Abstract
Flood frequency relations are generally highly uncertain for large return times due to the relatively short data set of annual maximum discharges. This extrapolation uncertainty can be decreased by extending the data set with historic flood events. However, two problems arise if a traditional flood frequency analysis should be performed, namely: (1) the historic flood events must be translated into present-day discharges since we are interested in the effects of these historic events in present times, and (2) a continuous data set is required to perform a traditional flood frequency analysis. In this study, a 1D-2D coupled hydraulic flood model is set up with which historic flood events are routed over the current geometry of the Rhine river. Furthermore, a bootstrap approach is proposed to enable the creation of a continuous data set of annual maximum discharges. The data set near Lobith (the German-Dutch border) is extended from 120 to 700 years resulting in a tremendous reduction of the 95% confidence interval of the fitted flood frequency relation for large return periods.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of FLOODrisk 2020 |
| Subtitle of host publication | 4th European Conference on Flood Risk Management |
| Number of pages | 8 |
| DOIs | |
| Publication status | Published - 2021 |
| Event | 4th European Conference on Flood Risk Management, FLOODrisk 2020 - Budapest University of Technology and Economics (BME) ; Online event, Virtual Conference, Hungary Duration: 21 Jun 2021 → 25 Jun 2021 Conference number: 4 |
Conference
| Conference | 4th European Conference on Flood Risk Management, FLOODrisk 2020 |
|---|---|
| Abbreviated title | FLOODrisk 2020 |
| Country/Territory | Hungary |
| City | Virtual Conference |
| Period | 21/06/21 → 25/06/21 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
-
SDG 11 Sustainable Cities and Communities
Fingerprint
Dive into the research topics of 'The use of historic flood events to reduce uncertainty in future flood frequency predictions: a bootstrap method'. Together they form a unique fingerprint.Cite this
- APA
- Author
- BIBTEX
- Harvard
- Standard
- RIS
- Vancouver