بررسی روند تغییرات دما با در نظر گرفتن ضریب هارست (مطالعه موردی: استان آذربایجان غربی)

نوع مقاله : مقالات پژوهشی

نویسندگان

• فرشاد احمدی ¹
• محمد ناظری تهرودی ¹
• رسول میرعباسی نجف آبادی ²

¹ دانشگاه آزاد اسلامی، ارومیه، ایران

² دانشگاه شهرکرد

https://doi.org/10.22067/jsw.v31i2.56035

چکیده

افزایش انتشار گازهای گلخانه‌ای در سال‌های گذشته با افزایش دما همراه بوده است. تغییرات دما از جمله عوامل مهم و تاثیرگذار در اقلیم هر منطقه بوده و به عنوان یکی از پارامترهای مهم مطالعات اقلیم‌شناسی همواره مطرح می‌باشد. در این مطالعه، روند درجه حرارت هوای استان آذربایجان‌غربی در دو مقیاس ماهانه و سالانه با استفاده از ویرایش چهارم آزمون ناپارامتری من- کندال (MK4) مورد بررسی قرار گرفت. داده‌های مورد استفاده دمای متوسط 24 ایستگاه تبخیرسنجی، در دوره آماری 1392-1360 می‌باشند. به منظور تخمین شیب خط روند، از روش تخمین‌گر شیب سن استفاده شد. نتایج نشان داد که در مقیاس سالانه، 71 درصد از ایستگاه‌های مورد بررسی (17 ایستگاه از 24 ایستگاه منتخب)، روند افزایشی معنی‌دار را در سطح اطمینان 10 درصد تجربه کرده‌اند و فقط 7 ایستگاه‌ (29 درصد از ایستگاه‌های منتخب) افزایش معنی‌دار در سری‌های درجه حرارت هوا نداشتند. بیشترین نرخ افزایش دما در مقیاس سالانه مربوط به ایستگاه چهریق با شیب (°C/Year) 12/0 بود. در مقیاس ماهانه، تعداد ماه‌ها با روند افزایشی شش برابر تعداد ماه‌ها با روند کاهشی بود. در این بین ماه‌های بهمن و اسفند بیشترین تعداد ایستگاه با روند افزایشی را به خود اختصاص داده‌اند. همچنین با توجه به مقدار شیب سن محاسبه شده، استان آذربایجان غربی در هر سال به طور متوسط 05/0 درجه سانتی-گراد (65/1 درجه سانتی گراد در طول دوره آماری مورد مطالعه) افزایش را در دمای سالانه تجربه کرده است.

کلیدواژه‌ها

• آزمون من- کندال
• سطح اطمینان
• شیب سن
• ماندگاری

عنوان مقاله [English]

Temperature Trend Analysis by Considering the Hurst Coefficient (Case Study: West Azarbayjan Province)

نویسندگان [English]

• Farshad Ahmadi ¹
• Mohammad Nazeri Tahroudi ¹
• Rasoul Mirabbasi Najaf Abadi ²

¹ Islamic Azad University, Urmia

² Shahre Kord University

چکیده [English]

