The hydrological model requires precise parameter calibration to reflect the basin characteristicsproperly. The optimum parameter values depend highly on the runoff characteristics; thus, the simulated runoff data affects the uncertainty in hydrological drought assessment using hydrological models. This study quantified the hydrological drought uncertainty based on all available calibrated parameters for 12 different observation periods. The Soil and water assessment Tool was used for hydrological modelling, and the uncertainty was analyzed using Bayesian model averaging (BMA). The hydrological drought index using the simulated runoff was analyzed to vary significantly with the optimized hydrological parameter cases. The drought index calculation using the estimated runoff showed that the number of droughts occurred frequently as the duration increased, But, it was observed that severe droughts of 21-month duration occur most frequently. The uncertainty analysis conducted with BMA revealed that for durations shorter than 18 months, the uncertainties in drought index calculations were higher than those in runoff simulations. As the duration increased, uncertainties decreased, with values of 57%, 54%, 50%, 23%, 23%, 19%, 16% and 16% for 3, 6, 9, 12, 15, 18, 21 and 24-month durations, respectively. The average uncertainty was larger for runoff estimation than for drought calculation. Still, the uncertainty variation by each PC was larger for drought calculation, ranging from 0 to 94% as the duration increased to 24 months. Therefore,the results of this study confirm that hydrological drought analysis using hydrological models contains uncertainties depending on the hydrological model parameter cases.


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    Titel :

    Quantifying Uncertainty in Hydrological Drought Index Using Calibrated SWAT Model


    Weitere Titelangaben:

    KSCE J Civ Eng


    Beteiligte:
    Kim, Jin Hyuck (Autor:in) / Chung, Eun-Sung (Autor:in) / Song, Jae Yeol (Autor:in) / Shahid, Shamsuddin (Autor:in)

    Erschienen in:

    Erscheinungsdatum :

    01.05.2024


    Format / Umfang :

    11 pages




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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