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The comparison of sensitivity analysis of hydrological uncertainty estimates by GLUE and Bayesian method under the impact of precipitation errors

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Abstract

The input uncertainty is as significant as model error, which affects the parameter estimation, yields bias and misleading results. This study performed a comprehensive comparison and evaluation of uncertainty estimates according to the impact of precipitation errors by GLUE and Bayesian methods using the Metropolis Hasting algorithm in a validated conceptual hydrological model (WASMOD). It aims to explain the sensitivity and differences between the GLUE and Bayesian method applied to hydrological model under precipitation errors with constant multiplier parameter and random multiplier parameter. The 95 % confidence interval of monthly discharge in low flow, medium flow and high flow were selected for comparison. Four indices, i.e. the average relative interval length, the percentage of observations bracketed by the confidence interval, the percentage of observations bracketed by the unit confidence interval and the continuous rank probability score (CRPS) were used in this study for sensitivity analysis under model input error via GLUE and Bayesian methods. It was found that (1) the posterior distributions derived by the Bayesian method are narrower and sharper than those obtained by the GLUE under precipitation errors, but the differences are quite small; (2) Bayesian method performs more sensitive in uncertainty estimates of discharge than GLUE according to the impact of precipitation errors; (3) GLUE and Bayesian methods are more sensitive in uncertainty estimate of high flow than the other flows by the impact of precipitation errors; and (4) under the impact of precipitation, the results of CRPS for low and medium flows are quite stable from both GLUE and Bayesian method while it is sensitive for high flow by Bayesian method.

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Acknowledgments

This study was supported by the Research Council of Norway, Research Project-JOINTINDNOR 203867, Department of Science and Technology, Govt. of India, Project 190159/V10 (SoCoCA) and Project NORINDIA 806793. The second author was also supported by Program of Introducing Talents of Discipline to Universities—the 111 Project of Hohai University.

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Authors and Affiliations

  1. Uni Climate, Uni Research, Bergen, Norway

    Lu Li

  2. Bjerknes Centre for Climate Research, Bergen, Norway

    Lu Li

  3. Department of Geosciences, University of Oslo, Oslo, Norway

    Chong-Yu Xu

  4. Department of Earth Sciences, Uppsala University, Uppsala, Sweden

    Chong-Yu Xu

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  1. Lu Li
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Correspondence to Lu Li.

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Li, L., Xu, CY. The comparison of sensitivity analysis of hydrological uncertainty estimates by GLUE and Bayesian method under the impact of precipitation errors. Stoch Environ Res Risk Assess 28, 491–504 (2014). https://doi.org/10.1007/s00477-013-0767-1

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