Use of Artificial Intelligence for Modeling the Flows of the Kalamu River and the Congo River at Boma for Energy Security

Authors

  • André Nzita Mampuya 1Regional School of Water (ERE), University of Kinshasa (UNIKIN), Kinshasa, Democratic Republic of the Congo Author
  • Clément Umba-di-Mbudi N’zau President Joseph Kasa-Vubu University, Faculty of Engineering, Boma, Democratic Republic of the Congo Author
  • Joséphine Kankolongo Ntumba University of Kinshasa, Faculty of science and technology, Kinshasa, Democratic Republic of the Congo Author
  • Guyh Ngoma Dituba University of Quebec in Abitibi-Temiscamingue, School of Engineering, Rouyn-Noranda, Canada Author

DOI:

https://doi.org/10.59228/rcst.026.v5.i1.232

Keywords:

Intelligence artificielle, Modélisation des débits, Forêt aléatoire, Sécurité énergétique, Gestion des ressources en eau, Artificial intelligence, Flow modeling, Random Forest, Energy security, Water resource management

Abstract

Water resource assessment is crucial in the face of growing energy and environmental security challenges. This study focuses on the feasibility of installing a pumped-storage hydroelectric system in Boma, Democratic Republic of Congo, in response to frequent power outages. Objectives include modeling the river of the Kalamu and Congo Rivers to determine the project's viability. To do this, historical data on river levels, collected between 1960 and 2017, as well as precipitation and evaporation data collected between 1992 and 2023, were analyzed, taking into account the lack of flow data on the Kalamu River, using artificial intelligence methods, including the Random Forest approach. The results show significant fluctuations in flow rates, with periods of prolonged drought affecting water availability for the project. The study highlights significant challenges related to water resource management, including flow variability, which may compromise the effectiveness of the proposed system. It is recommended that Congo River flows be considered as a viable alternative while integrating sustainable water resource management strategies to meet local needs.

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References

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Published

2026-02-18

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