Analyzing the Dynamics of Precipitation Frequency and its Prediction in North-western Iran Based on Chaos Theory

Document Type : Research Paper

Authors

1 Researcher of Soil Conservation and Watershed Management Department, Zanjan Agricultural and Natural Resources Research Center, AREEO, Zanjan, Iran,

2 Professor of Climatology, Geography Department, University of Zanjan, Zanjan, Iran

Abstract

Precipitation is one of the most important climate variables. However, the complex nature of precipitation makes it difficult to analyze its behavior and predict it. In this study, the dynamics of precipitation frequency in Northwestern Iran in 1970-2019 has been investigated using chaos theory, and its frequency has been predicted for the 2020-2036. The data used is precipitation grided data obtained from the interpolation of data from 219 stations. To investigate the dynamics of precipitation, average mutual information methods, Cao, the correlation dimension, and the largest Lyapunov exponent were used. A nonlinear method was used to predict the precipitation frequency. The result showed that the delay time and embedding dimension for reconstructing the phase space are 3 and 8, respectively. The correlation dimension and the largest Lyapunov exponent indicate that the frequency of monthly precipitation was chaotic. In addition, data analysis using the Hurst method revealed that the monthly frequency of precipitation in Northwestern Iran has a long-term memory. In addition, based on the prediction, the frequency of annual precipitation will decrease by 13.2% in the next period. The largest decreases are predicted in July and August. Apart from this, the frequency of precipitation will decrease in all seasons of the year; So that the greatest reduction will occur in the summer, then in the cold season, and the least reduction will occur in the spring.

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Main Subjects

References

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Geography and Development
Volume 24, Issue 84 - Serial Number 84
September 2026
Pages 197-220

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History

  • Receive Date: 27 November 2024
  • Revise Date: 15 May 2025
  • Accept Date: 18 May 2025

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