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
a GGx-x = HadCM2 ensemble mean scenario with proportional change in rainfall. b GGx-s = HadCM2 ensemble mean scenario with change in storm rainfall only.

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.

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