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A data censoring approach for predictive error modeling of flow in ephemeral rivers

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Wang, QJ, Bennett, JC, Robertson, DE and Li, M 2020 , 'A data censoring approach for predictive error modeling of flow in ephemeral rivers' , Water Resources Research, vol. 56, no. 1 , pp. 1-19 , doi: 10.1029/2019WR026128.

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Abstract

Flow simulations of ephemeral rivers are often highly uncertain. Therefore, error models that can reliably quantify predictive uncertainty are particularly important. Existing error models are incapable of producing predictive distributions that contain >50% zeros, making them unsuitable for use in highly ephemeral rivers. We propose a new method to produce reliable predictions in highly ephemeral rivers. The method uses data censoring of observed and simulated flow to estimate model parameters by maximum likelihood. Predictive uncertainty is conditioned on the simulation in such a way that it can generate >50% zeros. Our method allows the setting of a censoring threshold above zero. Many conceptual hydrological models can only approach, but never equal, zero. For these hydrological models, we show that setting a censoring threshold slightly above zero is required to produce reliable predictive distributions in highly ephemeral catchments. Our new method allows reliable predictions to be generated even in highly ephemeral catchments.

Item Type: Article
Authors/Creators:Wang, QJ and Bennett, JC and Robertson, DE and Li, M
Keywords: maximum likelihood estimation, hydrological prediction, ephemeral rivers
Journal or Publication Title: Water Resources Research
Publisher: Amer Geophysical Union
ISSN: 0043-1397
DOI / ID Number: 10.1029/2019WR026128
Copyright Information:

©2020. American Geophysical Union

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