Evaluation of Various Linear Regression Methods for Downscaling of Mean Monthly Precipitation in Arid Pichola Watershed

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ISSN Print: 2158-706X
ISSN Online: 2158-7086
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E-mail: nr@scirp.org

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"Evaluation of Various Linear Regression Methods for Downscaling of Mean Monthly Precipitation in Arid Pichola Watershed"
written by Manish Kumar Goyal, Chandra Shekhar Prasad Ojha,
published by Natural Resources, Vol.1 No.1, 2010

has been cited by the following article(s):

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[4]	Climate change projection using statistical downscaling model over Chittagong Division, Bangladesh Meteorology and Atmospheric Physics, 2021 DOI:10.1007/s00703-021-00817-x

[5]	Projection pursuit regression in statistical downscaling model using artificial neural network for rainfall prediction Journal of Physics: Conference Series, 2021 DOI:10.1088/1742-6596/1872/1/012021

[6]	Selection of suitable predictors and predictor domain for statistical downscaling over the Western Himalayan region of India Theoretical and Applied Climatology, 2019 DOI:10.1007/s00704-019-02980-z

[7]	Performance of Multimodel Schemes for Seasonal Precipitation over Indian Region Advances in Meteorology, 2018 DOI:10.1155/2018/5874270

[8]	Development and Evaluation of Statistical Downscaling Models for Monthly Precipitation Earth Interactions, 2014 DOI:10.1175/EI-D-14-0024.1

[9]	Improved point scale climate projections using a block bootstrap simulation and quantile matching method Climate Dynamics, 2013 DOI:10.1007/s00382-013-1791-z

[10]	Assessment of Various Statistical Downscaling Methods for Downscaling Precipitation in Florida World Environmental and Water Resources Congress 2013, 2013 DOI:10.1061/9780784412947.105

[11]	Downscaling of surface temperature for lake catchment in an arid region in India using linear multiple regression and neural networks International Journal of Climatology, 2012 DOI:10.1002/joc.2286

[12]	PLS regression-based pan evaporation and minimum–maximum temperature projections for an arid lake basin in India Theoretical and Applied Climatology, 2011 DOI:10.1007/s00704-011-0406-z

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