Statistical Downscaling techniques for prediction of multisite rainfall in a river basin fail to capture the correlation between multiple sites and thus are inadequate to model the" />

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Title of Journal: Stoch Environ Res Risk Assess

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Abbravation: Stochastic Environmental Research and Risk Assessment

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Springer-Verlag

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DOI

10.1016/0013-4686(78)85058-0

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1436-3259

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Prediction of daily rainfall state in a river basi

Authors: S Kannan Subimal Ghosh
Publish Date: 2010/07/13
Volume: 25, Issue: 4, Pages: 457-474
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Abstract

Conventional Statistical Downscaling techniques for prediction of multisite rainfall in a river basin fail to capture the correlation between multiple sites and thus are inadequate to model the variability of rainfall The present study addresses this problem through representation of the pattern of multisite rainfall using rainfall state in a river basin A model based on Kmeans clustering technique coupled with a supervised data classification technique namely Classification And Regression Tree CART is used for generation of rainfall states from largescale atmospheric variables in a river basin The Kmeans clustering is used to derive the daily rainfall state from the historical daily multisite rainfall data The optimum number of clusters in the observed rainfall data is obtained after application of various cluster validity measures to the clustered data The CART model is then trained to establish relationship between the daily rainfall state of the river basin and the standardized dimensionallyreduced National Centers for Environmental Prediction/National Center for Atmospheric Research NCEP/NCAR reanalysis climatic data set The relationship thus developed is applied to the General Circulation Model GCMsimulated standardized bias free largescale climate variables for prediction of rainfall states in future Comparisons of the number of days falling under different rainfall states for the observed period and the future give the change expected in the river basin due to global warming The methodology is tested for the Mahanadi river basin in IndiaThe authors sincerely thank the editor Bellie Sivakumar and the two anonymous reviewers for providing constructive suggestions to improve the quality of this article The work presented in this article is partially funded by IRCC Indian Institute of Technology Bombay India Seed Grant 07IR040 and Space Technology Cell STC Indian Space Research Organization and IIT Bombay

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