Unveiling the most effective model to predict streamflow capabilities from versatile hydrological models

Area of Science:

• Hydrology
• Water Resource Management
• Environmental Modeling

Background:

• Accurate streamflow prediction is crucial for water resource management, flood control, and agriculture, especially in rainfed regions.
• Evaluating different hydrological models is essential for selecting the most effective tools for specific watersheds.

Purpose of the Study:

• To assess and compare the streamflow prediction accuracy of four hydrological models: Parameter-Efficient Distribution (PED), Hydrologiska Byråns Vattenbalansavdelning (HBV), Hydrological Engineering Center-Hydrological Modeling System (HEC-HMS), and Soil and Water Assessment Tool (SWAT).
• To identify the most suitable model for streamflow prediction in the Koga Watershed, Ethiopia, to support water resource planning.

Main Methods:

• The study involved calibrating and validating four hydrological models using observed daily streamflow data from the Koga Watershed.
• Calibration was performed for the period 1997-2006, and validation for 2007-2011.
• Model performance was evaluated using metrics such as coefficient of determination (R²), Nash-Sutcliffe efficiency (NSE), root mean square error (RMSE), and percentage of bias (PBIAS).

Main Results:

• During calibration, the PED model demonstrated the best performance with R²=0.79 and NSE=0.782.
• During validation, PED continued to show excellent performance with R²=0.70 and NSE=0.72.
• SWAT tended to simulate higher flows, HEC-HMS overestimated flows, and HBV and SWAT forecasted minimal flows during validation.

Conclusions:

• The Parameter-Efficient Distribution (PED) model is identified as the most suitable hydrological model for streamflow prediction in the Koga Watershed due to its consistent performance.
• The study's findings offer valuable guidance for selecting appropriate hydrological models to enhance water resource planning and management strategies.