Environmental Engineering Reference
In-Depth Information
are required (
10 cm vertical accuracy and 2m
spatial resolution) (Smith et al. 2006). This also
applies to the topography of the river channels
themselves. However, for modelling over urban
floodplains knowledge of the microtopography
over large areas becomes much more important,
and a vertical accuracy of 5 cm with a spatial
resolution of 0.5m is needed to resolve gaps
between buildings (Smith et al.2006).Modellers
also require a variety of features present on the
ground surface to be measured and retained as
separate GIS (geographical information system)
layers to be used for tasks such as determining
distributed floodplain roughness coefficients.
Layers of particular interest include buildings, veg-
etation, embankments, bridges, culverts and
hedges. One important use for these is for adding
to theDTMcritical features influencingflowpaths
during flooding, such as buildings, hedges and
walls. A further use is the identification and re-
moval of false blockages to flows that may be
present in the DTM, such as bridges and culverts.
Flood inundationmodels also require discharge
and stage data to provide model boundary condi-
tions. The data are usually acquired from gauging
stations spaced 10-60 km apart on the river
network, which provide input to flood warning
systems. Modellers ideally require gauged flow
rates to be accurate to 5% for all flow rates, with
all significant tributaries in a catchment gauged.
However, problems with the rating curve extrap-
olation to high flows and gauge bypassing might
mean that discharge measurement errors can be
much higher than this acceptable value during
floods. At such times gauged flow rates are likely
only to be accurate to 10% at best, and at many
sites errors of 20%will bemuchmore common. At
a few sites where the gauge installation is signif-
icantly bypassed at high flow, errors may even be
as large as 50%.
Estimates of bottom roughness coefficients in
the channel and floodplain are also required. The
role of these coefficients is to parameterize those
energy losses not represented explicitly in the
model equations. In practice, they are usually
estimated by calibration, which often results in
them compensating for model structural and
extents with DTMs, is discussed. The integration
of these observations into the models involves
quantification of model performance based on
flood extent and water levels, and consideration
of how model performance measures can be used
to develop measures of uncertainty via flood
inundation uncertainty maps. The assimilation
of water stage measurements into inundation
models is also discussed. The article concludes
by considering possible future research directions
that aim to reduce shortfalls in the capability
of current data sources to meet modellers'
requirements.
Data Requirements for Flood Inundation
Modelling
The data requirements of flood inundationmodels
have been reviewed by Smith et al. (2006). They
fall into four distinct categories:
1
topographic data of the channel and floodplain
to act as model bathymetry;
2
time series of bulk flow rates and stage data to
provide model
input and output boundary
conditions;
3
roughness coefficients for channel and flood-
plain, which may be spatially distributed;
4
data for model calibration, validation and
assimilation.
The basic topographic data requirement is for
a high-quality Digital Terrain Model (DTM) repre-
senting the ground surface with surface objects
removed. For rural floodplainmodelling,modellers
require that the DTM has vertical accuracy of
about 0.5m and a spatial resolution of at least
10m (Ramsbottom and Wicks 2003). Whilst this
level of accuracy and spatial scale is insufficient to
represent the microtopography of relict channels
and drainage ditches existing on the floodplain that
control its initial wetting, at higher flood depths
inundation is controlled mainly by the larger scale
valley morphology, and detailed knowledge of the
microtopography becomes less critical (Horritt and
Bates 2001). Important exceptions are features such
as embankments and levees controlling overbank
flow, for which a higher accuracy and spatial scale
