Technical Notes
Jan 29, 2013

Evaluation of Rule and Decision Tree Induction Algorithms for Generating Climate Change Scenarios for Temperature and Pan Evaporation on a Lake Basin

Publication: Journal of Hydrologic Engineering
Volume 19, Issue 4

Abstract

Climate change scenarios generated by general circulation models (GCMs) have too coarse a spatial resolution to be useful in planning disaster risk reduction and climate change adaptation strategies at regional to river/lake basin scales. This paper investigates the performances of existing state-of-the-art rule induction and tree algorithms, namely, single conjunctive rule learner, decision table, M5P model tree, decision stump, and REPTree. Downscaling models are developed to obtain projections of mean monthly maximum and minimum temperatures (Tmax and Tmin) as well as pan evaporation to lake-basin scale in an arid region in India using these algorithms. The predictor variables, such as air temperature, zonal wind, meridional wind, and geo-potential height, are extracted from the National Centers for Environmental Prediction (NCEP) reanalysis data set for the period 1948–2000 and from the simulations using third-generation Canadian coupled global climate models for emission scenarios for the period 2001–2100. A simple multiplicative shift was used for correcting predictand values. The performances of various models have been evaluated on several statistical performance parameters such as correlation coefficient, mean absolute error, and root mean square error. The M5P model tree algorithm was found to yield better performance among all other learning techniques explored in the present study. An increasing trend is observed for Tmax and Tmin for emission scenarios, whereas no trend has been observed for pan evaporation in the future.

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Acknowledgments

The authors are grateful to four unknown reviewers in addition to associate editor and section editor for their insightful comments and suggestions that improved the paper.

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Go to Journal of Hydrologic Engineering
Journal of Hydrologic Engineering
Volume 19Issue 4April 2014
Pages: 828 - 835

History

Received: Nov 8, 2011
Accepted: Jan 25, 2013
Published online: Jan 29, 2013
Discussion open until: Jun 29, 2013
Published in print: Apr 1, 2014

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Authors

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Manish Kumar Goyal [email protected]
Assistant Professor, Dept. of Civil Engineering, Indian Institute of Technology, Guwahati 781039, India; Research Fellow, DHI-NTU Water and Environment Research Centre and Education Hub, School of Civil and Environmental Engineering, Nanyang Ave., Nanyang Technological Univ., Singapore 639798; and Research Scholar, Indian Institute of Technology, Roorkee 247667, India (corresponding author). E-mail: [email protected]
C. S. P. Ojha
Professor, Dept. of Civil Engineering, Indian Institute of Technology, Roorkee 27667, India.

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