The Impact of Breakpoints in Rainfall Time Series on Drought Characteristics Changes (Case Study: Tabriz and Arak Stations, Iran)

Document Type : Research Article

Authors

• M. Gaznavi ¹
• A. Mosaedi ²
• M. Ghabaei Sough ³

¹ Former M.Sc. Student of Watershed Managements, Ferdowsi University of Mashhad, Mashhad, Iran

² Professor in Water Resources Engineering, Ferdowsi University of Mashhad, Mashhad, Iran

³ Ph.D. in Water Science and Engineering, Iran Water Recourses Management Company, Tehran, Iran

10.22067/jsw.2021.14899.0

Abstract

Introduction: Drought is a climatic phenomenon and an integral part of climate fluctuations that occurs periodically and intermittently throughout the world and across all climates. However, the magnitude of this natural hazard in arid and semi-arid regions, such as most parts of Iran, is more acute due to the high sensitivity and weakness of these areas, and its effects may persist for years after the occurrence of drought. Drought is a multifaceted phenomenon as precipitation, temperature, evaporation, wind and relative humidity play important roles in the drought characteristics such as occurrence, severity, and magnitude. Climate change and global warming, and in some cases displacement of meteorological stations cause heterogeneity in time series of meteorological data. Therefore, the purpose of this study was to investigate the homogeneity and break point in precipitation time series data and the effects of a break point in drought characteristics in some synoptic stations in Iran.
Materials and Methods: In this study, homogeneity of rainfall time series data at two time scales of annual (water year) and plant growth periods in some selected synoptic stations of Iran with different climatic conditions was investigated. For this purpose, four tests including Standardized Normal Homogeneity test (SNH), Buishand’s Range test (BHR), Buishand’s U test (BUR) and Petite’s test were applied and the break points were determined. Then, at the stations with break points in the precipitation data series, the drought severity values were determined using four indices of SPI, SPEI, RDI and eRDI, for two periods, (before and after of the break points). Then drought characteristics based on Markov Chain Model and Transition probability matrix including vulnerability, reliability, reversibility and stationary of three condition of droughts (dry, normal and/or wet condition) were determined for the two time scales periods (annual and plant growth periods). Then, the differences between the characteristics for the two periods were investigated. Also, the characteristics of drought-free time intervals for the two periods based on Run’s theory were determined and compared.
Results and Discussion: Based on the homogeneity tests, precipitation data of Arak and Tabriz stations for two scales of annual and plant growth periods have break points. According to the results, in the most cases, the second period's reversibility was lower than the first period. Reliability and vulnerability also decreased and increased in all cases in the second period, respectively, compared with the first period. In most cases, there was an increase in stationary of drought in the second period relative to the first period. The rate of change in the probability of survival of the normal and wet condition in both periods was increasing and in some cases decreasing. Regarding the results of Run’s theory at the growth periods scale, the average and maximum duration of drought periods increased in all cases in the second period. The minimum, average and maximum severity of drought periods also increased in most cases in the second period. The minimum, average, and maximum values increased in most cases in the second period. On an annual basis, the number of drought periods in most cases has increased in the second period. The average and maximum duration of drought periods increased in all cases in the second period. The minimum, average, and maximum severity of drought periods also increased almost in all cases in the second period. Minimum, average, and maximum of drought magnitude values increased in most cases in the second period with respect to the first one. The minimum, average and maximum values of the drought-free durations (interval time without drought conditions) in most cases were lower in the second period. At the annual scale, the minimum duration of drought was one year in all cases and no change was found between the time slices. The average duration in most cases was lower in the second period.
Conclusion: The results show that the rainfall data of Arak and Tabriz stations have break points in the time scales of plant growth period and annual  periods. The reliability was decreasing while the vulnerability of drought was increasing in the second period, indicating an increase in drought occurrence in recent decades. Moreover, the probability of drought stability (stationary) in the second period increased in most cases. The average and maximum duration of drought periods also increased in the second period. The minimum, average, and maximum drought severity, and the minimum, average, and maximum of magnitude of drought periods were higher during the second period. In most cases, the minimum, average, and maximum of severity and magnitude of drought-free time intervals were lower in the second period. In general, difference in the characteristics of drought before and after of precipitation break point can be due to increased evapotranspiration, as a result of global warming, intensifying the effects of drought. Moreover, based on the results of the eRDI index, the climatic conditions became drier in both stations and time periods. In other words, it can be stated that the effective rainfall has decreased to some extent in recent years compared to the early years of the study period. Further studies are needed to assess the changes in drought characteristics in all synoptic stations in the country having long-term data.

