تحلیل روند تغییرات ایستگاهی و منطقه ای بارش نیم قرن اخیر کشور ایران

نوع مقاله : مقالات پژوهشی

نویسندگان

1 دانشگاه ارومیه

2 دانشگاه شهید چمران اهواز

چکیده

در طی دهه های اخیر، تغییر جهانی اقلیم یکی از موضوع های مهم تحقیقاتی در مطالعات محققین بوده است. بارش یکی از عناصر موثر اصلی در اقلیم هر منطقه است که در برنامه ریزی های شهری و روستایی، مکان یابی صنعتی، معماری، کشاورزی، صنایع، اقلیم منطقه و غیره نقش تعیین کننده دارد. هر چند بررسی روند داده های متوسط بارندگی در مقیاس ماهانه و سالانه صورت گرفته است، اما مطالعات کمتری در مقیاس منطقه ای وجود دارد. در این مطالعه با استفاده از داده های مقدار بارش سالانه ایستگاه های سینوپتیک 31 استان در کشور ایران در دوره آماری 2010-1961، به بررسی روند تغییرات ایستگاهی و منطقه ای بارش در سطح کشور پرداخته شده است. جهت بررسی روند پارامتر مذکور در مقیاس منطقه ای، ابتدا با استفاده از خوشه بندی فازی، ایستگاه های مورد مطالعه به 5 منطقه تقسیم و شماره گذاری شدند. سپس با استفاده از آماره کندال منطقه ای، روند تغییرات پارامتر مورد نظر در 5 منطقه و در سطح کل ایران مورد بررسی قرار گرفت. نتایج روند در هر دو مقیاس ایستگاهی و منطقه ای روند کاهشی را در شمال غرب تایید کرد. در مقیاس منطقه ای، روند کاهشی معنی دار در مناطق شمال غرب, نیمه مرکزی و جنوب غرب کشور، روند کاهشی غیرمعنی دار در مناطق غربی ایران و روند افزایشی غیرمعنی دار در مناطق شمالی و حاشیه دریای خزر مشاهده شد. بیشترین روند کاهشی بارش در مناطق شمال غرب کشور مشاهده شد که این موضوع ناشی از افزایش روند تغییرات درجه حرارت سالانه این منطقه و تغییر اقلیم ناشی از آن است.

کلیدواژه‌ها


عنوان مقاله [English]

Spatial and Regional Analysis of Precipitation Trend over Iran in the Last Half of Century

نویسندگان [English]

  • Mohammad Nazeri Tahrudi 1
  • Keivan Khalili 1
  • Farshad Ahmadi 2
1 Urmia University
2 Shahid Chamran University of Ahvaz
چکیده [English]

Introduction: Climate change has been one the most important subject in studies in the recent decades. Precipitation is an effective climatic parameter in the municipal and rural studies and in the industry, architecture, agriculture, climate and other fields. Trend analysis of average monthly and yearly rainfall investigated in many studies, but less researches probe regional rainfall analysis. In this study average yearly precipitation data measured at 31 synoptic stations of Iran in the period of 1961 to 2010 used to study regional variations of precipitation. In this order station divided to five regions by fuzzy clustering. Then, using the regional Kendall method, trend of precipitation investigated at five regions and all of Iran.
Materials and Methods: Iran with an area of over 16480000 square kilometers is situated in the northern hemisphere and southwest of Asia. Almost all parts of Iran have four seasons. In general, a year can be divided into two warm and cold seasons. Iran with range annual precipitation of 62.1-344.8 mm is located between two meridians of eastern 44° and 64° and two orbits of northern 40° and 25°. In order to investigate trend of precipitation two Mann-Kendall and Regional Kendall tests used. Also to evaluate the regional trends the Fuzzy method applied to clustering the studied region. The classic form of Mann-Kendall test has been used in many studies. The null hypothesis (no trends) is accepted when , otherwise H0 is rejected and its opposite hypothesis, i.e. the existence of a trend is accepted (5, 13). To estimate regional trend, the mean S statistic of Regional Mann-Kendall introduced that was presented by Douglas et al (7). Fuzzy Clustering: Clustering the studied area was done using the Fuzzy clustering method. One of the first clustering methods that were based on the objective function and Euclidean distance was presented by Dunn in 1974 and then was generalized by Bezdak in 1981.The FCM clustering algorithm is modified type of K-Means clustering algorithm. This algorithm minimizes the variance of clusters (1). The assumption of this algorithm is that data are in a vector space and the objective of this algorithm is to minimize the sum of variance in the D v cluster.
Results and Discussion: In this section the results of decreasing and increasing trend of annual precipitation of Iran can be observed in order to the data that recorded at provinces synoptic stations in the 1 and 5 percentage significance levels. Isfahan Synoptic station detected an increasing trend insignificant level of 5 percentages and the East Azerbaijan synoptic station followed a significant and severe decreasing trends. In order to investigate regional trend it is needed to use the clustering methods. After investigation the trend of mean annual precipitation at each station, the studied area was clustered using the Fuzzy clustering method and then the regional trend of Iran’s precipitation was evaluated. At first the number of different clusters investigated using the geographic properties and mean annual precipitation of the studied area and then with attention to the correlation of precipitation series in each cluster, five clusters selected to investigate the regional trend of precipitation. Overall the results showed that about 67 percentages of synoptic stations in center of provinces detected decreasing trend in the recent half century. Increasing the precipitation almost accrued in the center and northern part of Iran and other areas detected a decreasing precipitation trend in the studied data period that this subject is corresponded with Azerakhshi and et al (2). The observed trends over Iran and almost all stations and provinces were downward trend. This decreasing trend of precipitation also observed in Iran in the two past decades by Khalili et al (13).
Conclusion: Result showed decreasing trend in the west, north of Iran at each station and regional scale. Results indicated also a significant downward trend at northwest, central and south-west of the country, non-significant downward trend in western of Iran and non-significant upward trends in northern regions and Caspian Sea margins in the regional analysis. The most decreasing trend of precipitation observed at the north west of Iran because of increasing temperature and climate changes in the recent years.

