CONTINUOUS TIME MARKOV MODEL OF KANJI DAM WATER OUTFLOW AS A PANACEA TO FLOODING IN NIGERIA
Abstract
This paper examines the application of a continuous time Markov model with non-stationary transition probabilities to study the water outflow level of Kainji Dam. The results show that state 2 (Medium water outflow) has the optimal water outflow of about 36%. This consolidates the reality on the phenomenon that the water outflow stays in state 2 (Medium outflow) most of the time and in other states some other time. Also, High water outflow is obtained for about 32%, which shows that flooding is not occur every year in Kainji hydroelectric Dam. These variations of the water outflow directly affect the hydroelectric power generation, periodic floods experienced, and availability of other dam resources. Continuous-time Markov model could be used as a predictive technique for studying the reservoir outflow of the Kainji Hydro Dam. These projections might be useful for the management of the dam resources, readiness and control of periodic floods being experienced in this era in Nigeria.
References
Ahmed Badr, Ahmed Y., Sonia H, and Wael El-D. (2021) Coupled Continuous-Time Markov ChainBayesian Network Model for Dam Failure Risk Prediction. Journal of Infrastructure System 27(4) https://doi.org/10.1061/(ASCE)IS. 1943-555X.0000649 DOI: https://doi.org/10.1061/(ASCE)IS.1943-555X.0000649
Akyuz, D.E, Bayazit.M., & Onoz, B. (2012): Markov Chain Models for Hydrological Drought Characteristics, American Meteorological Society (AMMS) journal, 13(1)25-29 DOI: https://doi.org/10.1175/JHM-D-11-019.1
Arash Adib and Ali Reza Mohammad Majd (2009) Optimization of Reservoir Volume by Yield Model and Simulation of it by Dynamic Programming and Markov Chain Model. American-Eurasian J. Agric. & Environ. Sci., 5 (6): 796-803, 2009. ISSN 1818-6769 IDOSI
Bhat, U. N (1984). Elements of Applied Stochastic Processes, New York: John Wiley
Dingying Yang, Jiamei Wu, Zhenxu Guo, Xiaoye Zeng & Qianqian Zhang (2024) Safety risk Assessment of reservoir dam structure: an empirical study in China. Fuzhou University, Fuzhou 350116, China.2School Content courtesy of Springer Nature, terms of use app DOI: https://doi.org/10.1038/s41598-024-71156-1
Jain, R.K. (1988). The Use of a Time. Varying Markov Model to Study the Effect of Weather on Asthma. Biomedical Journal, 30, 93-97. Korve, K.N. (2000). A Three State Continuous Time Markov Model for the Asthma Process. (Abacus) the Journal of the Mathematical Association of Nigeria, 207, (2), 33-46. DOI: https://doi.org/10.1002/bimj.4710300117
Mohammed A. (2013): Application of Markov Model to Reservoir Elevation of Shiroro Dam, Unpublished M Tech thesis, Department of Mathematics and Statistics, FUT Minna.
Paraskevi, T. (2006). Calculation of the Steady state Probabilities for a Water Management Problem with Three Connected Dams. University of South Australia.
Piantadosi, J. (2004). Optimal Policies for Storage of Urban Storm Water, Unpublished PhD Thesis, University of South Australia.
Thomas, O. A., Benjamin, J. O., & Mathew, O. O. (2023). A Markov model of a generator Performance at the Kainji Hydro-power Station in Nigeria International Journal of Electrical and Computer Engineering (IJECE) Vol. 13, No. 4, August 2023, pp. 3585~3592 ISSN: 2088-8708, https://doi.org/10.11591/ijece.v13i4.pp3585-3592 DOI: https://doi.org/10.11591/ijece.v13i4.pp3585-3592
Copyright (c) 2025 FUDMA JOURNAL OF SCIENCES

This work is licensed under a Creative Commons Attribution 4.0 International License.
FUDMA Journal of Sciences