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Calibration and Uncertainty Analysis for Isovel Contours-based Stage-discharge Rating Curve by Sequential Uncertainty Fitting (SUFI-2) Method

Author

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  • Sajjad M. Vatanchi

    (Ferdowsi University of Mashhad)

  • Mahmoud F. Maghrebi

    (Ferdowsi University of Mashhad)

Abstract

Accurately estimating river streamflow necessitates reliable uncertainty quantification in stage-discharge rating curves (SDRCs). This study investigates three methods (Quasi-Newton + covariance matrix (QN + CM), Generalized Likelihood Uncertainty Estimation (GLUE), and Sequential Uncertainty Fitting Ver-2 (SUFI-2)) to analyze uncertainty in isovel contour-based SDRCs and evaluate their performance. By leveraging hydraulic parameters and velocities derived from isovel contours, SDRCs can be established. The model was calibrated using observational data, its performance assessed during the validation period, and its accuracy verified in the testing period. The optimal number of observation data was determined based on the model’s performance in the validation phase. Correlation coefficient (CC) and mutual information (MI) were employed to identify influential hydraulic parameters. The Trent River, characterized by a complex cross-sectional geometry including a floodplain, was selected as a case study. Results indicated that GLUE outperformed SUFI-2 in both the validation and testing periods, achieving superior streamflow estimation (NSE = 0.97, R2 = 0.97, PBIAS=-0.14, and RSR = 0.17). Based on the P/R criterion for assessing uncertainty analysis accuracy, GLUE (P/R = 2.50) and SUFI-2 (P/R = 2.57) significantly outperformed QN + CM. Consequently, calibrating the model using GLUE or SUFI-2 enhances both estimation and uncertainty analysis accuracy. This research also contributes to identifying outliers in streamflow time series.

Suggested Citation

  • Sajjad M. Vatanchi & Mahmoud F. Maghrebi, 2025. "Calibration and Uncertainty Analysis for Isovel Contours-based Stage-discharge Rating Curve by Sequential Uncertainty Fitting (SUFI-2) Method," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 39(4), pages 1655-1676, March.
    • Handle: RePEc:spr:waterr:v:39:y:2025:i:4:d:10.1007_s11269-024-04039-9
    DOI: 10.1007/s11269-024-04039-9
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    References listed on IDEAS

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    1. Manlin Wang & Yu Zhang & Yan Lu & Li Gao & Leizhi Wang, 2023. "Attribution Analysis of Streamflow Changes Based on Large-scale Hydrological Modeling with Uncertainties," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(2), pages 713-730, January.
    2. Evren Turhan, 2022. "An Investigation on the Effect of Outliers for Flood Frequency Analysis: The Case of the Eastern Mediterranean Basin, Turkey," Sustainability, MDPI, vol. 14(24), pages 1-12, December.
    3. Nasrin Fathollahzadeh Attar & Mohammad Taghi Sattari & Halit Apaydin, 2024. "A Novel Stochastic Tree Model for Daily Streamflow Prediction Based on A Noise Suppression Hybridization Algorithm and Efficient Uncertainty Quantification," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 38(6), pages 1943-1964, April.
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