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  Flood tailored regional rainfall-runoff modelling with stochastic discharge ensemble generation

Lombardo, L., Pesce, M., Cafiero, L., Terasova, L., Claps, P., Vogel, R., Papalexiou, S., Merz, R., Viglione, A. (2023): Flood tailored regional rainfall-runoff modelling with stochastic discharge ensemble generation, XXVIII General Assembly of the International Union of Geodesy and Geophysics (IUGG) (Berlin 2023).
https://doi.org/10.57757/IUGG23-3619

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Item Permalink: https://gfzpublic.gfz-potsdam.de/pubman/item/item_5020923 Version Permalink: https://gfzpublic.gfz-potsdam.de/pubman/item/item_5020923_1
Genre: Conference Paper

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 Creators:
Lombardo, Luca1, Author
Pesce, Matteo1, Author
Cafiero, Luigi1, Author
Terasova, Larisa1, Author
Claps, Pierluigi1, Author
Vogel, Richard1, Author
Papalexiou, Simon1, Author
Merz, Ralf1, Author
Viglione, Alberto1, Author
Affiliations:
1IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations, ou_5011304              

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 Abstract: As our climate system climbs through its current warming path, temperature and precipitation are greatly affected also in their extremes. There is a general concern that climate change may affect also the magnitude and frequency of river floods and that existing and planned hydraulic structures and flood defenses may become inadequate to provide the required protection level in the future. At the same time, land-use changes and river training also have affected, are affecting, and will affect river floods in the future. Deterministic rainfall-runoff models are used in nearly all hydrologic planning, design, and management activities, and in theory can account for changes in forcing and processes due to climate and environmental change. Yet they are not easily transferred to ungauged locations, and they cannot properly reproduce extreme design quantiles obtained from commonly accepted statistical methods. We aim at coupling a newly developed methodology for regional model parameter calibration based on machine learning techniques, which allow for tuning models in a distributed way over large areas, to a post-processing approach that adds a stochastic error to the deterministic model predictions and reduces the bias in the estimation of extreme discharges associated to low exceedance probabilities. The research questions are:How well can the stochastic post-processing of the outputs of rainfall-runoff models, designed to reproduce everyday river flow dynamics, reproduce the statistics of extreme events obtainable through flood frequency analysis?How well regionally distributed rainfall-runoff models with post-processed outputs compare to regional flood frequency analysis outcomes?Preliminary results will be discussed during the presentation.

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Language(s): eng - English
 Dates: 2023-07-112023-07-11
 Publication Status: Finally published
 Pages: -
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 Rev. Type: -
 Identifiers: DOI: 10.57757/IUGG23-3619
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Title: XXVIII General Assembly of the International Union of Geodesy and Geophysics (IUGG)
Place of Event: Berlin
Start-/End Date: 2023-07-11 - 2023-07-20

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Title: XXVIII General Assembly of the International Union of Geodesy and Geophysics (IUGG)
Source Genre: Proceedings
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Publ. Info: Potsdam : GFZ German Research Centre for Geosciences
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