costantini, M. L., Rossi, L., Scialanca, F., Nascetti, G., Rossi, D., and Sabetta, L. (2007). Association of riparian features and water chemistry with reed litter breakdown in a volcanic lake (Lake Vico, Italy). Aquatic Sciences 69, 503–510.
| Association of riparian features and water chemistry with reed litter breakdown in a volcanic lake (Lake Vico, Italy).Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD1cXhtlarsbc%3D&md5=2ca7f2e1895c0b4e4b01269998870f00CAS |
Delgado, J., Nieto, J., and Boski, T. (2010). Analysis of the spatial variation of heavy metals in the Guadiana Estuary sediments (SW Iberian Peninsula) based on GIS-mapping techniques. Estuarine, Coastal and Shelf Science 88, 71–83.
| Analysis of the spatial variation of heavy metals in the Guadiana Estuary sediments (SW Iberian Peninsula) based on GIS-mapping techniques.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC3cXmtFKltrc%3D&md5=a21e68c10e5d5cd8fb9488a8eee23d1dCAS |
Gaudet, J. J. (1979). Seasonal changes in nutrients in a tropical swamp: North Swamp, Lake Naivasha, Kenya. Journal of Ecology 67, 953–981.
| Seasonal changes in nutrients in a tropical swamp: North Swamp, Lake Naivasha, Kenya.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DyaL3cXhs1ejsbg%3D&md5=f9923d510b5b4cb346ed9a1a2cccdc2eCAS |
Gaudet, J. J., and Melack, J. M. (1981). Major ion chemistry in a tropical African lake basin. Freshwater Biology 11, 309–333.
| Major ion chemistry in a tropical African lake basin.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DyaL3MXltlyhsrk%3D&md5=8b6b2f88ff8eb613ce8e8462a39f8820CAS |
Grochowska, J., and Tandyrak, R. (2009). The influence of the use of land on the content of calcium, magnesium, iron and manganese in water, exemplified in three lakes in the Olsztyn vicinity. Limnological Review 9, 9–16.
HACH (2005). ‘DR 2800 User Manual.’ 1st edition. (HACH Chemical Company: Loveland, Colorado.)
Harper, D. (1992). The ecological relationships of aquatic plants at Lake Naivasha, Kenya. Hydrobiologia 232, 65–71.
| The ecological relationships of aquatic plants at Lake Naivasha, Kenya.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DyaK38XkvFKrtrk%3D&md5=0d0fe15460abcc104e2445399def760aCAS |
Hubble, D. S., and Harper, D. M. (2001). Impact of light regimen and self-shading by algal cells on primary productivity in the water column of a shallow tropical lake (Lake Naivasha, Kenya). Lakes and Reservoirs: Research and Management 6, 143–150.
| Impact of light regimen and self-shading by algal cells on primary productivity in the water column of a shallow tropical lake (Lake Naivasha, Kenya).Crossref | GoogleScholarGoogle Scholar |
Kazi, T., Arain, M., Jamali, M., Jalbani, N., Afridi, H., Sarfraz, R., Baig, J., and Shah, A. Q. (2009). Assessment of water quality of polluted lake using multivariate statistical techniques: a case study. Ecotoxicology and Environmental Safety 72, 301–309.
| Assessment of water quality of polluted lake using multivariate statistical techniques: a case study.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD1cXhtlaqtbnF&md5=c5997a82d7fb0443c8e555ab2c89bdcdCAS | 18423587PubMed |
Kilham, P. (1990). Mechanisms controlling the chemical composition of lakes and rivers: data from Africa. Limnology and Oceanography 35, 80–83.
| Mechanisms controlling the chemical composition of lakes and rivers: data from Africa.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DyaK3MXitFekt7c%3D&md5=d39d28818a4a875421c8f55e5f63936cCAS |
Kitaka, N., Harper, D. M., and Mavuti, K. M. (2002). Phosphorus inputs to Lake Naivasha, Kenya, from its catchment and the trophic state of the lake. Hydrobiologia 488, 73–80.
