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

Subject Areas : Farm water management with the aim of improving irrigation management indicators

Raoof Mostafazadeh ¹ , Vahideh Moradzadeh ² , Nazila Alaei ³ , Zeinab Hazbavi ⁴

1 - Associate Professor, Department of Natural Resources, Faculty of Agriculture and Natural Resources, Water Management Research Center, University of Mohaghegh Ardabili, Ardabil, Iran.
2 - M.Sc. Student, Department of Natural Resources, Faculty of Agriculture and Natural Resources, University of Mohaghegh Ardabili, Ardabil, Iran.
3 - Ph.D. Student Watershed Management Science and Engineering, Faculty of Natural Resources, Urmia University, Urmia, Iran.
4 - Assistant Professor, Department of Natural Resources, Faculty of Assistant Professor, Department of Natural Resources, Faculty of Agriculture and Natural Resources, Water Management Research Center, University of Mohaghegh Ardabili, Ardabil, Iran.

Received: 2021-09-29 Accepted : 2021-12-18 Published : 2021-12-22

Keywords: Time series analysis, Rescaling range (R/S), Climate Change, Dispersion analysis,

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<H<0.55), relatively weak (0.55<H<0.65), relatively strong (0.65<H<0.75), and strong (0.75<H<0.80). Meanwhile, only 5.88% including Shamsabad station were classified as very weak (0.45<H<0.55) in terms of instability scale. According to the analysis of 28 hydrometric stations, 25, 50, and 21.42% were respectively relatively weak, relatively strong, and strong, and 3.58% were very weak on the instability scale, respectively. In the meantime, only the Amuqin Station was categorized with very poorly scale. According to the results of Hir, KoozehTapraghi, Shamsabad and Ahmadkandi rain gauge stations, a positive value of Moran index was found indicating similar values in terms of location. In the other stations, the Moran index values are negative, inficating non-similar valuses and no clusters were formed. The results of clustering in hydrometric stations showed that Iril Station was in the high-high clusters and the Atashgah Station was classified in the low-low clusters and positive values of Moran index. The rest of the study stations did not form specific clusters.Conclusion: The results showed that the Hurst index was obtained for the rainfall stations with an average of 0.64 and a standard deviation of 0.11. The Hurst index was also obtained in hydrometric stations with an average of 0.74 and a standard deviation of 0.12. In general, the range of Hurst index values and its spatial variations on annual precipitation data showed that precipitation values in the study period are not stable. Spatial changes of the mentioned indicators showed that there is a clear difference between different regions of the province in terms of stability of precipitation and discharge. However, according to the box diagram, amplitude of changes and spatial distribution of stations with strong and relatively strong stability, most stations located in the central part of the province have stability in discharge values, which can indicate the continuation of water currents and the occurrence of maximum discharges.

References:

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