Abstract:
The Akosombo hydroelectric dam accounts for over a third of the electricity generation
in Ghana. The amount of electricity produced depends on the amount of water in the
dam. Therefore, studying the tail behaviour of the dam’s water level is crucial given
the country’s rising demand for energy and the strain that this increased demand
places on the dam. For engineers and coastal development planners, determining the
likelihood that the water level of the Akosombo dam may rise due to heavy rains is
crucial as it can lead to flooding. In this study, Extreme Value Theory was to model
the tail behaviour of the water levels of the Akosombo dam. Truncation which is
introduced naturally by the height of the dam was incorporated. The possibility of
exceeding high-water levels that could cause flooding and its effects, as well as their
associated return periods were also estimated. An evaluation of the dam water level
data’s domain of attraction served as the study’s starting point. The data were fitted
using the Generalized Extreme Value distribution (GEV) and the Generalized Pareto
distribution (GPD). To account for potential truncation at very high-water levels,
the Right-Truncated Peaks-Over-Threshold (RT-POT) Distribution was fitted to the
data. The parameters of the GEV and GPD distributions were estimated using the
Maximum Likelihood (ML) and Bayesian estimation methods. The parameters of the
RT POT distribution were also estimated using the Maximum Likelihood (ML) and
Hill estimation methods. The results show that Akosombo dam water level data tail
distribution has a negative shape parameter (γ < 0), which places it in the Weibull
domain of attraction. Both estimation methods yielded remarkably similar estimates.
Several exceedance probabilities for various levels of the dam are also estimated. The
results show that it is not conceivable for the dam’s water level to rise over its 278-foot
maximum operating water level. Therefore, it is very unlikely for the water level to
rise above the crest of the dam under the prevailing operating conditions.
