Time Series Analysis of River Discharge, Water Stage, and Rainfall at Lokoja Section of Benue River, Kogi State, Nigeria
Ali Patricia, Deborah Yisaga, Monday Akpegi Onah*, Odeh Adimanyi and Ene Grace Stephen
ABSTRACT
This study carried out a time analysis of river water level (stage), rainfall, and discharge in the Lokoja section of River Benue and assessed their implications for flooding. The specific objectives that guided the study were focused on monthly and annual variability in water level, rainfall, and discharge are examined, along with their interrelationships. Data on water level and discharge were acquired from the Nigeria Hydrological Services Agency (NHSA), Abuja covering 22 years (2001 -2021), while rainfall data were obtained from the Nigeria Meteorological Agency (NiMet), Lagos Operational Headquarters. Time series analysis was carried out using the Least Square Regression Model. The significance of the trend was tested using the student’s t-test at a 0.05 (95%) confidence level. While descriptive statistics employed are mean, standard deviation, and coefficient of variation. The results indicate a decline in water levels from January to April, followed by a significant rise from May to October. Annual water levels show a significant positive trend over 21 years (R² = 0.2968, r = 0.5448), with notable fluctuations. Peak discharge exhibits a fluctuating monthly pattern, with a significant increasing trend over the years (R² = 0.2451, r = 0.4951), indicating potential flood risks. Monthly rainfall varies significantly, with notable peaks between April and August. Although annual rainfall shows a slight increasing trend, it’s not statistically significant. Strong correlations exist between peak discharge and water levels (r ≈ 0.982), while relationships between discharge and rainfall, and water levels and rainfall are moderate. Multiple regression analysis reveals water level significantly influences discharge (β ≈ 30.27, R² = 0.960). The study recommends implementing seasonal water management plans to address seasonal fluctuations, enhancing flood forecasting systems, adopting adaptive management strategies, investing in long-term monitoring and research, and promoting stakeholder collaboration. These measures aim to improve water resource management resilience, flood preparedness, and response capabilities in the face of climate variability and change.
