the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Flood drivers and trends: a case study of the Geul River Catchment (the Netherlands) over the past half century
Athanasios Tsiokanos
Martine Rutten
Ruud J. van der Ent
Remko Uijlenhoet
Abstract. Extreme precipitation in July 2021 caused devastating flooding in Germany, Belgium and in the Netherlands, particularly in the Geul river catchment. Such precipitation extremes were not recorded previously and were not expected to occur in summer. This contributed to poor flood forecast and hence to large damage. Climate change was mentioned as a potential explanation for these unprecedented events. Yet, before such a statement can be made, we need a better understanding of the drivers of floods in the Geul and their long-term variability, which are poorly understood and have not been examined recently. In this paper, we use an event-based approach to identify the dominant flood drivers in the Geul and employ a multi-temporal trend analysis to investigate their temporal variabilities, as well as, a novel methodology to detect the dominant direction of a trend. Results suggest that extreme 24-hour precipitation cannot solely lead to floods. Heavy multi-day precipitation is the primary high-flow driver in the catchment and the joint probability of heavy and prolonged rainfall with wet initial conditions (compound event) determines the chances of flooding. Critical precipitation (precipitation that leads to floods) shows a consistent increase in the winter half-year, a period in which more than 70 % of extremely high flows have occurred historically. While no consistent trend patterns are evident in the majority of precipitation and extreme flow trends in the summer half-year, an increasing direction in the recent past is visible.
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Athanasios Tsiokanos et al.
Status: open (until 10 Jan 2024)
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RC1: 'Comment on hess-2023-263', Anonymous Referee #1, 16 Nov 2023
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This paper studies drivers of flooding and flood change in the Geul River catchment (Netherlands). Better understanding the drivers of flood change is a very topical subject and this paper produces a useful contribution on this topic. It especially stands out by providing a more in-depth insight than many large-sample studies (involving many catchments at once) have managed to provide on this topic, while still providing methodologies and insights that can be more widely adopted in understanding drivers of flood and flood change. However, at the same time, the paper seems to suffer from one major issue. I personally recommend the publication of this after this can be addressed meaningfully
Major comments
The consideration of antecedent wetness as a flood driver relies on a threshold API value (exceeding 1). This API index is based on antecedent precipitation and does not take any evaporative processes into account. The latter seems somewhat problematic as soil wetness in this region tends rho be very seasonal (as ET is low in winter and high in summer) which very likely causes the strong seasonality in maximum flow and flood events (see e.g. Figure 3) but which is not visible in any of the considered flood drivers. Therefore it seems that the importance of soil wetness does not reflect soil wetness in this paper, but reflects relative wetness compared to what is normal for that part of the season (which is not relevant to the study?). This problem likely causes a strong bias in all results and thus the overall conclusions
Minor comments
- It seems like the statement “Results suggest that extreme 24-hour precipitation cannot solely lead to floods.” is unlikely but not physically impossible. Therefore, I recommend rephrasing “cannot”.
- L15: “Unprecedented precipitation” seems like a bold statement when it’s not specified for example since the observational record started, or some clause that determines the period over which we talk.
- L33: this statement could, in addition, be supported by some other publications that show the importance of antecedent wetness in other places.
- Fig 2. Check the label of “Feb”.
- L144: “all-4day” misspelled?
- I’d recommend (but maybe this is just personal taste you can ignore) to start the results paragraph with a sentence that summarizes the result. This would make it easier for a reader to focus on when reading the details in the figure that follows. This essentially applies to each new paragraph in the results.
Citation: https://doi.org/10.5194/hess-2023-263-RC1
Athanasios Tsiokanos et al.
Athanasios Tsiokanos et al.
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