4.3.8. Changes in Flood Frequency
Although a change in flood risk is frequently cited as one of the potential
effects of climate change, relatively few studies since the early 1990s (e.g.,
Nash and Gleick, 1993; Jeton et al., 1996) have looked explicitly at possible
changes in high flows. This largely reflects difficulties in defining credible
scenarios for change in the large rainfall (or snowmelt) events that trigger
flooding. Global climate models currently cannot simulate with accuracy short-duration,
high-intensity, localized heavy rainfall, and a change in mean monthly rainfall
may not be representative of a change in short-duration rainfall.
A few studies, however, have tried to estimate possible changes in flood frequencies,
largely by assuming that changes in monthly rainfall also apply to “flood-producing”
rainfall. In addition, some have looked at the possible additional effects of
changes in rainfall intensity. Reynard et al. (1998), for example, estimated
the change in the magnitude of different return period floods in the Thames
and Severn catchments, assuming first that all rainfall amounts change by the
same proportion and then that only “heavy” rainfall increases. Table
4-3 summarizes the changes in flood magnitudes in the Thames and Severn
by the 2050s: Flood risk increases because winter rainfall increases, and in
these relatively large catchments it is the total volume of rainfall over several
days, not the peak intensity of rainfall, that is important. Schreider et al.
(1996) in Australia assessed change in flood risk by assuming that all rainfall
amounts change by the same proportion. They found an increase in flood magnitudes
under their wettest scenarios—even though annual runoff totals did not
increase—but a decline in flood frequency under their driest scenarios.
| Table 4-3: Percentage change in
magnitude of peak floods in Severn and Thames catchments by the 2050s (Reynard
et al., 1998). |
 |
| |
Return Period
|
| Catchment |
2-Year
|
5-Year
|
10-Year
|
20-Year
|
50-Year
|
|
|
| Thames |
|
|
|
|
|
| – GGx-xa |
10
|
12
|
13
|
14
|
15
|
| – GGx-sb |
12
|
13
|
14
|
15
|
16
|
| |
|
|
|
|
|
| Severn |
|
|
|
|
|
| – GGx-xa |
13
|
15
|
16
|
17
|
20
|
| – GGx-sb |
15
|
17
|
18
|
19
|
21
|
|
Panagoulia and Dimou (1997) examined possible changes in flood frequency in
the Acheloos basin in central Greece. Floods in this catchment derive from snowmelt,
and an increase in winter precipitation—as indicated under the scenarios
used—results in more frequent flood events of longer duration. The frequency
and duration of small floods was most affected. Saelthun et al. (1998) explored
the effect of fixed increases in temperature and precipitation in 25 catchments
in the Nordic region. They show that higher temperatures and higher precipitation
increases flood magnitudes in parts of the region where floods tended to be
generated from heavy rainfall in autumn but decrease flood magnitudes where
floods are generated by spring snowmelt. In some cases, the peak flood season
shifts from spring to autumn. This conclusion also is likely to apply in other
environments where snow and rain floods both occur.
| Table 4-4: Computed change of 1-in-10 dry year runoff
under emission scenario IS92a between the present time (1961–90) and
2075: Influence of climate scenarios computed by two GCMs (Döll et
al., 1999). |
|
Change in Runoff between
Present and 2075
(%, decrease negative) |
Fraction of Global Land Area, where Runoff will have Changed
(%), using Climate Scenarios of |
| |
MPI
|
GFDL
|
|
| Increase by more than 200% |
8.4
|
14.4
|
| +50 to +200 |
13.4
|
34.9
|
| +10 to + 50 |
39.5
|
24.0
|
| -10 to +10 |
19.9
|
14.0
|
| -50 to -10 |
12.1
|
10.1
|
| Decrease by more than 50% |
6.7
|
2.5
|
|
Mirza et al.(1998) investigated the effects of changes in precipitation resulting
from global warming on future flooding in Bangladesh. Standardized precipitation
change scenarios from four GCMs were used for the analysis. The most extreme
scenario showed that for a 2°C rise in global mean temperature, the average
flood discharge for the Ganges, Brahmaputra, and Meghna could be as much as
15, 6, and 19% higher, respectively.