Keywords

• Breakpoint
• eRDI index
• RUN theory
• Stationary
• Transition probability matrix

20.1001.1.20084757.1400.35.3.8.7

Main Subjects

• Irrigation

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References

1-       Adnan S., Ullah K., Shuanglin L., Gao S., Hayat Khan A., and Mahmood R. 2018. Comparison of various drought indices to monitor drought status in Pakistan. Journal of Climate Dynamics 51(5-6): 1885-1899.

2-       Alijani B., Ghohroudi M., and Arabi N. 2008. Developing a climate model for Iran using GIS. Theoretical and Applied Climatology 92(1-2): 103–112.

3-       Allen R.G., Pereira L.S., Rees D. and Smith M. 1998. Crop Evapotranspiration- Guidelines for Computing Crop Water Requirements. FAO Irrigation and Drainage Paper No. 56. Food and Agriculture Organization of the United Nations. ISBN 92-5-104219-5.

4-       Bahlake M., Fathabadi A., Rouhani H., and Seyedian S.M. 2018. The effect of climate change on wet and dry period’s characteristics (Case study: Arazkuse and Tamar stations in Golestan Province). Scientific Journal of Agricultural Meteorology 5(2):11-23. (In Persian with English abstract)

5-       Bazgeer S., Abbasi F., Asadi Oskoue E., Haghighat M., and Rezazadeh P. 2019.  Assessing the Homogeneity of Temperature and Precipitation Data in Iran with Climatic Approach. Journal of Spatial Analysis Environmental Hazards 6(1): 51-70. (In Persian with English abstract)

6-       Bazrafshan O., Mahmudzadeh F., and Bazrafshan J. 2016. Evaluation of temporal trends of the drought indices SPI and SPEI in the Southern Coast of Iran. Journal of Desert Management 4(7-8): 54-69. (In Persian with English abstract)

7-       Byakatonda J., Parida B.P., Moalafhi D.B., and Kenabatho P. 2018. Analysis of long term drought severity characteristics and trends across semiarid Botswana using two drought indices. Atmospheric Research 213(2018): 492-508

8-       Duan J., Zhao L., Wang Q., and Li P. 2019. Detecting breakpoints in global temperature, Earth System Dynamics 10: 1-12

9-       Eghtedar Nezhad M., Bazrafshan O., and Bazrafshan J. 2017. Spatio-temporal variations of meteorological drought using Standardized Precipitation Evapotranspiration Index in Iran. Scientific Journal of Agricultural Meteorology 5(2): 35-46. (In Persian with English abstract)

10-   Ghabaei Sough M., Zare Abyaneh H., Mosaedi A., and Samadi, S.Z. 2016. Assessment of humidity conditions and trends based on Standardized Precipitation Evapotranspiration Index (SEPI) over different climatic regions of Iran. Journal of Water and Soil (Agricultural Science and Technology) 30(5): 1700-1717. (In Persian with English abstract)

11-   Ghabaei Sough M., and Mosaedi A. 2018. Analysis of trends and breakpoints in precipitation values in some Watersheds of Iran. 7^th National Conference of Water Resources Management of Iran, 24-25 October. 2018. Yazd University. (In Persian)

12-   Ghorbani Kh., Valizadeh E., and Bararkhanpoor S. 2018. Investigation of spatiotemporal trend of the bivariate meteorological drought index, SPEI, in Iran. Journal of Desert Management 6(11): 25-38. (In Persian with English abstract)

13-   Ghorbani Kh., Bararkhan Poor S., Valizadeh E., and Molaarazi A.J. 2020. Regional analysis of trend and change point in seasonal series of SPEI drought index in Iran. Journal of Water and Soil Conservation 27(4): 185-200. (In Persian with English abstract)

14-   Guo H., Bao A., Liu T., Jiapaer G., Ndayisaba F., Jiang L., Kurban A., and De Maeyer P. 2018. Spatial and temporal characteristics of droughts in Central Asia during 1966-2015. Journal of Science of the Total Environment 624: 1523-1538.

15-   Isaacson DL., and Madsen R. 1976. Markov Chains: Theory and Applications. John Wiley, New York.

16-   Kwarteng F., Shwetha G., and Patil R. 2016. Reconnaissance Drought Index as potential drought monitoring tool in A Deccan Plateau, hot semi-arid climatic zone. International Journal of Agriculture Sciences 51(8): 2183-2186.

17-   Liu Z., Wang Y., Shao M., Jia X., and Li X. 2016. Spatiotemporal analysis of multiscalar drought characteristics across the Loess Plateau of China. Journal of Hydrology 534: 281-299.

18-   Lin H., Wang J., Li F., Xie Y., Jiang C., and Sun L. 2020. Drought trends and the extreme drought frequency and characteristics under climate change based on SPI and HI in the upper and middle reaches of the Huai river basin, China. Water 12(4): 1100.    

