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ISSN : 2456-8643


Mutyaba, Joseph,Ngubiri John,Obubu Peter And Begumana,John,Uganda

Lake Victoria being a source of livelihood for millions of people in the great lakes region ensuing from the supply of water, fish, ecosystem management transport and recreation, its water has to be monitored both in quantity and quality. Its quality is negatively impacted by anthropogenic factors in the catchment area such as high rates of deforestation and wetland degradation due to agricultural expansion, repository for human, agricultural and industrial waste. The quality of the water is meant to be monitored at least once every three months by sampling water pollution estimates at several monitoring stations within the lake. For the years 2014 - 2017, this had not been the situation in Uganda since measurements were a year apart. Hence a major technical challenge facing management is the timely quantification of the lake's nutrient load. The current approach is limited in geographical extent and temporal resolution as well as costly in both time and other resources for the entire Eastern African region. To address the timely data gap challenge, the research proposed the benefits of augmenting the current approach with Remote Sensing and GIS to monitor the catchment area and the lake ecosystem to deliver timely and cost effective information to management. Through regression analysis, optical remote sensing imagery and field data from off shore water monitoring stations were correlated and used to study spatial-temporal dynamics of water quality. Processes in the catchment area, such as industrialization, population growth and land use change, were considered as explanatory variables to changes in water quality. The resultant regression models of water quality were key in understanding the past spatial temporal trends in water quality and also give insights into what is likely to happen in the future. Parameters for which models were designed are transparency and chlorophyll-a. Transparency exhibited R2 of 0.67 at design and R2 of 0.92 at validation stages. Modelled results indicated that for the entire lake transparency was improving since 1995 to 2015. Chlorophyll-a on the other hand, had ups and downs with the downward (deteriorating) trend being more significant after International Journal of Agriculture, Environment and Bioresearch Vol. 3, No. 05; 2018 ISSN: 2456-8643 Page 122 2003. Taking a close look at specific locations up to 40 Km within the lake from the shoreline, the trend was more of a worsening nature as opposed to entire lake. Simulations of prospective events revealed that concentrations of chlorophyll-a are expected to continue to rise at a rate greater than 0.22 gL-1 per year that was observed between 2003 and 2015 giving averages of 30 gL-1 by year 2023. The hyperbolic rise is likely to be accompanied with lower fish catches and rise in water borne diseases. The quality of imagery remained the single most important factor determining usability of imagery for water quality

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