Spatial and temporal variation in water quality between the Lakes Naivasha and Oloiden in the Kenyan Rift Valley.

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Date
2023-07-06
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The Eldoret National Polytechnic
Abstract
Lakes Naivasha and Oloiden merged due to the rise in the water level in the former. A studywas conducted for one year in an endeavor to investigate spatial temporal variation of selectphysical and chemical parameters between the Lakes Naivasha and Oloiden. The waterquality was sampled monthly in each site in Lake Oloiden and Lake Naivasha by measuringsome water quality variables insitu and collection of water samples for laboratory analysis.The water depth and the secchi depth were measured in each site while some physicalchemical parameters were measured insitu using a YSI Multiparameter probe. Nutrients(phosphates and nitrates), total suspended solids, chlorophyll-a analysis was done in thelaboratory using the standard methods. The lakes depth and the secchi depth have increasedin both lakes. The phosphates varied site-wise and chlorophyll-a concentration has decreasedpost water level rise. Lake Oloiden’s temperature, pH, conductivity and salinity were higheras compared to the Lake Naivasha’s. The principal component analysis showed 4 principalcomponents (PCA-1 to PCA-4) which accounted for 94.7% of the variation. PCA-1 andPCA-2 biplots suggested: a link between chlorophyll-a to orthophosphates, nitrates,phosphates (Oloiden ST1 and ST2). Oseria and Korongo sites were closely associated withthe secchi depth, lake depth, pH and salinity. 4 distinct clusters were noted: Crescent,Malewa, midsection (Midlake, Korongo, Oseria) and Lake Oloiden (Oloiden ST1 and ST2).The increase in the water level and the merging of saline and fresh water ecosystem led to thecreation of a salinity gradient; an area where abiotic and biotic processes are non-linear.There was spatial temporal variation in water quality among the sites. Analysis of variance inwater quality in the Lake Naivasha and Lake Oloiden provided an insight about water qualitystatus: associations between water quality variables and sites may aid in effectivemanagement decisions
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