extensive spatio-temporal assessment of flood events by application of pair-copulas
Clicks: 129
ID: 218901
2015
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This
article has not been analysed, so there is no overall score —
reader engagement is measured and shown alongside.
Reader Engagement
Steady Performance
30.0
/100
129 views
13 readers
AI Quality Assessment
Not analyzed
Readership in this journal
SteadyRanked #50 of 73 articles by views in gruppe interaktion organisation zeitschrift fur angewandte organisationspsychologie
Most read
Least read
Bar heights use a square-root scale.
Mint this article as an NFT
Not yet mintedCreate a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.
5
SUSD
one-off · no wallet required
Abstract
Although the consequences of floods are strongly related to their peak
discharges, a statistical classification of flood events that only depends
on these peaks may not be sufficient for flood risk assessments. In many
cases, the flood risk depends on a number of event characteristics. In case
of an extreme flood, the whole river basin may be affected instead of a
single watershed, and there will be superposition of peak discharges from
adjoining catchments. These peaks differ in size and timing according to the
spatial distribution of precipitation and watershed-specific processes of
flood formation. Thus, the spatial characteristics of flood events should be
considered as stochastic processes. Hence, there is a need for a
multivariate statistical approach that represents the spatial
interdependencies between floods from different watersheds and their
coincidences. This paper addresses the question how these spatial
interdependencies can be quantified. Each flood event is not only assessed
with regard to its local conditions but also according to its
spatio-temporal pattern within the river basin. In this paper we
characterise the coincidence of floods by trivariate Joe-copula and
pair-copulas. Their ability to link the marginal distributions of the
variates while maintaining their dependence structure characterizes them as
an adequate method. The results indicate that the trivariate copula model is
able to represent the multivariate probabilities of the occurrence of
simultaneous flood peaks well. It is suggested that the approach of this
paper is very useful for the risk-based design of retention basins as it
accounts for the complex spatio-temporal interactions of floods.
| Reference Key |
schulte2015proceedingsextensive
Use this key to autocite in the manuscript while using
SciMatic Manuscript Manager or Thesis Manager
|
|---|---|
| Authors | ;M. Schulte;A. H. Schumann |
| Journal | gruppe interaktion organisation zeitschrift fur angewandte organisationspsychologie |
| Year | 2015 |
| DOI |
10.5194/piahs-370-177-2015
|
| URL | |
| Keywords |
Citations
No citations found. To add a citation, contact the admin at info@scimatic.org
Comments
No comments yet. Be the first to comment on this article.