| Phosphorus inputs to Lake Naivasha, Kenya, from its catchment and the trophic state of the lake.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD3sXivFymsr0%3D&md5=79f349c3cdb535a78fb3bc573381b86eCAS |
Kundu, R., Aura, C. M., Muchiri, M., Njiru, J. M., and Ojuok, J. E. (2010). Difficulties of fishing at Lake Naivasha, Kenya: is community participation in management the solution? Lakes and Reservoirs: Research and Management 15, 15–23.
| Difficulties of fishing at Lake Naivasha, Kenya: is community participation in management the solution?Crossref | GoogleScholarGoogle Scholar |
Lee, C. S.-l., Li, X., Shi, W., Cheung, S. C.-n., and Thornton, I. (2006). Metal contamination in urban, suburban, and country park soils of Hong Kong: a study based on GIS and multivariate statistics. The Science of the Total Environment 356, 45–61.
| Metal contamination in urban, suburban, and country park soils of Hong Kong: a study based on GIS and multivariate statistics.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD28Xhs1yqur8%3D&md5=cc8c5557249f6d1b53b9530cd507f231CAS |
Lake Naivasha Riparian Association (LNRA) (1999). ‘Lake Naivasha Management Plan.’ (LNRA: Naivasha, Kenya.)
Lung’Ayia, H., M’Harzi, A., Tackx, M., Gichuki, J., and Symoens, J. (2000). Phytoplankton community structure and environment in the Kenyan waters of Lake Victoria. Freshwater Biology 43, 529–543.
| Phytoplankton community structure and environment in the Kenyan waters of Lake Victoria.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD3cXjsFCgtLs%3D&md5=79690aa82cfee922df3ca2cf653a3fc0CAS |
Machado, L., Magnusson, M., Paul, N. A., de Nys, R., and Tomkins, N. (2014). Effects of marine and freshwater macroalgae on in vitro total gas and methane production. PLoS ONE 9, e85289.
| Effects of marine and freshwater macroalgae on in vitro total gas and methane production.Crossref | GoogleScholarGoogle Scholar | 24465524PubMed |
Magyar, N., Hatvani, I. G., Székely, I. K., Herzig, A., Dinka, M., and Kovács, J. (2013). Application of multivariate statistical methods in determining spatial changes in water quality in the Austrian part of Neusiedler See. Ecological Engineering 55, 82–92.
| Application of multivariate statistical methods in determining spatial changes in water quality in the Austrian part of Neusiedler See.Crossref | GoogleScholarGoogle Scholar |
Meglen, R. R. (1992). Examining large databases: a chemometric approach using principal component analysis. Marine Chemistry 39, 217–237.
| Examining large databases: a chemometric approach using principal component analysis.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DyaK38Xmtlejurk%3D&md5=c9ab11aebedf4c7e6f085c8704663b20CAS |
Mellinger, M. (1987). Multivariate data analysis: its methods. Chemometrics and Intelligent Laboratory Systems 2, 29–36.
| Multivariate data analysis: its methods.Crossref | GoogleScholarGoogle Scholar |
Mergeay, J. (2004). Two hundred years of a diverse Daphnia community in Lake Naivasha (Kenya): effects of natural and human-induced environmental changes. Freshwater Biology 49, 998–1013.
| Two hundred years of a diverse Daphnia community in Lake Naivasha (Kenya): effects of natural and human-induced environmental changes.Crossref | GoogleScholarGoogle Scholar |
Mugidde, R., Gichuki, J., Rutagemwa, D., Ndawula, L., and Matovu, X. (2005). Status of water quality an its implication on the fishery production. In ‘The State of the Fisheries Resources of Lake Victoria and Their Management. Proceedings of the Regional Stakeholders’ Conference’. (Ed. L.V.F.O. Secretariat.) pp. 106–112. (Jinja, Uganda.)
