 |
| Titel |
The role of the forest cover on the definition of runoff coefficient in a regional flood frequency analysis applied to Mediterranean catchments |
| VerfasserIn |
Giovanni Battista Chirico, Giovanni Forzieri, Federico Preti |
| Konferenz |
EGU General Assembly 2014
|
| Medientyp |
Artikel
|
| Sprache |
Englisch
|
| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 16 (2014) |
| Datensatznummer |
250093423
|
| Publikation (Nr.) |
 EGU/EGU2014-8125.pdf |
|
|
|
|
|
| Zusammenfassung |
| Flood frequency is fundamental for planning and design structural and non-structural
mitigation strategies against land degradation. Flood frequency analysis aims at estimating
the probability distributions of flood peaks, so that the flood magnitude for any
design return period can be easily determined. The approach commonly employed in
engineering hydrology in ungauged catchments is the regional analysis, which exploits the
hydrological similarities among catchments and the scaling properties of flood
statistics for exporting the information available in gauged catchments to ungauged
catchments. One of method most widely applied by hydrologists and engineers
is the index flood method, based on the identification of homogeneous regions,
where the probability distributions of the annual maximum floods are assumed
invariant except for a site-specific scale parameter known as the index flood. The index
flood is generally assumed coincident with the mean of annual maximum of flood
peaks and is estimated by indirect methods. An indirect estimation method largely
applied is based on a conceptual model structured according to the well-known
rational formula. A key parameter of the rational formula is the runoff coefficient,
which can be interpreted as a probabilistic factor controlling not only the position
but also the slope and the curvature of the flood frequency curve. Provided that
vegetation patterns can have a significant influence on the catchment antecedent
conditions as well as on other rainfall runoff processes in rural catchments, in this
study we explore to what extent forest cover can be employed to predict the runoff
coefficient, in the framework of a regional flood frequency analysis based on the
rational formula coupled with a regional analysis of annual maximum rainfall depths.
The results of a k-means cluster analysis applied to a data set of 75 catchments
distributed from South to Central Italy, evidenced that the second component of the
runoff coefficient can be partly explained by the forest cover fraction, scaled with
the corresponding critical areal rainfall depth. We proposed a linear regression
model to improve the prediction of the runoff coefficient, exploiting the ratio of the
forest cover to the catchment critical rainfall depth as dependent variable, with just
one additional empirical parameter. The proposed regression enables a significant
bias correction of the runoff coefficient, particularly for those small mountainous
catchments, characterised by larger forest cover fraction and lower critical rainfall depth. |
|
|
|
|
|
|