Articles | Volume 385
https://doi.org/10.5194/piahs-385-399-2024
https://doi.org/10.5194/piahs-385-399-2024
Post-conference publication
 | 
19 Apr 2024
Post-conference publication |  | 19 Apr 2024

Bayesian inference of synthetic daily rating curves by coupling Chebyshev Polynomials and the GR4J model

Rafael Navas, Pablo Gamazo, and R. Willem Vervoort

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Cited articles

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Arsenault, R. and Brissette, F. P.: Continuous streamflow prediction in ungauged basins: The effects of equifinality and parameter set selection on uncertainty in regionalization approaches, Water Resour. Res., 50, 6135–6153, https://doi.org/10.1002/2013WR014898, 2014. 
Bhandari, B., Markert, K., Mishra, V., Markert, A., and Griffin, R.: Investigation of Data-Driven Rating Curve (DDRC) Approach, Water, 15, 604, https://doi.org/10.3390/w15030604, 2023. 
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Bureau of Meteorology: Water Data Online, Water Information, Bureau of Meteorology [data set], http://www.bom.gov.au/waterdata/, last access: 14 September 2023. 
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Short summary
It’s difficult to estimate the daily discharge of a river when only one instantaneous level record is available per day. This work proposes to estimate synthetic daily rating curves from nearby gauged locations using a rainfall-runoff model and bayesian inference. The results can help provide a more comprehensive understanding of the hydrological functioning of systems where only one instantaneous stage level per day is available.