Error Correction Modelling of Wind Speed Through Hydro-Meteorological Parameters and Mesoscale Model: A Hybrid Approach (original) (raw)

Abstract

Accurate estimation of wind speed is essential for many hydrological applications. One way to generate wind velocity is from the fifth generation PENN/NCAR MM5 mesoscale model. However, there is a problem in using wind speed data in hydrological processes due to large errors obtained from the mesoscale model MM5. The theme of this article has been focused on hybridization of MM5 with four mathematical models (two regression models- the multiple linear regression (MLR) and the nonlinear regression (NLR), and two artificial intelligence models – the artificial neural network (ANN) and the support vector machines (SVMs)) in such a way so that the properly modelled schemes reduce the wind speed errors with the information from other MM5 derived hydro-meteorological parameters. The forward selection method was employed as an input variable selection procedure to examine the model generalization errors. The input variables of this statistical analysis include wind speed, temperature, relative humidity, pressure, solar radiation and rainfall from the MM5. The proposed conjunction structure was calibrated and validated at the Brue catchment, Southwest of England. The study results show that relatively simple models like MLR are useful tools for positively altering the wind speed time series obtaining from the MM5 model. The SVM based hybrid scheme could make a better robust modelling framework capable of capturing the non-linear nature than that of the ANN based scheme. Although the proposed hybrid schemes are applied on error correction modelling in this study, there are further scopes for application in a wide range of areas in conjunction with any higher end models.

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Acknowledgements

This research is funded by the Public Services Department of Malaysian Government. We also acknowledge the support from the Irrigation and Drainage Department, Malaysian Government. Many thanks are expressed to the anonymous reviewers for their valuable comments.

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Authors and Affiliations

1. WEMRC, Department of Civil Engineering, University of Bristol, Bristol, BS81TR, UK
   Asnor Muizan Ishak, Prashant K. Srivastava, Tanvir Islam & Dawei Han
2. Department of Geography, University of Hull, Cottingham Road, Hull, HU6 7RX, UK
   Renji Remesan
3. Hydrology and Water Resources Division, Department of Irrigation and Drainage, Ministry of Natural Resources and Environment, KM 7, Jalan Ampang, 68000, Kuala Lumpur, Malaysia
   Asnor Muizan Ishak

Authors

1. Asnor Muizan Ishak
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2. Renji Remesan
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3. Prashant K. Srivastava
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4. Tanvir Islam
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5. Dawei Han
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Correspondence toAsnor Muizan Ishak.

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Ishak, A.M., Remesan, R., Srivastava, P.K. et al. Error Correction Modelling of Wind Speed Through Hydro-Meteorological Parameters and Mesoscale Model: A Hybrid Approach.Water Resour Manage 27, 1–23 (2013). https://doi.org/10.1007/s11269-012-0130-1

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• Received: 08 May 2011
• Accepted: 27 August 2012
• Published: 21 November 2012
• Issue Date: January 2013
• DOI: https://doi.org/10.1007/s11269-012-0130-1

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