A comparison of bpnn, gmdh, and arima for monthly rainfall forecasting based on wavelet packet decomposition

Wenchuan Wang, Yujin Du, Kwokwing Chau, Haitao Chen, Changjun Liu, Qiang Ma

Research output: Journal article publicationJournal articleAcademic researchpeer-review

24 Citations (Scopus)


Accurate rainfall forecasting in watersheds is of indispensable importance for predicting streamflow and flash floods. This paper investigates the accuracy of several forecasting technologies based on Wavelet Packet Decomposition (WPD) in monthly rainfall forecasting. First, WPD decomposes the observed monthly rainfall data into several subcomponents. Then, three data-based models, namely Back-propagation Neural Network (BPNN) model, group method of data handing (GMDH) model, and autoregressive integrated moving average (ARIMA) model, are utilized to complete the prediction of the decomposed monthly rainfall series, respectively. Finally, the ensemble prediction result of the model is formulated by summing the outputs of all submodules. Meanwhile, these six models are employed for benchmark comparison to study the prediction performance of these conjunction methods, which are BPNN, WPD-BPNN, GMDH, WPD-GMDH, ARIMA, and WPD-ARIMA models. The paper takes monthly data from Luoning and Zuoyu stations in Luoyang city of China as the case study. The performance of these conjunction methods is tested by four quantitative indexes. Results show that WPD can efficiently improve the forecasting accuracy and the proposed WPD-BPNN model can achieve better prediction results. It is concluded that the hybrid forecast model is a very efficient tool to improve the accuracy of mid-and long-term rainfall forecasting.

Original languageEnglish
Article number2871
JournalWater (Switzerland)
Issue number20
Publication statusPublished - 1 Oct 2021


  • Autoregressive integrated moving average
  • Back-propagation neural network
  • Group method of data handing
  • Monthly rainfall forecasting
  • Wavelet packet decomposition

ASJC Scopus subject areas

  • Geography, Planning and Development
  • Biochemistry
  • Aquatic Science
  • Water Science and Technology


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