Browsing Department of Water Resources Engineering by Subject "Machine Learning"

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Assessing groundwater vulnerability to salinity using modified drastic model and machine learning

Othieno, Timothy (Busitema University, 2025)

Groundwater vulnerability to salinity assessment serves as a measure of potential groundwater salinity pollution in a target area. The study focused on modiﬁed DRASTIC model to assess groundwater vulnerability to salinity, ...
Assessment of the application of machine learning in groundwater prospecting for siting of boreholes

Ssekyanzi, Christopher (Busitema University, 2025)

This report presents an evaluation of the role of machine learning in predictive studies focusing on groundwater. Machine learning algorithms such and Artificial Neural Networks (ANN) and Extreme Gradient Boost(XGB) to ...
Development of a sediment monitoring model for river systems

Edima, James (Busitema University, 2025)

This study presents a comprehensive framework for monitoring and managing sedimentation in River Malaba, a transboundary river shared by Uganda and Kenya within the Malaba subcatchment. The research integrated hydro ...

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