Multi-Dimensional Rainfall Risk for Hydropower Dam Safety from Extreme-Weighted CMIP6 Ensembles Across the Mekong Basin

Climate change affects the intensity of extreme rainfall, which is an important factor for design flood assessment and dam safety, particularly in the monsoon region of Southeast Asia and the Mekong Basin, where seasonal rainfall variability is high and there are many hydropower dams that are vulnerable to changes in severe rainfall. This study develops a framework for assessing design rainfall and Probable Maximum Precipitation (PMP) under climate change for three dam catchments of different sizes in Thailand and Lao PDR, namely the Ubolrat Dam, the Nam Theun 1, and the Nam Kong 3 Dam. The framework connects the bias correction of GCM data from ten CMIP6 models using CMhyd, extreme-focused model selection with catchment-specific ranking, and the construction of the Top-3 Ensemble median, through to the analysis of the Return Period, DDF, IDF, PMP, and extreme rainfall trends under the SSP24.5 and SSP58.5 scenarios. The results show that the suitable models are catchment-specific, and that each catchment has a different risk profile under SSP58.5. The UB shows a 63.20% increase in the 100-year 1-day rainfall, the Nam Theun 1 shows a 40.64% increase in the 100-year 7-day rainfall, while the Nam Kong 3 has the highest PMP value and the steepest Rx7day trend at 18.03 mm per decade. The results indicate that the assessment of extreme rainfall risk must consider magnitude, variability, and trend together, and the outputs can serve as input data for the assessment of PMF and hydropower dam safety under future climate variability.