This study investigated the variation of extreme precipitation on a catchment under climate change. Extreme value analysis using generalized extreme value distribution was used to characterize the extreme precipitation. Reliability ensemble average of annual maximum precipitation projections of five global climate model-regional climate model (GCM-RCM) combinations was used to analyse the precipitation extremes under the representative concentration pathways, RCPs 4.5 and 8.5. In order to tackle the nonstationarity present in the bias-corrected ensemble-averaged annual maximum precipitation series under RCPs 4.5 and 8.5, it was split in such a way that the resulting blocks were stationary. Here the analysis was performed for three blocks 2010-2039, 2040-2069 and 2070-2099, each of which were individually stationary. Uncertainty analysis was done to estimate the ranges of extreme precipitation corresponding to return periods of 10, 25 and 50 years. Results of the study indicate that the extreme precipitation corresponding to these return periods in the three time blocks under the RCPs 4.5 and 8.5 exhibit an increasing trend. Extreme precipitation for these return periods are obtained as higher for the RCP scenarios compared to that obtained using observations. Also the extreme precipitation under RCP8.5 is higher compared to that under RCP4.5 scenario.

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