Drawing a better understanding of flood quantiles from a bag
The "100-year flood" is commonly used, for instance in newspapers, but flood hazard assessment is more complex than it seems. We first describe an animation entitled "bag of floods" to make flood quantiles more concrete, using marbles whose colour corresponds to a class of return...
Gespeichert in:
Hauptverfasser: | , , , |
---|---|
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext bestellen |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
Zusammenfassung: | The "100-year flood" is commonly used, for instance in newspapers, but flood
hazard assessment is more complex than it seems. We first describe an animation
entitled "bag of floods" to make flood quantiles more concrete, using marbles
whose colour corresponds to a class of return period. Discussing the analogies
and differences between drawing a marble from the bag and the next annual flood
make it easier to explain that flood hazard assessment (i) must not be focussed
on the "100-yr flood", (ii) is often expressed as a probability over one given
year, but for planning it should be estimated over a much longer duration (like
successive draws from the bag) and (iii) variability is significant and
matters. Scripts allowing to simulate long series of draws confirm that
empirical probabilities get close to theoretical probabilities, but also
illustrate less intuitive results : on average one quarter of 100 successive
draws, contains two floods or more with a discharge exceeding the "100-yr
discharge". To go further, Sample2Gumbel is a teaching tool drawing annual
maxima discharges. It compares on a graph (i) a "real distribution", coded in
the script and used to draw a sample, (ii) the sample expressed with respect to
"plotting position", expressed as a return period but which is in fact a crude
estimation to allow plotting, (iii) the distribution fitted on the sample. This
demo tool illustrates the variability of different tries, with samples of the
same length, and shows how uncertainty evolves with the sample size. To improve
it, more distributions could be included, and damage estimation could be added. |
---|---|
DOI: | 10.48550/arxiv.2312.11068 |