Comparison Of ARIMA And Local Prediction Models In Runoff Simulation(Case Study:Sofi Chai Basin)

Author

Department of Civil Engineering, Tabriz Branch , Islamic Azad University, Tabriz, Iran

Abstract

Runoff process as one of the most important hydrological processes has special importance. In the field of studying this process, several models have been used including mathematical, stochastic, statistical, conceptual and intelligence techniques based on nonlinear dynamics. In this research, the runoff process of the SofiChai basin at the entrance to the dam reservior has been studied, and the abilities of two types of time series models in simulation of runoff have been compared with each other. ARIMA as a stochastic model, and local prediction as a nonlinear dynamics model based on chaos theory have been selected to simulate runoff of the basin. The daily runoff data from date 2009/09/23 to 2014/09/22, which the last year has been considered as a test sample. The results indicate that both of the models have good and almost equal abilities to simulate runoff of the basin, and the ARIMA model with a minor difference has better performance. In ARIMA model with the best difference, R-square and RMSE are respectively 0.95,0.48. Also Runoff data with 57 delay time and 3/6 correlation dimension are high chaotic.

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References

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Water and Soil Science
Volume 34, Issue 3
August 2024
Pages 263-279

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