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Examination of Various Feature Selection Approaches for Daily Precipitation Downscaling in Different Climates

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Abstract

To turn General Circulation Models (GCMs) projection toward better assessment, it is crucial to employ a downscaling process to get more reliability of their outputs. The data-driven based downscaling techniques recently have been used widely, and predictor selection is usually considered as the main challenge in these methods. Hence, this study aims to examine the most common approaches of feature selection in the downscaling of daily rainfall in two different climates in Iran. So, the measured daily rainfall and National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) predictors were collected, and Support Vector Machine (SVM) was considered as downscaling methods. Also, a complete set of comparative tests considering all dimensions was employed to identify the best subset of predictors. Results indicated that the skill of various selection methods in different tests is significantly different. Despite a few partial superiorities viewed between selection models, they not presented an obvious distinction. However, regarding all related factors, it may be deduced that the Stepwise Regression Analysis (SRA) and Bayesian Model Averaging (BMA) are better than others. Also, the finding of this study showed that there are some weaknesses in the interpretation of SRA, so concerning this issue, it may be concluded that BMA has more reliable performance. Furthermore, results indicated that generally, the downscaling procedure has more accuracy in arid climate than cold-semi arid climate.

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Data Availability

The authors confirm that all data supporting the findings of this study are available from the corresponding author by request.

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Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

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Authors and Affiliations

  1. Department of Water Engineering, University of Birjand, Birjand, Iran

    Ahmad Jafarzadeh, Mohsen Pourreza-Bilondi & Abbas Khashei Siuki

  2. Department of Water Engineering, Faculty of Agriculture and Natural Resources, University of Mohaghegh Ardabili, Ardebil, Iran

    Javad Ramezani Moghadam

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  1. Ahmad Jafarzadeh
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  2. Mohsen Pourreza-Bilondi
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  3. Abbas Khashei Siuki
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  4. Javad Ramezani Moghadam
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Contributions

All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by Jafarzadeh, Ahmad, Pourreza Bilondi, Mohsen, Khashei Siuki, Abbas, and Ramezani Moghadam, Javad. The first draft of the manuscript was written by Jafarzadeh, Ahmad and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

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Correspondence to Ahmad Jafarzadeh.

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Jafarzadeh, A., Pourreza-Bilondi, M., Khashei Siuki, A. et al. Examination of Various Feature Selection Approaches for Daily Precipitation Downscaling in Different Climates. Water Resour Manage 35, 407–427 (2021). https://doi.org/10.1007/s11269-020-02701-6

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