Introduction: Climate change in the current century is an important environmental challenge facing the world. Increase in atmospheric concentration of greenhouse gases such as CO2 as a result of human activities has caused a change in a number of hydroclimatic parameters. Climate change and global warming are the most important issues that have attracted many attentions in recent years. Climatic changes have interpreted as significant changes in average weather over a long period (Salari and ghandomkar, 2012). Global warming may cause drastic fluctuations in various processes and also it can significantly affect mean and variance of relative humidity, precipitation, solar radiation and etc. Global warming phenomena can change the components of the hydrological cycle and re-distribute the world's water resources in time and space. This may exacerbate desertification in arid and semi-arid countries such as Iran (Ahmadi and Radmanesh, 2014). Therefore, a large part of hydroclimatic researches has focused on temperature trend analysis at different spatial and temporal scales,
Materials and Methods: In the present study, the long-term temperature data from 24 climatological stations uniformly distributed over the West Azarbayjan province during 1981-2013 were used for investigating the temperature trends. The aim of trend test is to specify whether an increasing or decreasing trend exists in time series. Since parametric tests have some assumptions such as normality, stability, and independence of variables which may not be valid for most hydrologic series, the nonparametric methods are more preferred in meteorological and hydrological studies. In addition, the nonparametric trend analysis methods are less sensitive to extreme values compared to parametric trend tests. Nonparametric tests can also be applied regardless of linearity or nonlinearity of time series trend (Khalili et al. 2015). One of the most well-known nonparametric tests is the Mann–Kendall test (Mann 1945; Kendall 1975). Existence of more than one significant autocorrelation among data is long-term persistence (LTP). The presence of LTP in time series results in the underestimation of serial correlation and overestimation of the significance of the Mann-Kendall test (Koutsoyiannis 2003). In addition, Koutsoyiannis and Montanari (2007) pointed out that the Hurst phenomenon (Hurst 1951) is one of the most major sources of uncertainty in hydrometeorological trend analysis. Hamed (2008) studied the impact of LTP and Hurst phenomenon on the Mann–Kendall test, and Kumar et al. (2009) named it as the MK4. Since the MK3 test (Mann-Kendall method after the removal of the effect of all significant auto-correlation coefficients) is a generalized version of the MK2 (Mann-Kendall method after removing the effect of significant lag-1 auto-correlation), the MK3 and MK4 tests were used in this study and explained briefly in the following sections according to Kumar et al. (2009) and Dinpashoh et al. (2014). In the current study, the MK4 test was employed.
Results and Discussion: In this study, the mean monthly and annual air temperature trends were investigated using non-parametric Mann-Kendall test by considering the Hurst coefficient (MK4) for West Azarbayjan province. The Sen's slope estimator was also used for estimation of the slope of the trend line. Results indicate that 71% of selected stations (17 stations out of 24 considered stations) experienced a significant positive trend and only 7 stations (%29 of studied stations) did not show a significant upward trend in annual temperature time series. The highest increasing temperature rate (0.12 °C/Year) in annual timescale was found in Chehriq station. On monthly time scale, the numbers of months with increasing trends were 6 times greater than those with negative trends. Most of the stations had significant positive trends in mean temperature in February and March, Moreover, according to calculated Sen's slope, the mean air temperature of West Azarbayjan province increased by 0.05 °C/Year (1.65 °C during the study period).
Conclusion: The results show that the temperature of West Azarbayjan province substantially increased. The temperature increment can cause more drought occurrence and crop yield loss. As most of people’s income in this province depends on agricultural activates, temperature rise seems to have led to many social and economic problems in our studied area. Further, drying up of Urmia Lake and decreasing water input to the Urmia Lake basin can intensify the environmental problems.

کلیدواژه‌ها [English]

• Mann-Kendall test
• Confidence level
• Sen’s Slope
• Persistence
• Hurst coefficient

مراجع

1. Abdul Aziz O.I., and Burn D.H. 2006. Trends and variability in the hydrological regime of the Mackenzie River Basin. Journal of Hydrology, 319:282–294.

2. Abghari H., Tabari H., Hosseinzadeh T. 2013. River flow trends in the west of Iran during the past 40 years: impact of precipitation variability. Global and Planetary Change, 101:52–60.

3. Ahmadi F., and Radmanesh F. 2014. Trend Analysis of Monthly and Annual Mean Temperature of the Northern Half of Iran Over the Last 50 Years. Journal of Water and Soil, 28(4): 855-865. (In Persian with English abstract)

4. Alijani B., Mahmoodi P., Saligeh M., and Righi E. 2011. Investigation of changes in the minimum and maximum annual air temperature in Iran. Geographical Research, 26(3): 101-122. (In Persian with English abstract)

5. Box J.E. 2002. Survey of Greenland instrumental temperature records: 1873–2001. International Journal of Climatology, 22(15): 1829-1847.

6. Caloiero T. 2016. Trend of monthly temperature and daily extreme temperature during 1951–2012 in New Zealand. Theoretical and Applied Climatology, 1-17.

7. Dinpashoh Y., Jhajharia D., Fakheri-Fard A., Singh VP. and Kahya E. 2011. Trends in reference crop evapotranspiration over Iran, Journal of Hydrology, 399: 422–433.