کلیدواژه‌ها [English]

  • Clustering
  • Fuzzy method
  • Mann-Kendall
  • Regional Kendall
1- Ayvaza M.T., Karahana H., and Aral M.M. 2007. Aquifer parameter and zone structure estimation using kernel-based Fuzzy C-Means clustering and genetic algorithm. J.Hydrol.343: 3-4. 240-253
2- Azerakshi M., Farzadmehr J., Eslah M., and Sahabi H. 2013. Investigation of annual and seasonal precipitation and temperature parameters in different climate of Iran. Journal of Range and Watershed Management, Volume 66, Issue 1, page 1.
3- Brooks C.E.P., and Carrthers N. 1953. Handbook of Statistical Methods in Meteorology, London, H.M.S.O., pp 412.
4- Chen j., Wub X., Finlayson B., Webber M., Wei T., and Li M. 2014. Variability and trend in the hydrology of the Yangtze River, China: Annual precipitation and runoff. Journal of Hydrology. 513: 403-412.
5- Dinpashoh Y., Jhajharia D., Fakheri-Fard A., Singh V. P., and Kahya E. 2011. Trends in referencecrop evapotranspiration over Iran. Journal of Hydrology, 399: 422–433.
6- Dodangeh A., Nateghi M.B., Rahnema H., and Dadrasi Sabzevar A.Gh. 2014. Regional flood frequency analysis by integrating L-moments and fuzzy clustering techniques (Case study: Khorasan Razavi). J. of Water and Soil Conservation, Vol. 21(1), 2014
7- Douglas E.M., Vogel R.M., and Kroll C.N. 2000. Trends in floods and low flow in the United States: impact of spatial correlation. Journal of Hydrology. 240: 90-105.
8- Duhan D., and Pandy A. 2013. Statistical analysis of long term spatial and temporal trends of precipitation during 1901–2002 at Madhya Pradesh, India. Atmospheric Research. 122: 136-149.
9- Hirsch R.M., and Slack J.R. 1984. A nonparametric trend test for seasonal data with serial dependence. Water Resources Research, 20(6): 727-732.
10- Hirsch R.M., Slack J.R., and Smith R.A. 1982. Techniquesof trend analysis for monthly water quality data, Water Resources Research, 18(1): 107-121.
11- Jain SK., Kumar V., and Saharia M. 2013. Analysis of rainfall and temperature trends in northeast India. International Journal of Climatology. 33: 968-978.
12- Khalili K., NazeriTahrudi M., and Khanmohammadi N. 2014. Trend Analysis of Precipitation in Recent two Decades over Iran. J. Appl. Environ. Biol. Sci., 4(1s) 5-10, 2014.
13- Khalili K., Ahmadi F., Behmanesh J., and Verdinejad V. 2012. Determination of Climate Changes on Air Temperature and Shahar-Chai River in the West of Urmia Lake Using Trend and Stationarity Analysis. Irrigation Sciences and Engineering (Scientific Journal of Agriculture). 35(4): 97-107. (in Persian with English abstract).
14- Kousari MR., 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.
15- 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).
16- Rio S. D., Herrero L., Pinto-Gomes C., and Peras A. 2011. Spatial analysis of mean temperaturetrends in Spain over the period 1961-2006. Global and Planetary Change, 78: 65-75
17- Saboohi R., Soltani S., and khodagholi M. 2012. Trend analysis of temperature parameters in Iran. Theor Appl Climatol. 109: 529–547.
18- Tabar H., and Hosseinzadeh-Talaee P. 2011a. Recent trends of mean maximum and minimum air temperatures in the western half of Iran. Journal of Meteorological Atmosphere Physics, 111: 121–131.
19- Tabari H., and Hosseinzadeh-Talaee P. 2011b. Analysis trends in temperature data in arid and semi-arid regions of Iran. Atmospheric Research, 79:1-10.
20- Turkes M. 1996. Spatial and temporal analysis of annual rainfall variations in Turkey, International Journal of Climatology., 16: 1057-1076.
21- Turkes M., UtKu M.S., and Kolic G. 1995. Variations and trends in annual mean air temperature in Turkey with respect to climatic variability, International Journal of Climatology, 15: 557-569.
22- Xu Z., liu Z., Fu G., and Chen Y. 2010. Trends of major of hydro climatic variables in the Tarim River basin during the past 50 years. Journal of Arid Environments, 74: 256-267.
23- Yang X. L., Xu L. R., Li C. h., Hu J., and Xia H.X. 2012. Trends in temperature and precipitation in the Zhangweinan river basin during last 53 years. Procedia Environmental Sciences. 13: 1774-1966.
24- Zarenistanak M., Dhorde A.G., and Kripalani R.H. 2014. Temperature analysis over southwest Iran: trends and projections. Theor ApplClimatol. 116: 103-117. DOI 10.1007/s00704-013-0913-1.
25- Zhang X., Harvey K.D., Hogg W.D., and Yuzyk R. 2001. Trends in Canadian Stream flow. Water Resources Research, 37 (4): 987-99.
CAPTCHA Image