Ndungu, J., Augustijn, D. C. M., Hulscher, S. J. M. H., Kitaka, N., and Mathooko, J. (2013a). Spatio-temporal variations in the trophic status of Lake Naivasha, Kenya. Lakes and Reservoirs: Research and Management 18, 317–328.
| Spatio-temporal variations in the trophic status of Lake Naivasha, Kenya.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC3sXhvFegtLnO&md5=29bcb18bb23e9b7c3fc4408b26513f8cCAS |
Ndungu, J., Monger, B. C., Augustijn, D. C. M., Hulscher, S. J. M. H., Kitaka, N., and Mathooko, J. M. (2013b). Evaluation of spatio-temporal variations in chlorophyll-a in Lake Naivasha, Kenya: remote-sensing approach. International Journal of Remote Sensing 34, 8142–8155.
| Evaluation of spatio-temporal variations in chlorophyll-a in Lake Naivasha, Kenya: remote-sensing approach.Crossref | GoogleScholarGoogle Scholar |
Ochieng, E., Lalah, J., and Wandiga, S. (2007). Analysis of heavy metals in water and surface sediment in five rift valley lakes in Kenya for assessment of recent increase in anthropogenic activities. Bulletin of Environmental Contamination and Toxicology 79, 570–576.
| Analysis of heavy metals in water and surface sediment in five rift valley lakes in Kenya for assessment of recent increase in anthropogenic activities.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD2sXhtlCntb%2FK&md5=e75af443bffc562b526c78122c643b7aCAS | 17943221PubMed |
Pearce, A. R., Rizzo, D. M., Watzin, M. C., and Druschel, G. K. (2013). Unraveling associations between cyanobacteria blooms and in-lake environmental conditions in Missisquoi Bay, Lake Champlain, USA, using a modified self-organizing map. Environmental Science & Technology 47, 14267–14274.
| Unraveling associations between cyanobacteria blooms and in-lake environmental conditions in Missisquoi Bay, Lake Champlain, USA, using a modified self-organizing map.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC3sXhvVSntbvE&md5=f77b6b1b887d41bfca1b580776cc5ae5CAS |
Prepas, E. E., Planas, D., Gibson, J., Vitt, D., Prowse, T., Dinsmore, W., Halsey, L., McEachern, P., Paquet, S., and Scrimgeour, G. (2001). Landscape variables influencing nutrients and phytoplankton communities in Boreal Plain lakes of northern Alberta: a comparison of wetland-and upland-dominated catchments. Canadian Journal of Fisheries and Aquatic Sciences 58, 1286–1299.
| Landscape variables influencing nutrients and phytoplankton communities in Boreal Plain lakes of northern Alberta: a comparison of wetland-and upland-dominated catchments.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD3MXmsV2ksLk%3D&md5=547fcae39259d3692e5e5610de6da789CAS |
Reghunath, R., Murthy, T. R. S., and Raghavan, B. R. (2002). The utility of multivariate statistical techniques in hydrogeochemical studies: an example from Karnataka, India. Water Research 36, 2437–2442.
| The utility of multivariate statistical techniques in hydrogeochemical studies: an example from Karnataka, India.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD38XktFaqtr8%3D&md5=e2d7acc09b5cc0a76ed3721f85076123CAS | 12153009PubMed |
Sheela, A.M., Letha, J., Joseph, S., Chacko, M., Sanal kumar, S. P., and Thomas, J. (2012). Water quality assessment of a tropical coastal lake system using multivariate cluster, principal component and factor analysis. Lakes and Reservoirs: Research and Management 17, 143–159.
| Water quality assessment of a tropical coastal lake system using multivariate cluster, principal component and factor analysis.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC38Xht1Wlu7fE&md5=94db051db63b8109e944413c4edce344CAS |
Shrestha, S., and Kazama, F. (2007). Assessment of surface water quality using multivariate statistical techniques: a case study of the Fuji river basin, Japan. Environmental Modelling & Software 22, 464–475.
| Assessment of surface water quality using multivariate statistical techniques: a case study of the Fuji river basin, Japan.Crossref | GoogleScholarGoogle Scholar |
Simeonov, V., Simeonova, P., Tsakovski, S., and Lovchinov, V. (2010). Lake water monitoring data assessment by multivariate statistics. Journal of Water Resource and Protection 2, 353–361.
