تحلیل روند سری‌های زمانی خشکسالی برای نیم‌قرن اخیر در ایران مرکزی

نویسندگان

دانشگاه کاشان

چکیده

خشکسالی به‌دلیل وسعت زیاد و طولانی‌بودن مدت اثر، تاکنون به‌عنوان پرهزینه‌ترین بلای طبیعی شناخته شده که باعث ایجاد بحران کمبود آب و مواد غذایی در مناطق متأثر از آن می‌شود. تشخیص روند داده‌های اقلیمی در مدیریت منابع آب بسیار حائز اهمیت است. در این مطالعه، تحلیل روند سری‌های زمانی بارش و خشکسالی با استفاده از آزمون ناپارامتریک من‌ـ کندال در ایران مرکزی و برای 14 ایستگاه دارای 50 سال اطلاعات آماری (1965-2014) صورت گرفت. شاخص بارش استاندارد به‌منظور بررسی خشکسالی و در مقیاس‌های زمانی مختلف 1 ،3، 6، 9، 12، 18، 24 و 48ماهه محاسبه شد. براساس نتایج به‌دست‌آمده در سطح اطمینان 95 درصد،سری‌های زمانی بارش در هیچ‌یک از ایستگاه‌ها روند معناداری از خود نشان نداد، درحالی‌که شاخص بارش استاندارد در بیش از 50 درصد از ایستگاه‌ها به‌طور معنادار روند منفی داشت. همچنین سری‌های طولانی‌مدت خشکسالی در مقیاس‌های زمانی 18، 24 و 4‌ ماهه، روند را به مراتب بهتر از سری‌های کوتاه‌مدت 1، 3، 6، 9 و 12‌ماهه نشان دادند. براساس نتایج به‌دست‌آمده می‌توان چنین استنباط کرد که شاخص خشکسالی در ایران مرکزی، به‌صورت منفی رو به افزایش است و با توجه به تغییرات اقلیمی، این روند خشکی در سال‌های آینده نیز می‌تواند ادامه یابد.

کلیدواژه‌ها


عنوان مقاله [English]

A time series analysis of drought for the last five decades in Central Iran

نویسندگان [English]

  • Abbasali Vali
  • fatemeh roustaei
چکیده [English]

Widespread and long-term effects of droughts has caused it to be known as the worst natural disaster that causes water and food deficiency in affected areas. One of the popular indexes in recognizing and monitoring of drought is Standardized Precipitation Index (SPI) that its efficiency has been approved in the world. Trend detection is very important to manage water resources. The Mann-Kendall estimator non-parametric tests are used in climatological factors trend. The SPI has been extensively applied for spatial drought analysis in various regions. Central Iran has been located among the Alborz Mountains in the north, the Zagros Mountains in the south and west, and the scattered mountains of Khorasan in the east. Because of special conditions the average annual rainfall within this area is less than 300 mm. In this study, the monthly precipitation data were obtained from Iran Meteorological Organization and after calculating SPIs in different time series (1, 3, 6, 9, 12, 24 and 48 monthly) precipitation and drought trends were investigated in all station. An investigation of precipitation and SPI drought trend was done in central Iran using Man-Kendal. The results show a significant negative trend in all station except in two stations, so it can be said that aridity in Central Iran has been increased during past five decades. Also based on achieve result in this study, long term time series can show more significant trend rather than short ones.

کلیدواژه‌ها [English]

  • Central Iran
  • Drought
  • Mann–Kendall statistics
  • SPI
Bari Abarghouei, H., Zarch, M. A. A., Dastorani, M. T., Kousari, M. R., Zarch, M. S., 2011. The survey of climatic drought trend in Iran. Stochastic Environmental Research and Risk Assessment 25, 851-863. 2. