With increasing uncertainties associated with climate change, precipitation characteristics pattern are receiving much attention these days. This paper investigated the impact of climate change oil precipitation in the Kansabati basin, India. Trend and persistence of projected precipitation based oil annual, wet and dry periods were Studied using global climate model (GCM) and scenario uncertainty. A downscaling method based oil Bayesian neural network was applied to project precipitation generated from six GCMs using two scenarios (A2 and B2). The precipitation values for any of three time periods (dry, wet and annual) do not show significant increasing or decreasing trends during 2001-2050 time period. There is likely an increasing trend in precipitation for annual and wet periods during 2051-2100 based oil A2 scenario and a decreasing trend in dry period precipitation based oil B2 scenario. Persistence during dry period precipitation among stations varies drastically based oil historical data with the highest persistence towards north-west part of the basin. Copyright (C) 2009 John Wiley & Sons, Ltd.