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Uncertainty analysis for streamflow modeling using multiple optimization algorithms at a data-scarce semi-arid region: Altınapa Reservoir Watershed, Turkey

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Abstract

The calibration of ecohydrological models is challenging in semi-arid regions, particularly for data-scarce conditions. Precise uncertainty analysis is also critical for determining the range of uncertainty in model predictions. In this study, we evaluated the applicability of a ecohydrological model, Soil and Water Assessment Tool (SWAT), for a data-scarce semi-arid basin (Altınapa Reservoir Watershed) in Turkey. We used multiple optimization algorithms for model calibration and uncertainty assessment and compared their performances. The SWAT model was set up using the digital elevation model, land use/cover, and soil data obtained from global datasets, and climate data obtained from local stations. The optimization algorithms included Sequential Uncertainty Fitting (SUFI-2), Parameter Solution (ParaSol), Generalized Likelihood Uncertainty Estimation (GLUE), and Particle Swarm Optimization (PSO). Twenty-four parameters with initial parameter ranges were chosen for parameter uncertainty analysis. The performance of four algorithms were evaluated based on the Nash-Sutcliffe Efficiency (NSE), determination coefficient (R2), P-factor, R-factor, and convenience of implementation of model. The models provided the general representation of the hydrologic processes and hydrological dynamics in the basin. Satisfactory model performance was obtained based on NSE (> 0.5) with the SUFI-2 algorithm during model calibration and validation. R2 criteria (> 0.6) was met by all algorithms, except for SUFI-2, during calibration, but it was not met during validation. 70 to 80% of the values were bracketed by the 95PPU during the calibration period and 50–60% during the validation period with all four algorithms. The R-factor was smaller than 1 with only SUFI-2 during calibration and with GLUE, ParaSol, and PSO during validation. Overall, the SUFI-2 calculation was accepted as a viable technique for calibration and uncertainty assessment, even though it requires more work and extra requirements for adjusting parameter ranges.

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Acknowledgements

This study was supported by the Scientific and Technological Research Council of Turkey (Project No: 118Y402) and Erciyes University Research Fund (FDK-2021-10794). We would like to thank State Hydraulic Works (Turkey), State Meteorology Service (Turkey), and Konya Water and Sewerage Administration for their support with data acquisition. We also would like to thank two anonymous reviewers for their valuable comments and suggestions that improved the quality of the paper.

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  1. Department of Environmental Engineering, Erciyes University, Kayseri, Turkey

    Dilibaier Aibaidula, Nuray Ates & Filiz Dadaser-Celik

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Correspondence to Filiz Dadaser-Celik.

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Aibaidula, D., Ates, N. & Dadaser-Celik, F. Uncertainty analysis for streamflow modeling using multiple optimization algorithms at a data-scarce semi-arid region: Altınapa Reservoir Watershed, Turkey. Stoch Environ Res Risk Assess 37, 1997–2011 (2023). https://doi.org/10.1007/s00477-022-02377-x

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