Assessing the effects of rating curve uncertainty in flood frequency analysis

Abstract

Maximum flows are often estimated from flood frequency analysis, by means of the statistical fitting of a theoretical probability distribution to maximum annual flow data. However, because of the limitations imposed by the practice of at-site flow measurement, empirical models are applied as the rating curve for estimating streamflow. These curves are approximations of the actual flows and incorporate different sources of uncertainty, especially in the extrapolation portions. These uncertainties are propagated in the frequency analysis and influence the estimated quantiles. For better understanding and describing the influence of the stage-discharge uncertainty in this process, the results of Bayesian rating curve modeling, which considers the physical knowledge of the gauging station as prior information, were combined with Bayesian flood frequency analysis under asymptotic extreme value theory. The method was applied to the Acorizal stream gauging station, located in the interior of the state of Mato Grosso - BR. The main results suggested that, although the uncertainties of the rating curve can be relevant in the estimation of maximum flow quantiles, the uncertainties arising from finite-sample inference might exert greater impacts on the flow credibility intervals even for moderate sample sizes.

Are historical stage records useful to decrease the uncertainty of flood frequency analysis ? A 200-year long case study

“…Moreover, the estimation and the propagation of the various sources of uncertainty throughout the FFA chain is not straightforward to achieve. Several papers performed an integrated analysis in which both rating curve parameters and flood frequency distribution were estimated ; Steinbakk et al (2016); Vieira et al (2022)). They concluded that accounting for rating curve uncertainties may notably widen the total uncertainty of flood quantiles.…”

“…Therefore, it is possible to distinguish the effects of independent and systematic stage errors on streamflow uncertainty. , Steinbakk et al (2016), and Vieira et al (2022) performed an integrated analysis in which both rating curve parameters and flood frequency distribution are estimated. These studies highlighted the importance of considering rating curve uncertainty for design flood estimations and concluded that, under some conditions, accounting for rating curve uncertainty may notably widen the uncertainty intervals around flood quantiles.…”