| Lake water monitoring data assessment by multivariate statistics.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC3cXovV2rtrw%3D&md5=a396ec9f00cf9343c1628b17cef1e9a9CAS |
Singh, K. P., Malik, A., Mohan, D., and Sinha, S. (2004). Multivariate statistical techniques for the evaluation of spatial and temporal variations in water quality of Gomti River (India): a case study. Water Research 38, 3980–3992.
| Multivariate statistical techniques for the evaluation of spatial and temporal variations in water quality of Gomti River (India): a case study.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD2cXns1eqt7o%3D&md5=130f5290f7bbc1677f1bbf0b79495ab3CAS | 15380988PubMed |
Stoof-Leichsenring, K., Junginger, A., Olaka, L., Tiedemann, R., and Trauth, M. (2011). Environmental variability in Lake Naivasha, Kenya, over the last two centuries. Journal of Paleolimnology 45, 353–367.
| Environmental variability in Lake Naivasha, Kenya, over the last two centuries.Crossref | GoogleScholarGoogle Scholar |
Tariq, S. R., Shah, M. H., Shaheen, N., Khalique, A., Manzoor, S., and Jaffar, M. (2005). Multivariate analysis of selected metals in tannery effluents and related soil. Journal of Hazardous Materials 122, 17–22.
| Multivariate analysis of selected metals in tannery effluents and related soil.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD2MXkvFWhsrc%3D&md5=ed2ab1eff763c8df0110394919d35d7cCAS | 15943925PubMed |
Vega, M., Pardo, R., Barrado, E., and Debán, L. (1998). Assessment of seasonal and polluting effects on the quality of river water by exploratory data analysis. Water Research 32, 3581–3592.
| Assessment of seasonal and polluting effects on the quality of river water by exploratory data analysis.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DyaK1cXnslGjtLY%3D&md5=5e77fd444f6b5b4572d25b034f551c09CAS |
Wang, Y.-B., Liu, C.-W., Liao, P.-Y., and Lee, J.-J. (2014). Spatial pattern assessment of river water quality: implications of reducing the number of monitoring stations and chemical parameters. Environmental Monitoring and Assessment 186, 1781–1792.
| Spatial pattern assessment of river water quality: implications of reducing the number of monitoring stations and chemical parameters.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC3sXhvVaitL7E&md5=19dc1c274a3901da5b7c48586cebdeb4CAS | 24242081PubMed |
Ward, J. H. (1963). Hierarchical Grouping to optimize an objective function. Journal of American Statistical Association 58, 236–244.
Wenchuan, Q., Dickman, M., and Sumin, W. (2001). Multivariate analysis of heavy metal and nutrient concentrations in sediments of Taihu Lake, China. Hydrobiologia 450, 83–89.
| Multivariate analysis of heavy metal and nutrient concentrations in sediments of Taihu Lake, China.Crossref | GoogleScholarGoogle Scholar |
Wenning, R. J., and Erickson, G. A. (1994). Interpretation and analysis of complex environmental data using chemometric methods. TrAC Trends in Analytical Chemistry 13, 446–457.
| Interpretation and analysis of complex environmental data using chemometric methods.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DyaK2MXitVCrtb8%3D&md5=8d15607ea04300215f8eff8911229b79CAS |
Wetzel, R.G. (2001). ‘Limnology: lake and river ecosystems.’ (Access Online via Elsevier.)
Zeng, T., and Arnold, W. A. (2014). Clustering chlorine reactivity of haloacetic acid precursors in inland lakes. Environmental Science & Technology 48, 139–148.
| Clustering chlorine reactivity of haloacetic acid precursors in inland lakes.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC3sXhvV2mt7rE&md5=5e3df834a6db7594c4a9c6c9a37f3fe6CAS |
Zinabu, G., and Pearce, N. J. (2003). Concentrations of heavy metals and related trace elements in some Ethiopian rift-valley lakes and their in-flows. Hydrobiologia 492, 171–178.
| Concentrations of heavy metals and related trace elements in some Ethiopian rift-valley lakes and their in-flows.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD3sXlsFKrtbs%3D&md5=14d59d7fdfd9166c8bb489cf253496cfCAS |
