Environmental Engineering Reference
In-Depth Information
2007; see also Chapter 5) often termed pre-processing.
Scale corrections are required as the time/space scale of
the hydrological model will not match the scale of the
meteorological model (river catchments are often only a
few hundred square kilometres and there are only 3-4 of
the weather model cells in each catchment). The simplest
downscaling method is to establish whether there are
systematic biases, for example whether the temperature
is always predicted 2 C too low, and then to correct for
those. The correction methods used can be more com-
plex statistical procedures use of an additional finer scale
model - so called local area models (Maraun et al ., 2010;
Hagedorn et al ., 2008; Hamill et al ., 2008).
distribution of possible discharges and which can be
depicted in a 'spaghetti' plot (Figure 25.3).
Themove towardsHEPS inflood forecasting represents
the state of the art in forecasting science (Thielen et al .,
2011), following on the success of the use of ensembles for
weather forecasting (Buizza et al ., 2005) and paralleling
the move towards ensemble forecasting in other related
disciplines such as climate-change predictions (Collins
and Knight, 2007). Many research studies since 2000
have shown that HEPS-based forecasts add value and can
increase warning lead times (Cloke and Pappenberger,
2009). The use of HEPS has been internationally fostered
by initiatives such as the Hydrologic Ensemble Prediction
Experiment (HEPEX), created with the aim of investigat-
ing howbest toproduce, communicate anduse hydrologic
ensemble forecasts in hydrological short-, medium- and
long-term prediction of hydrological processes (Schaake
et al ., 2007, 2010; Thielen et al ., 2008).
By counting the number of ensemble members above
a threshold and dividing by the total number of members
in the ensemble, one can compute the frequency with
which a flood level may be reached. In the example of
Figure 25.3, two out of 51 ensemble members exceed
25.2.4 Hydrological EnsemblePredictionSystems
(HEPS)
Hydrological Ensemble Prediction Systems (HEPS) use
medium-range EPS weather forecasts as meteorological
forcing for operational flood forecasting systems (Schaake
et al ., 2007; Thielen et al ., 2008; Cloke et al ., 2009; Cloke
and Pappenberger, 2009). River-discharge forecasts
are then provided as an 'ensemble' that represents the
450
Extreme warning level
400
350
300
High warning level
Medium warning level
Low warning level
250
200
150
100
Members
Observed discharge
50
0
11-10
14-10
17-10
20-10
23-10
Date
26-10
29-10
01-11
Figure 25.3 An example of an ensemble 'spaghetti' hydrograph for a hindcasted flood event. The plot shows the discharge predicted
for each ensemble member, i.e. individual forecast run (solid lines), the observed discharge (dashed black line) and four flood
discharge warning levels (horizontal dashed lines). The example is taken from the October 2007 Flood in Romania on the river Jiu as
modelled by the EFAS (Reproduced with permission from Cloke, H.L. and Pappenberger, F. (2009). Ensemble flood forecasting: a
review. Journal of Hydrology , 375, 613-25).
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