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Multi-models for SPI drought forecasting in the north of Haihe River Basin, China

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Abstract

Drought is one of the most devastating climate disasters. Hence, drought forecasting plays an important role in mitigating some of the adverse effects of drought. Data-driven models are widely used for drought forecasting such as ARIMA model, artificial neural network (ANN) model, wavelet neural network (WANN) model, support vector regression model, grey model and so on. Three data-driven models (ARIMA model; ANN model; WANN model) are used in this study for drought forecasting based on standard precipitation index of two time scales (SPI; SPI-6 and SPI-12). The optimal data-driven model and time scale of SPI are then selected for effective drought forecasting in the North of Haihe River Basin. The effectiveness of the three data-models is compared by Kolmogorov–Smirnov (K–S) test, Kendall rank correlation, and the correlation coefficients (R2). The forecast results shows that the WANN model is more suitable and effective for forecasting SPI-6 and SPI-12 values in the north of Haihe River Basin.

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Acknowledgements

Support was provided by the National Science and Technology Support Plan during the 12th Five-year Plan Period of China (Nos. 2012BAC19B03 and 2013BAC10B01) and the Natural Science Fund of China (41201331 and 41071020). It is realized as a part of the Project “Statistical Analysis and Information Extraction of High-dimensional Complicate Data” jointly funded by Scientific Research Project of Beijing Educational Committee (No. KZ201410028030).

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Authors and Affiliations

  1. College of Resource Environment and Tourism, Capital Normal University, Beijing, 100048, China

    Yuhu Zhang, Xiao Pu & Liu Xiang

  2. Beijing Laboratory of Water Resource Security, Beijing, 100048, China

    Yuhu Zhang & Xiao Pu

  3. School of Mathematical Sciences, Capital Normal University, Beijing, 100048, China

    Weiwei Li & Qiuhua Chen

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  1. Yuhu Zhang
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  2. Weiwei Li
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  3. Qiuhua Chen
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Correspondence to Weiwei Li.

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Zhang, Y., Li, W., Chen, Q. et al. Multi-models for SPI drought forecasting in the north of Haihe River Basin, China. Stoch Environ Res Risk Assess 31, 2471–2481 (2017). https://doi.org/10.1007/s00477-017-1437-5

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