19-   Mahmoudi P., Rigi A., and Miri Kamak M. 2019. A comparative study of precipitation-based drought indices with the aim of selecting the best index for drought monitoring in Iran. Journal of Theoretical and Applied Climatology 137(3-4): 3123–3138.

20-   Majidi A., Radfar M., Mirabbasi Najafabadi R., and Marofi S. 2018. Analysis of trend Properties of meteorological droughts in Hamedan province. Journal of Watershed Management Research 9(17): 295-305. (In Persian with English abstract)

21-   McKee T.B., Doesken N.J., and Kleist J. 1993. The relationship of drought frequency and duration to time scales. Proceeding, 8th Conference on Applied Climatology. January 17-22. JanuaryAnaheim, California.

22-   Moghimi M.M., Kouhi E., and Zarei A.R. 2018. Drought Monitoring and Forecasting, using RDI Index and Markov Chain Mathematical Model. Journal of Irrigation and Water Engineering 8(3): 153-165. (In Persian with English abstract)

23-   Mosaedi M., Mohammadi Moghaddam S., and Kavakebi Gh. 2017. Drought characteristics based on Reconnaissance Drought Index and its variations in different time periods and regions of Iran. Journal of Water and Soil Conservation 23(6): 27-52. (In Persian with English abstract)

24-   Mousavi Baigi M., and Ashraf B. 2018. Weather and Climate in Agriculture. Ferdowsi University of Mashhad Press. (In Persian)

25-   Nouri M., Homaee M., and Bannayan M. 2018. Analyzing the trends of precipitation and drought in some semi-arid to humid regions of Iran. Journal of Water and Soil Science 22(1): 45-60. (In Persian with English abstract)

26-   Parsamehr A.H., Mobin M.H., and Khosravani Z. 2018. Using Run theory to analysis of drought severity – duration – return period (case study: Fars province). Iranian Journal of Ecohydrology 5(2): 471-481. (In Persian with English abstract)

27-   Pei Z., Fang S., Wang L., and Yang W. 2020. Comparative analysis of drought indicated by the SPI and SPEI at various timescales in Inner Mongolia, China. Water 12(7): 1925.

28-   Pirnia A., Golshan M., Bigonah S., and Solaimani K. 2018. Investigating the drought characteristics of Tamar basin (upstream of Golestan Dam) using SPI and SPEI indices under current and future climate conditions. Iranian Journal of Ecohydrology 5(1): 215-228. (In Persian with English abstract)

29-   Salehpour Jam A., Tabatabaei M., Sarreshtehdari A., and Mosaffaie J. 2018. Investigation of drought characteristics in northwest of Iran using deciles index. Journal of Watershed Engineering and Management 10(4): 552-563. (In Persian with English abstract)

30-   Steinman A. 2003. Drought Indicators and Triggers: A stochastic approach to evaluation. Journal of the American Water Resources Association 39(5): 1217-1233.

31-   Thomas T., Jaiswal R.K., Galkate R.V., and Nayak T.R. 2016. Reconnaissance drought index based evaluation of meteorological drought characteristics in Bundelkhand. Journal of Procedia Technology 24: 23-30.

32-   Tigkas D., Vangelis H., and Tsakiris G. 2017. An enhanced effective Reconnaissance Drought Index for the characterisation of agricultural drought. Environmental Process 4(1): 137–148.

33-   Tsakiris G., and Vangelis H. 2004. Towards a drought watch system based on spatial SPI. Water ResourcesManagement 18:1-12.

34-   Vicente-Serrano S.M., Beguería S., and López-Moreno J.I. 2010. A multi-scalar drought index sensitive to global warming: the standardized precipitation evapotranspiration index. Journal of Climate 23(7): 1696-1718.

35-   Vicente-Serrano S.M., L´opez-Moreno J.I., Gimeno L., Nieto R., Mor´an –Tejeda E., Lorenzo-Lacruz J., Beguer´ıa S., and Azorin-Molina C. 2011. A multiscalar global evaluation of the impact of ENSO on droughts. Journal of Geophysical Research: Atmospheres 116: 1-9.

36-   Yan-Jun I., Xiao-dong Z., Fan L., and Jing MA. 2012. Analysis of drought evolvement characteristics based on standardized precipitation index in the Huaihe river basin. Journal of Procedia Engineering 28: 434-437.

37-   Zarei A.R., Moghimi M.M., and Bahrami M. 2019. Comparison of reconnaissance drought index (RDI) and effective reconnaissance drought index (eRDI) to evaluate drought severity. Sustainable Water Resources Management 5(3): 1345-1356.