Severe floods are common in the Brahmani-Baitarani river basin in India. Insights into the implications of climate change on rainfall extremes and resulting floods are of major importance to improve flood risk analysis and water system design. A wide range of statistical and dynamical downscaling and bias-correction methods for the generation of local climate projections exists. Yet, the applicability of these methods highly depends on availability of meteorological data. In developing countries, data availability is often limited, either because data do not exist or because of restrictions on use. We here present a climate change analysis for the Brahmani-Baitarani river basin focusing on changes in rainfall using data from three GCMs from the Fifth Coupled Model Intercomparison Project (CMIP5) that were selected based on their performance. We apply and compare two widely used and easy to implement bias-correction methods. These were selected because reliable open historical meteorological datasets required for advanced methods were not available. The results indicate likely increases in monsoon rainfall especially in the mountainous regions and likely increases in the number of heavy rain days. We conclude with a discussion on the gap between state-of-the-art downscaling techniques and the actual options in regional climate change assessments.

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