Stochastic Time Series Analysis of Stream Flow Data of the River Niger at Lokoja, Kogi State, Nigeria

Abstract

This paper is produced to improve the management and operation system of the River Niger at Lokoja - Nigeria. It is important to determine the hydrological system of River Niger, which is the major water sources of the annual flood in the area. Lokoja has been experiencing the problem of flooding every wet season from April to October of the year. It experienced the highest flood in 2022. In this study, a Modified Thomas Fiering Model (MTFM) is used. This method is a stochastic method that is employed for generating and predicting a synthetic flow in hydrology. It is used to generate a synthetic river flow in Lokoja, Kogi State, Nigeria. The procedure for stochastic or statistical method is applied on the data obtained at the Lokoja gauging station, Nigeria. The study utilized the monthly flows data (discharge in m3/s) from the year 2000 to year 2019. After estimating the model parameters (mean, standard deviation, maximum, minimum, coefficient of variation, skweness and kutrosis), the synthetic time series of monthly flows were simulated. The results showed that the Modified Thomas Fiering model is appropriate and can be applied to forecast monthly flow for planning, design and operation of Water Resources infrastructure. Hence in the presence of large dataset, future forecasting of the river flow can be done to create awareness on it, to allow adequate preparation in mitigating the future effects of flooding in the study area.