07 Mar 2023
 | 07 Mar 2023

Using structured expert judgment to Estimate extreme river discharges: a case study of the Meuse River

Guus Rongen, Oswaldo Morales-Nápoles, and Matthijs Kok

Abstract. Accurate estimation of extreme discharges in rivers, such as the Meuse, is crucial for effective flood risk assessment. However, existing statistical and hydrological models that estimate these discharges often lack transparency regarding the uncertainty of their predictions, as evidenced by the devastating flood event that occurred in July 2021 which was not captured by the existing model for estimating design discharges. This article proposes an alternative approach with a central role for expert judgment, using Cooke’s method. A simple statistical model was developed for the river basin, consisting of correlated GEV-distributions for discharges in upstream sub-catchments. The model was fitted to expert judgments, measurements, and the combination of both, using Markov chain Monte Carlo. Results from the model fitted only to measurements were accurate for more frequent events, but less certain for extreme events. Using expert judgment reduced uncertainty for these extremes but was less accurate for more frequent events. The combined approach provided the most plausible results, with Cooke's method reducing the uncertainty by appointing most weight to two of the seven experts. The study demonstrates that utilizing hydrological experts in this manner can provide plausible results with a relatively limited effort, even in situations where measurements are scarce or unavailable.

Guus Rongen et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Referee Comment on egusphere-2023-39', Anonymous Referee #1, 29 Mar 2023
    • AC1: 'Reply on RC1', Guus Rongen, 22 Apr 2023
  • RC2: 'Comment on egusphere-2023-39', Anonymous Referee #2, 15 Apr 2023
    • AC2: 'Reply on RC2', Guus Rongen, 22 Apr 2023

Guus Rongen et al.


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Short summary
This study proposes a new method for predicting extreme flood levels in rivers like the Meuse. The current has shown to be unreliable as it did not predict a recent flood. We have developed a model that includes information from experts and combines this with measurements. We found that this approach gives more accurate predictions, particularly for extreme events. The research is important for predictions of extreme flood levels that are necessary for protecting communities against floods.