Authors:
Mutyaba, Joseph,Ngubiri John,Obubu Peter And Begumana,John,Uganda |
Abstract:
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
www.ijaeb.org 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 |
