Hydrology and Earth System Sciences
Hydrology and Earth System Sciences
HESS
Articles | Volume 28, issue 13
Articles | Volume 28, issue 13
https://doi.org/10.5194/hess-28-2831-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-28-2831-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 28, issue 13
Research article
 | 
03 Jul 2024
Research article |  | 03 Jul 2024

Using the classical model for structured expert judgment to estimate extremes: a case study of discharges in the Meuse River

Guus Rongen, Oswaldo Morales-Nápoles, and Matthijs Kok

Related authors

Calculating flood probability in Obihiro using a probabilistic method: incorporating the probability of dike failure with uncertainty
Fumihiko Uemura, Guus Rongen, Shigekazu Masuya, Takatoshi Yoshida, and Tomohito J. Yamada
Proc. IAHS, 386, 69–74, https://doi.org/10.5194/piahs-386-69-2024,https://doi.org/10.5194/piahs-386-69-2024, 2024
Short summary

Related subject area

Subject: Rivers and Lakes | Techniques and Approaches: Uncertainty analysis
Ensemble streamflow data assimilation using WRF-Hydro and DART: novel localization and inflation techniques applied to Hurricane Florence flooding
Mohamad El Gharamti, James L. McCreight, Seong Jin Noh, Timothy J. Hoar, Arezoo RafieeiNasab, and Benjamin K. Johnson
Hydrol. Earth Syst. Sci., 25, 5315–5336, https://doi.org/10.5194/hess-25-5315-2021,https://doi.org/10.5194/hess-25-5315-2021, 2021
Short summary
Assessment of uncertainties in soil erosion and sediment yield estimates at ungauged basins: an application to the Garra River basin, India
Somil Swarnkar, Anshu Malini, Shivam Tripathi, and Rajiv Sinha
Hydrol. Earth Syst. Sci., 22, 2471–2485, https://doi.org/10.5194/hess-22-2471-2018,https://doi.org/10.5194/hess-22-2471-2018, 2018
Short summary
Sediment and nutrient budgets are inherently dynamic: evidence from a long-term study of two subtropical reservoirs
Katherine R. O'Brien, Tony R. Weber, Catherine Leigh, and Michele A. Burford
Hydrol. Earth Syst. Sci., 20, 4881–4894, https://doi.org/10.5194/hess-20-4881-2016,https://doi.org/10.5194/hess-20-4881-2016, 2016
Short summary
Performance and robustness of probabilistic river forecasts computed with quantile regression based on multiple independent variables
F. Hoss and P. S. Fischbeck
Hydrol. Earth Syst. Sci., 19, 3969–3990, https://doi.org/10.5194/hess-19-3969-2015,https://doi.org/10.5194/hess-19-3969-2015, 2015
Short summary
Using high-frequency water quality data to assess sampling strategies for the EU Water Framework Directive
R. A. Skeffington, S. J. Halliday, A. J. Wade, M. J. Bowes, and M. Loewenthal
Hydrol. Earth Syst. Sci., 19, 2491–2504, https://doi.org/10.5194/hess-19-2491-2015,https://doi.org/10.5194/hess-19-2491-2015, 2015
Short summary
More articles (3)

Cited articles

Al-Awadhi, S. A. and Garthwaite, P. H.: An elicitation method for multivariate normal distributions, Commun. Stat. Theory 27, 1123–1142, 1998. a
Bamber, J. L., Oppenheimer, M., Kopp, R. E., Aspinall, W. P., and Cooke, R. M.: Ice sheet contributions to future sea-level rise from structured expert judgment, P. Natl. Acad. Sci. USA, 116, 11195–11200, 2019. a
Benito, G. and Thorndycraft, V.: Palaeoflood hydrology and its role in applied hydrological sciences, J. Hydrol., 313, 3–15, 2005. a
Bernard, A. and Bos-Levenbach, E.: The plotting of observations on probability-paper, Stichting Mathematisch Centrum, Statistische Afdeling, https://ir.cwi.nl/pub/8241 (last access: 21 June 2024), 1955. a
Bouaziz, L. J. E., Fenicia, F., Thirel, G., de Boer-Euser, T., Buitink, J., Brauer, C. C., De Niel, J., Dewals, B. J., Drogue, G., Grelier, B., Melsen, L. A., Moustakas, S., Nossent, J., Pereira, F., Sprokkereef, E., Stam, J., Weerts, A. H., Willems, P., Savenije, H. H. G., and Hrachowitz, M.: Behind the scenes of streamflow model performance, Hydrol. Earth Syst. Sci., 25, 1069–1095, https://doi.org/10.5194/hess-25-1069-2021, 2021. a
More articles (51)
Download
Short summary
This study proposes a new method for predicting extreme events such as floods on the river Meuse. The current method was shown to be unreliable as it did not predict a recent flood. We 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.
Read more