![Hier klicken, um den Treffer aus der Auswahl zu entfernen](images/unchecked.gif) |
Titel |
Flood risk assessment in a Spanish Mediterranean catchment |
VerfasserIn |
S. Salazar, F. Francés, R. García-Bartual, E. Ortiz, J. C. Múnera, J. J. Vélez |
Konferenz |
EGU General Assembly 2009
|
Medientyp |
Artikel
|
Sprache |
Englisch
|
Digitales Dokument |
PDF |
Erschienen |
In: GRA - Volume 11 (2009) |
Datensatznummer |
250024163
|
|
|
|
Zusammenfassung |
This paper describes a multidisciplinary approach for the risk assessment and its application
to analysing the effects of extreme flood events on the Mediterranean catchment called
“Rambla del Poyo” in Valencia (Spain). This catchment located in the East coast of Spain has
an area of 380 km2 and is clearly open to the Mediterranean Mesoscale Convective Storms.
The climate is semiarid, and the flow regime is typically ephemeral, but with highly
frequent flash floods, with peak flows in the order of 500 m3/s. Recently, in 2000
and 2002 the area was severe flooded. The flood prone area is located in the lower
part of the basin, with an important concentration of different urban centers and
industrial and commercial areas (including part of the Valencia International Airport).
For this reason, the analysis of damages of residential, industrial and commercial
urbanized areas is essential for the prevention of damages with a proper flood risk
management.
The approach is based on three main steps. The first step entails a detailed hydrological
analysis (parameter estimation, calibration-validation and simulations) using a distributed
rainfall-runoff model called TETIS. In the case study, on one hand, high temporal resolutions
rain gauge data are scarce, because of this, in addition to a small number of historic events,
100 synthetic rainstorms were generated using the multidimensional stochastic model
called RAINGEN, which adequately represents the main structural properties typical
of intense convective storms, including occurrence of raincells in space and time
and the generated intensities. An equivalent daily maximum precipitation Pd was
estimated for each synthetic event, thus allowing a return period assignment using the
known statistical distribution of Pd in the region. On the other hand, the initial soil
moisture condition can have a strong influence in the runoff production, for this
reason, long term daily simulation has been done in order to asses the probability
distribution of the initial situation before the extreme flood events (dry and wet
conditions). For all combinations of precipitation inputs and initial conditions, 200
hydrological simulations has been done in order to obtain the input hydrographs
for the hydraulic model. Finally in this step, a frequency analysis to obtain the
non-exceedence probability of the peak discharges has been developed using the
annual maximum daily precipitation and the initial soil moisture condition with this
expression:
--«
FX (x) = FX |r (x|r).fR (r).dr
--
where: X= random variable of interest (peak discharge), R= annual maximum daily
precipitation, fR(r)= probability density function of R, FX-r(x/r)= conditional density
function of X given r obtained from simulations.
The main objective of second step is flood hazard estimation, which, the hydraulic
modelling has been developed using the coupled computing version of Sobek 1D/2D. In
this task, the treatment of DEM calculation can be a key task depending on the
scale of work. The introduction of buildings, walls, the opening of drainage works-¦
improving the quality of results in areas with high anthropogenic influence; in our case
has been made 6 simulations with 3 different resolutions, after all, the model has
been done with a model one-dimensional (1D), logging throughout the stretch to
two-dimensional (2D) grid with the parent of 30x30 metres, except for its passage through
the urban, commercial and industrial land uses in the flood prone area where it
connects with the child grid of 10x10 metres. Unfortunately, for reasons of computer
time, the hydraulic model has not been run for the 200 available events. However,
20 events have been carefully select trying to cover the best probabilistic interest
spectrum for this study (from two to one thousand years of return period). From
the 20 selected flooding maps it has been developed a GIS computational tool for
calculating a regression between the independent variable (maximum water depth) and
the dependent variable return period transformed into natural logarithm. Using
this methodology have been generated the hazard maps for the return periods of
interest.
Finally, the third step concerns to the flood risk, which was defined as probabilistic
integral of the combination of flood hazard and land use vulnerability:
--«
R = V (h).fH (h).dh
0
Where: R is the flood risk, V(h) is the land use vulnerability, h is the flood magnitude and
fH(h) is its probability density function. The land use vulnerability is expressed in terms of
stage-damage functions for urban, commercial and industrial land uses. Both, flood hazard
and land use vulnerability are defined in terms of magnitude (water depth). This integral has
been solved in discrete form using a GIS tools. The flood risk assessment by a
resolution of 10 meters in size cell in the flood prone area of the “Rambla del Poyo” has
been done. With this useful methodology, we believe that a complete flood risk
analysis is needed in order to objectively compare different future scenarios that
can affect either the flood hazard and/or the vulnerability in the flood prone area. |
|
|
|
|
|