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Uncertainty Analysis of Hydrologic Forecasts Based on Copulas

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Copulas and Its Application in Hydrology and Water Resources

Part of the book series: Springer Water ((SPWA))

Abstract

A hydrologic uncertainty processor (HUP) that the prior density and likelihood function are explicitly expressed is introduced based on a copula function. The results show that the copula-based HUP is comparable to the meta-Gaussian HUP regarding the posterior median forecasts. Besides, the probabilistic forecasts produced by the copula-based HUP have slightly higher reliability and lower resolution, as compared to those of the meta-Gaussian HUP. A Copula Bayesian processor associated with the Bayesian model averaging (CBP-BMA) method is used with ensemble lumped hydrological models. Compared with the BMA and Copula-BMA methods, the CBP-BMA method relaxes any assumption on the distribution of conditional PDFs. The case study results demonstrate that the CBP-BMA method can improve hydrological forecasting precision with higher coverage ratios. The copula-based HUP and CBP-BMA methods provide alternative approaches to uncertainty analysis of hydrological forecasts.

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Authors and Affiliations

  1. School of Hydropower & Information Engineering, Huazhong University of Science and Technology, No. 1037 Luoyu Road, Wuhan, 430074, Hubei, China

    Lu Chen

  2. State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, No. 299 Bayi Road, Wuhan, 430072, Hubei, China

    Shenglian Guo

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Chen, L., Guo, S. (2019). Uncertainty Analysis of Hydrologic Forecasts Based on Copulas. In: Copulas and Its Application in Hydrology and Water Resources. Springer Water. Springer, Singapore. https://doi.org/10.1007/978-981-13-0574-0_8

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