Error propagation of climate model rainfall to streamflow simulation in the Gidabo sub-basin, Ethiopian Rift Valley Lakes Basin

• Published in: Hydrological sciences journal Vol. 67; no. 8; pp. 1185 - 1198
• Main Authors: Worako, Adimasu Woldesenbet, Haile, Alemseged Tamiru, Rientjes, Tom, Woldesenbet, Tekalegn Ayele
• Format: Journal Article
• Language: English
• Published: Abingdon Taylor & Francis 11.06.2022; Taylor & Francis Ltd
• Subjects: basins; Bias; Bias correction; Climate; climate change; Climate models; Coefficient of variation; Error correction; error propagation; Ethiopia; Global climate; HBV model; Hydrologic models; Hydrology; Lakes; Methods; model validation; Modelling; Propagation; Rain; Rain effects; Rainfall runoff; Rainfall simulators; Rainfall-runoff modeling; Rainfall-runoff relationships; Regional climate models; Regional climates; Rift valleys; Simulation; Stream discharge; Stream flow; systematic error; Ethiopia
• ISSN: 0262-6667; 2150-3435; 2150-3435
• DOI: 10.1080/02626667.2022.2072220

This study assesses bias error of rainfall from climate models and related error propagation effects to simulated streamflow in the Gidabo sub-basin, Ethiopia. Rainfall is obtained from a combination of four global and regional climate models (GCM-RCMs), and streamflow is simulated by means of the Hydrologiska Byråns Vattenbalansavdelning (HBV-96) rainfall-runoff model. Five bias correction methods were tested to reduce the rainfall bias. To assess the effects of rainfall bias error propagation, percent bias (PBIAS), difference in coefficient of variation (CV), and 10th and 90th percentile indicators were applied. Findings indicate that the bias of the uncorrected rainfall caused large errors in simulated streamflow. All five bias correction methods improved the HBV-96 model performance in terms of capturing the observed streamflow. Overall, the findings of this study indicate that the magnitude of the error propagation varies subject to the selected performance indicator, bias correction method and climate model.