Abstract
Hydrologic risk assessment studies in the context of changing climate scenario require quality information at regional scale. Commonly used general circulation models (GCMs), simulating climate impacts, have low spatial resolution. A number of statistical and dynamical downscaling approaches are available to overcome the mismatch between site resolution at which information is required and the GCM spatial resolutions. Three such statistical downscaling approaches, viz. Long Ashton Research Station-Weather Generator (LARS-WG), linear scaling (LS) and quantile mapping (QM), are used to downscale daily precipitation data from EC-EARTH model simulations under Representative Concentration Pathway (RCP) 4.5 scenario in Hemavathy River basin. It is observed that an increase in precipitation intensities and magnitudes is expected.
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