Assessment of Using Rainfall-Runoff Model to Predict Stream-flow in Ungauged Awun River Watershed, Kwara State, Nigeria

Abstract

Predicting streamflow for an ungauged river is essential for effective water resource management, flood risk mitigation, ecological protection, and infrastructure planning, providing critical insights despite the absence of direct measurement data. Therefore, the objective of this paper is to assess the use of a rainfall-runoff model for predicting streamflow in the ungauged Awun River Watershed, Kwara State, Nigeria. Due to the absence of measured data, regional calibration techniques were employed, utilizing data from nearby gauged river with similar hydrological characteristics. The hydrologic model predicted a peak discharge of 2164 m³/s and a total runoff volume of 19967.78 m³ during the modeling period, providing valuable insights for flood forecasting and water resource planning. Performance evaluation metrics indicated a Nash-Sutcliffe Efficiency (NSE) of 0.54 and a Mean Error (ME) of 0.33, reflecting moderate agreement between observed and simulated runoff data. The Percent Bias (PBIAS) of 49.25% highlighted a tendency towards overestimation. Furthermore, a high R-squared (R²) value of 0.89 demonstrated that the model successfully explained 89% of the variance in observed runoff, effectively capturing the key hydrological characteristics of the Awun River watershed. This modeling framework is valuable for land-use planning, water resource management, decision-making, and flood risk assessments in the Awun River region.