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Prediction of rainfall using artificial neural networks for synoptic station of Mashhad: a case study

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Abstract

In this paper, we have utilized ANN (artificial neural network) modeling for the prediction of monthly rainfall in Mashhad synoptic station which is located in Iran. To achieve this black-box model, we have used monthly rainfall data from 1953 to 2003 for this synoptic station. First, the Hurst rescaled range statistical (R/S) analysis is used to evaluate the predictability of the collected data. Then, to extract the rainfall dynamic of this station using ANN modeling, a three-layer feed-forward perceptron network with back propagation algorithm is utilized. Using this ANN structure as a black-box model, we have realized the complex dynamics of rainfall through the past information of the system. The approach employs the gradient decent algorithm to train the network. Trying different parameters, two structures, M531 and M741, have been selected which give the best estimation performance. The performance statistical analysis of the obtained models shows with the best tuning of the developed monthly prediction model the correlation coefficient (R), root mean square error (RMSE), and mean absolute error (MAE) are 0.93, 0.99, and 6.02 mm, respectively, which confirms the effectiveness of the developed models.

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Acknowledgments

The authors gratefully acknowledge the support of the Meteorology Organization of Iran for providing the rainfall data for this case study.

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Authors and Affiliations

  1. Water Engineering Department, Ferdowsi University of Mashhad, Mashhad, Iran

    Najmeh Khalili, Saeed Reza Khodashenas, Kamran Davary & Mohammad Mousavi Baygi

  2. Department of Agriculture and Biological, Faculty of engineering, University Putra Malaysia, Serdang, Malaysia

    Fatemeh Karimaldini

Authors
  1. Najmeh Khalili
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  2. Saeed Reza Khodashenas
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  3. Kamran Davary
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  4. Mohammad Mousavi Baygi
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  5. Fatemeh Karimaldini
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Correspondence to Saeed Reza Khodashenas.

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Khalili, N., Khodashenas, S.R., Davary, K. et al. Prediction of rainfall using artificial neural networks for synoptic station of Mashhad: a case study. Arab J Geosci 9, 624 (2016). https://doi.org/10.1007/s12517-016-2633-1

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  • DOI: https://doi.org/10.1007/s12517-016-2633-1

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