Rainfall-Riverflow Trends of Enyong Creek in Akwa Ibom State, Nigeria

Abstract

Rainfall-riverflow is crucial for effective hydrology and water resource management. Hence, the objective of this study was to evaluate the rainfall-riverflow trends of Enyong Creek in Akwa Ibom State, Nigeria, utilizing daily hydro-meteorological data of daily rainfall, river discharge, and temperature data collected from the period 2018 to 2023 and modeling the data by Vector Autoregressive (VAR) models. The results show that the VAR model successfully captured the dynamic relationships among water discharge (WD), rainfall (RF), and average temperature (AVE.TEMP). Equations revealed the influence of past values on the current state of each variable. Correlation matrix and graphical representations confirmed model adequacy. Validation results demonstrated the model's accuracy, with model R-squared value of 0.8781 indicating a strong correlation. The performance measurement of evaluation for the developed model showed a Mean Average Error (MAE), Root Mean Square error (RMSE), and Mean Absolute Percentage Error (MAPE) values of 5.5066, 6.7831, and 7.4203 respectively, revealing a satisfactory accuracy and precision. Information derived from this study offers valuable insights for government officials, policymakers, and planners in accurate flood forecasting, emergency management, land use planning, and infrastructure development.

Keywords

• Keywords: Rainfall-Riverflow Trends; Vector Autoregressive; River Discharge; Flood Forecasting