The conventional approach to the frequency analysis of extreme rainfall is complicated by non-stationarity resulting from climate change. In this study significant trends in extreme rainfall are detected using statistical trend tests (Mann-Kendall test and t-test) for all over the Korean Peninsula. The violation of the stationarity for 1 hour annual maximum series is detected for large part of the area especially for southwestern and northeastern regions. For stations showing non-stationarity, the non-stationary generalized extreme value (GEV) distribution model with a location parameter in the form of linear function of time makes significant improvement in modeling rainfall extremes when compared to the stationary GEV model. The Bartlett-Lewis rainfall model is used to generate annual maximum series for the purpose of generating the Intensity-Duration-Frequency (IDF) curve. Using 100 sets of 50 year synthetic annual maxima, it is found that the observed annual rainfall maximum series are reasonably represented by the model. The observed data is perturbed by change factors to incorporate the climate change scenario from the WRF (Weather Research and Forecasting) regional climate model into IDF estimates. The IDF curves for the future period 2040-2079 show highest estimates for all return periods and rainfall durations. The future IDF estimates show significant difference from the IDF estimates of the historical period (1968-2000). Overall, IDF curves show an increasing tendency over time. A historical and future climate simulation is evaluated over the Colorado River Basin using a 111-year simulation (1969-2079) of the WRF climate change scenario. We find the future projections show statistically significant increases in temperature with larger increases in the northern part of the basin. There are statistically insignificant increases in precipitation, while snowfall shows a statistically significant decrease throughout the period in all but the highest elevations and latitudes. The strongest decrease in snowfall is seen at high elevations in the southern part of the basin and low elevations in the northern part of the basin.

Issues arising from climate change and long-term natural climate variability have become the focus of much recent research. In this study, we specifically explore the impacts of long-term climate variability and climate changes upon flood frequencies. The analyses of the flood frequencies are carried out in a comparative manner in catchments located in semiarid-temperate and tropical landscapes in Australia, namely Perth, Newcastle and Darwin, using a process-based derived flood frequency approach. The derived flood frequency analyses are carried out using deterministic rainfall-runoff models that capture the intrinsic water balance variability in the study catchments, and driven by temporal rainfall event sequences that are generated by a stochastic rainfall model that incorporates temporal variabilities over a multiplicity of time scales, ranging from within-event, between-event to seasonal, multi-annual and multi-decadal time scales. Six climate scenarios are considered for Newcastle, that combine the ENSO (El Niño Southern Oscillation) and IPO (Inter-decadal Pacific Oscillation) modes of variability, and six different climate scenarios are considered for Perth and Darwin that combine these different ENSO modes and step changes in climate (upwards or downwards) that occurred in 1970 in both regions, which were identified through statistical analysis. The results of the analyses showed that La Niña years cause higher annual maximum floods compared to El Niño and Neutral years in all three catchments. The impact of ENSO on annual maximum floods in the Newcastle catchment is enhanced when the IPO is negative and for Perth, the impact of ENSO weakens in the post-1970 period, while it strengthens in Darwin in the same period. In addition, the results of sensitivity and scenario analyses with the derived flood frequency model explored the change of dominant runoff generation processes contributing to floods in each of the study catchments. These analyses highlighted a switch from subsurface stormflow to saturation excess runoff with a change of return period, which was much more pronounced in Perth and Darwin, and not so in Newcastle. In Perth and Darwin this switch was caused by the interactions between the out-of-phase seasonal variabilities of rainfall and potential evaporation, whereas the seasonality was much weaker in Newcastle. On the other hand, the combination of higher rainfall intensities and shallower soil depths led to saturation excess runoff being the dominant mechanism in Newcastle across the full range of return periods. Consequently, within-storm rainfall intensity patterns were important in Newcastle in all major flood producing events (all return periods), where they were only important in Perth and Darwin for floods of high return periods, which occur during wet months in wet years, when saturation excess runoff was the dominant mechanism. Additionally, due to the possibility of a change of process from subsurface stormflow to saturation excess when conditions suited this switch, the estimates of flood frequency are highly uncertain especially at high return periods (in Darwin and Perth) and much less in Newcastle (when no process change was involved).