Ensemble physically based semi-distributed models for the rainfall-runoff process modeling in the data-scarce Katar catchment, Ethiopia

Author:

Gelete Gebre12ORCID,Nourani Vahid13,Gokcekus Huseyin1,Gichamo Tagesse2

Affiliation:

1. a Faculty of Civil and Environmental Engineering, Near East University, TRNC, via Mersin 10, Nicosia 99138, Turkey

2. b College of Agriculture and Environmental Science, Arsi University, Asela 193, Ethiopia

3. c Center of Excellence in Hydro informatics and Faculty of Civil Engineering, University of Tabriz, Tabriz, Iran

Abstract

Abstract This study evaluates the performance of the soil and water assessment tool (SWAT), the hydrologiska byråns vattenbalansavdelning (HBV) and the hydrologic engineering center-hydrologic modeling system (HEC-HMS) for modeling rainfall-runoff in the data-scarce Katar catchment, Ethiopia. First, the rainfall-runoff process was simulated using the SWAT, HBV and HEC-HMS models individually. Second, simple average ensemble (SAE), weighted average ensemble (WAE) and neural network ensemble (NNE) techniques were developed by combining the results of individual models to improve overall accuracy. Statistical performance measures and flow duration curves (FDCs) were used to compare and evaluate the performance of the models. The results showed that the SWAT model outperformed the HBV and HEC-HMS models with the coefficient of determination (R2) and Nash–Sutcliffe efficiency (NSE) of 0.857 and 0.83 for calibration and 0.85 and 0.799 for validation, respectively. The ensemble result showed that NNE outperformed the SAE and WAE techniques, with NSE and R2 values of 0.924 and 0.925 for calibration and 0.896 and 0.904 for validation, respectively. The NNE technique improved the performance of SWAT, HBV and HEC-HMS by 12.14, 22.7 and 26.8%, respectively, in the validation phase. Overall, the results showed that ensemble modeling is a promising option for accurate modeling of the rainfall-runoff process.

Publisher

IWA Publishing

Subject

Atmospheric Science,Geotechnical Engineering and Engineering Geology,Civil and Structural Engineering,Water Science and Technology

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