The estimation of the uncertainty associated with rating curves of the river Ivinhema in the state of Paraná/Brazil

Abstract

The estimation of the uncertainty associated with stage-discharge relations is a challenge to the hydrologists. Bayesian inference with likelihood estimator is a promissory approach. The choice of the likelihood function has an important impact on the capability of the model to represent the residues. This paper aims evaluate two likelihood functions with DREAM algorithm to estimate specific non-unique stage-discharge rating curves: normal likelihood function and Laplace likelihood function. The result of BaRatin is also discussed. The MCMC of the DREAM and the BaRatin algorithm have been compared and its results seem consistent for the studied case. The Laplace likelihood function presented as good results as normal likelihood function for the residues. Other gauging stations should be evaluated to attend more general conclusions.

Development of a national 7-day ensemble streamflow forecasting service for Australia

“…There are advanced methods for estimating the uncertainty caused by instrument and rating errors. Maldonado et al (2018) present a method for estimating the uncertainty associated with stage-discharge relations using Bayesian inference with the likelihood estimator approach. However, maintaining the precision of observation 540 instruments and updating rating tables is the responsibility of data providers, including state water management entities, irrigators, hydropower generators and water utilities and is out of scope of this study.…”