rainfall extremes and runoff dynamics in lokoja using hec-hms: a hydro-climate modeling approach

The hydrological modeling methodology integrates climate and hydrological frameworks to scrutinize the ramifications of climatic variability on aquatic systems, underscoring the necessity of comprehending rainfall-runoff dynamics in lokoja for the formulation of efficacious flood management and climate adaptation strategies. this study analyzed rainfall-runoff responses using a data-driven hydrological model to identify seasonal rainfall patterns and evaluate flood risk through simulation outputs. daily rainfall and runoff data from 2010 to 2023, obtained from the nigerian meteorological agency (nimet), were analyzed using a hydrologic engineering center's hydrologic modeling system (hec–hms)-inspired framework. model calibration and validation were conducted using the nash–sutcliffe efficiency coefficient, while impulse response functions were employed to compare observed and simulated data. results indicated the rainfall distribution with a peak (~320 mm) in august and dry conditions from november to april. significant anomalies occurred in 2012, 2017, and 2022—years marked by heightened flood events—while 2015, 2016, and 2021 displayed drought-like tendencies. runoff often exceeded 100 m³/s and revealed a near-perfect statistical correlation (r = 1.0) between annual rainfall and modeled runoff with a regression slope of 0.1484 m³/s per mm of rainfall. the model effectively captured the hydrological response of lokoja's watershed, highlighting the significant influence of rainfall anomalies on runoff patterns. these findings reinforce the importance of predictive modeling for flood risk assessment. future studies should integrate climate forecasts and land use change assessments to enhance hydrological predictions and inform sustainable flood mitigation strategies.