Browsing by Author "Maina, Caroline W."

Now showing 1 - 3 of 3

Bathymetric survey of lake Naivasha and its satellite lake Oloiden in Kenya; using acoustic profiling system
(wileyonlinelibrary.com/journal/lre, 2018-10-23) Raude, James M.; Maina, Caroline W.; Sang, Joseph K.; Mutua, Benedict M.
Lakes and reservoirs play important roles as freshwater sources for domestic, indus-trial, agricultural, fisheries and recreational purposes. However, for the lakes to be sustainably exploited, there is need to understand their bathymetric characteristics by conducting bathymetric surveys. This aids in generating information that can guide lakes stakeholders and managers in establishing the volume of available water. It is recommended, therefore, that bathymetric surveys be conducted at ten-year intervals. Such continuous bathymetric information is lacking in many lakes, espe-cially in developing countries. One example is Lake Naivasha in Kenya, which is largely exploited for various socio-economic purposes. Despite its importance, its most recent published bathymetric data were collected in 1991. The goal of the pre-sent study, therefore, was to conduct a bathymetric survey of Lake Naivasha and its satellite Lake Oloiden, using an Acoustic Profiling System (APS) to generate Depth–Area–Volume relationships for the lakes. The survey results indicate the in the year 2016 mean depth, volume and surface area of the lake were 4.68 m, 722 × 106 m3and 154.17 × 106 m2, respectively. Because of limited information from the 1991 sur-vey, the 2016 survey results were comparable with those of 1983. The difference in the lakes mean, and maximum depth for the 1983 and 2016 survey was less by 0.23 and 2 m, respectively. This could be an indicator the lake is being affected by anthro-pogenic activities or environmental changes. The established Depth–Area–Volume relationships are crucial since they provide invaluable information to lake and water resources managers for making informed decisions regarding management of the lake’s water resources.
Geochronological and spatial distribution of heavy metal contamination in sediment from lake Naivasha, Kenya
(Taylor & Francis, 2019-01-02) Maina, Caroline W.; Sang, Joseph K.; Raud, James M.; Mutua, Benedict M.
Sediment cores hold large information on the history of human interactions with lakes and surrounding environments. Hence, this study investigated the geochronological and heavy metals characteristics of sediment from Lake Naivasha, Kenya. Geochronological characteristics were established from sediment cores, using 210Pb and 137Cs. On the other hand, heavy metals; Al, As, Cr, Cu, Fe, Mn, Ni, Pb, and Zn were analyzed using Inductively Coupled Plasma - Optical Emission Spectrometer (ICP – OES). Their probable sources were predicted using Pearson’s correlation and Principal Component Analysis (PCA) while heavy metal contamination levels were assessed using geoaccumulation Index (Igeo), Contamination Factor (CF) and Enrichment Factor (EF) pollution indices. Results showed that the cores were about 140 years old with an estimated average mass sedimentation rate of 0.32 g/cm2/yr. Vertical fluctuations of heavy metal contamination were observed along the sediment cores with high values recorded near the surface. Further, PCA and pollution indices showed that Al, Cr, Cu, Ni, and Pb were from natural sources while, Zn, Mn, Fe, and As, (in order of contamination levels), were both from natural and anthropogenic sources. Therefore, this study showed the geochronological trends of sedimentation and impacts of human activities on Lake Naivasha.
Simulation of constructed wetland treatment in wastewater polishing using PREWet model Publ
(Routledge, 2012-03-01) Oduor, Steve O.; Maina, Caroline W.; Mutua, Benedict M.
To minimize the negative impact of wastewater when disposed into water bodies, proper treatment before its disposal is vital. Different wastewater treatment scenarios can be tested using predictive and analytical models. A screening-level, analytical model known as the PREWet model was calibrated and validated. The model assumes steady-state conditions and one-dimensional longitudinally varying concentration. The model was calibrated on a pilot-scale wetland and used to predict treatment through a constructed wetland. Performance of the calibrated model was statistically evaluated for its predictive ability by simulating the wastewater treatment through a constructed wetland. Different constituents were modelled which include: total phosphorous (TP), total coliform (TC), biochemical oxygen demand (BOD) and total suspended solids (TSS). The model coefficients were estimated using field and laboratory studies. Sensitivity analysis indicated that detention time of wastewater in constructed wetland was the most sensitive parameter in the PREWet model. Coefficient of determination and Nash–Sutcliffe coefficient were used to compare the observed and simulated results. The Nash–Sutcliffe coefficient of model efficiency for TP, TC, BOD and TSS was 0.97, 0.96, 0.97 and 0.77, respectively. The PREWet model was found to be an effective tool in simulating wastewater treatment through constructed wetlands.