Trend and persistence of precipitation under climate change scenarios for Kansabati basin,India |
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| Authors: | Ashok K Mishra Mehmet Özger Vijay P Singh |
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| Institution: | 1. Department of Civil, Biological and Agricultural Engineering, Texas A&M University, TX 77843‐2117, USA;2. Hydraulics Division, Civil Engineering Department, Istanbul Technical University, Istanbul 34469, Turkey |
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| Abstract: | With increasing uncertainties associated with climate change, precipitation characteristics pattern are receiving much attention these days. This paper investigated the impact of climate change on precipitation in the Kansabati basin, India. Trend and persistence of projected precipitation based on annual, wet and dry periods were studied using global climate model (GCM) and scenario uncertainty. A downscaling method based on 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 on A2 scenario and a decreasing trend in dry period precipitation based on B2 scenario. Persistence during dry period precipitation among stations varies drastically based on historical data with the highest persistence towards north‐west part of the basin. Copyright © 2009 John Wiley & Sons, Ltd. |
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| Keywords: | Bayesian neural network downscaling trend persistence precipitation |
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