8. Fischer T., Gemmer M., Lüliu L., and Buda S. 2011. Temperature and precipitation trends and dryness/wetness pattern in the Zhujiang River Basin, South China, 1961–2007. Quaternary International, 244(2): 138-148.

9. Gocic M. and Trajkovic S. 2013. Analysis of changes in meteorological variables using Mann-Kendall and Sen's slope estimator statistical tests in Serbia. Global and Planetary Change, 100:172-182.

10. Hamed K.H. 2008. Trend detection in hydrologic data: the Mann-Kendall

trend test under the scaling hypothesis. Journal of Hydrology, 349:350–363.

11. Hamed K.H. and Rao A.R. 1998. A modified Mann–Kendall trend test for autocorrelated data. Journal of Hydrology, 204: 182–196.

12. Khalili K., Tahoudi M.N., Mirabbasi R., Ahmadi F. 2015. Investigation of spatial and temporal variability of precipitation in Iran over the last half century. Stochastic Environmental Research and Risk Assessment, 1–17.

13. Kousari M.R., Ahani H. and Hendi-Zadeh R. 2013. Temporal and spatial trend detection of maximum air temperature in Iran during 1960–2005. Global and Planetary Change, 111:97-110.

14. Koutsoyiannis D. 2003. Climate change, the Hurst phenomenon, and hydrological statistics. Hydrological Sciences Journal, 48:3–24.

15. Koutsoyiannis D., and Montanari A. 2007. Statistical analysis of hydroclimatic time series: uncertainty and insights. Water Resources Research, 43:1–9.

16. Kumar S., Merwade V., Kam J. and Thurner K. 2009. Streamflow trends in Indiana: Effects of long term persistence, precipitation and subsurface drains. Journal of Hydrology, 374: 171-183.

17. Martinez C., Maleski J. and Miller F. 2012. Trends in precipitation and temperature in Florida, USA. Journal of Hydrology, 453: 259-281.

18. Mirabbasi Najafabadi R., and Dinpashoh Y. 2012. Trend analysis of precipitation of NW of Iran over the past half of the century. Irrigation Sciences and Engineering (Scientific Journal of Agriculture). 35: 4. 60-73. (In Persian with English abstract)

19. Mondal A., Khare D., and Kundu S. 2015. Spatial and temporal analysis of rainfall and temperature trend of India. Theoretical and Applied Climatology, 122(1-2), 143-158.

20. Perez J.F., Gimeno L., Ribera P., Gallego D., Garia R., and Hernandez E. 2000. Influence of the North Atlantic oscillation on winter equivalent temperature. In: Proceedings of the AGU Chapman Conference of "The North Atlantic Oscillation", University of Vigo (Orense campus), Orense, Galicia, Spain.

21. Rio S.D., Herrero L., Pinto-Gomes C. and Peras A. 2011. Spatial analysis of mean temperature trends in Spain over the period 1961-2006. Global and Planetary change, 78: 65-75.

22. Salari A., and Gandomkar A. 2012. Forecasting temperature changes in Bandar Abbas and Qeshm island using with test Mann-kendall. Journal of Territory, 9(3):79-94. (In Persian with English abstract)

23. Tabari H., and Hosseinzadeh T. 2011. Analysis trends in temperature data in arid and semi-arid regions of Iran. Atmospheric Research, 79:1-10.

24. Vergni L., and Todisco F. 2011. Spatio-temporal variability of precipitation, temperature and agricultural drought indices in Central Italy. Agricultural and Forest Meteorology, 151(3): 301-313.

25. Wang Q., Fan X., Qin Z. and Wang M. 2012. Change trends of temperature and precipitation in the Loess Plateau Region of China, 1961–2010. Global and Planetary Change, 93:138-147.

26. Yang X.L., Xu L.R., Li C.h., Hu J. and Xia X.H. 2012. Trends in temperature and precipitation in the Zhangweinan River basin during last 53 years. Procedia Environmental Sciences, 13: 1966-1774.

27. Zamani R., Mirabbasi R., Abdollahi S., and Jhajharia D. 2016. Streamflow trend analysis by considering autocorrelation structure, long-term persistence, and Hurst coefficient in a semi-arid region of Iran. Theoretical and Applied Climatology, 1-13.