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Comment on “Comparison of the Ability of ARIMA, WNN and SVM Models for Drought Forecasting in the Sanjiang Plain, China” by Yuhu Zhang, Huirong Yang, Hengjian Cui, and Qiuhua Chen, in Natural Resources Research DOI: 10.1007/s11053-019-09512-6

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A Brief Communication to this article was published on 04 March 2020

The Original Article was published on 03 July 2019

Abstract

We thank Zhang et al. (Nat Resour Res, 2019. https://doi.org/10.1007/s11053-019-09512-6) for investigating the accuracy of artificial intelligence techniques in the prediction of drought in China. In the paper by Zhang et al. (2019), two data-driven models, namely artificial neural network and support vector machine, and autoregressive integrated moving average (ARIMA) model were established to estimate standardized precipitation evapotranspiration index (SPEI) values. In that paper, temperature and precipitation values were used as independent variables to predict SPEI. They stated that ARIMA models give higher accuracy in the prediction of SPEI values. Here, not only some of the missing points and deficiencies in the original publication, but also improvements that can be made in future studies, were mentioned. In addition, several points are introduced in order to make these points more clarified for potential readers.

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Authors and Affiliations

  1. Hydraulics Division, Faculty of Civil Engineering, Istanbul Technical University, 34469, Istanbul, Maslak, Turkey

    Eyyup Ensar Başakın & Ömer Ekmekcioğlu

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  1. Eyyup Ensar Başakın
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  2. Ömer Ekmekcioğlu
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Correspondence to Eyyup Ensar Başakın.

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Başakın, E.E., Ekmekcioğlu, Ö. Comment on “Comparison of the Ability of ARIMA, WNN and SVM Models for Drought Forecasting in the Sanjiang Plain, China” by Yuhu Zhang, Huirong Yang, Hengjian Cui, and Qiuhua Chen, in Natural Resources Research DOI: 10.1007/s11053-019-09512-6. Nat Resour Res 29, 1465–1467 (2020). https://doi.org/10.1007/s11053-020-09638-y

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  • DOI: https://doi.org/10.1007/s11053-020-09638-y

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