Determining Long-term Memory using Hurst Index for Precipitation and Discharge Time Series of Selected Stations in Ardabil Province

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MOSTAFAZADEH RAOOF; Moradzadeh Vahideh; Alaei Nazila; Hazbav Zeinab

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Journal: JOURNAL OF WATER AND SOIL RESOURCES CONSERVATION Year:2022 | Volume:11 | Issue:2 Page(s): 113-131

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Title

Determining Long-term Memory using Hurst Index for Precipitation and Discharge Time Series of Selected Stations in Ardabil Province

Author(s)

MOSTAFAZADEH RAOOF | Moradzadeh Vahideh | Alaei Nazila | Hazbav Zeinab | Issue Writer Certificate

Keywords

Climate changeQ1

Dispersion analysisQ1

Rescaling range (R/S)Q1

Time series analysisQ1

Abstract

Background and Aim: Ecosystems disturbances induced from social factors affect the environmental changes, temperature, evapotranspiration, runoff production and flow rate. In this regard, Hurst index has been used to analyze changes in hydrological processes due to various factors. The Hurst index is known as an important feature for analyzing hydrological effects. One of the most appropriate tests for long-term memory detection is the rescaling range (R/S) test. The R/S test makes it possible to calculate the self-similarity parameter H (Hurst), which measures the severity of long-term dependence over a time series. Towards this, the present study was conducted to determine the long-term memory using Hurst index for precipitation and discharge time series throughout some selected stations in Ardabil Province, NW Iran. Method: In the present study, long-term memory for annual precipitation and discharge time series (1991-2013) in 17 rain gauges stations and28 river gauge stations in Ardabil Province was assessed. The Hurst index computational values were classified into five categories from very weak to very strong in terms of dependency and scale of instability in the time series. Spatial correlation analysis of Hurst index was performed using Moran index. The Hurst index values were then interpolated by the inverse weighted distance (IDW) method in Arc Map 10. 8. Results: The results showed that the among 17 study stations, 23. 53, 29. 41, 17. 65, and 23. 53% respectively were classified in the stability scale of very weak (0. 50

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APA: Copy

MOSTAFAZADEH, RAOOF, Moradzadeh, Vahideh, Alaei, Nazila, & Hazbav, Zeinab. (2022). Determining Long-term Memory using Hurst Index for Precipitation and Discharge Time Series of Selected Stations in Ardabil Province. JOURNAL OF WATER AND SOIL RESOURCES CONSERVATION, 11(2 ), 113-131. SID. https://sid.ir/paper/416028/en

Vancouver: Copy

MOSTAFAZADEH RAOOF, Moradzadeh Vahideh, Alaei Nazila, Hazbav Zeinab. Determining Long-term Memory using Hurst Index for Precipitation and Discharge Time Series of Selected Stations in Ardabil Province. JOURNAL OF WATER AND SOIL RESOURCES CONSERVATION[Internet]. 2022;11(2 ):113-131. Available from: https://sid.ir/paper/416028/en

IEEE: Copy

RAOOF MOSTAFAZADEH, Vahideh Moradzadeh, Nazila Alaei, and Zeinab Hazbav, “Determining Long-term Memory using Hurst Index for Precipitation and Discharge Time Series of Selected Stations in Ardabil Province,” JOURNAL OF WATER AND SOIL RESOURCES CONSERVATION, vol. 11, no. 2 , pp. 113–131, 2022, [Online]. Available: https://sid.ir/paper/416028/en

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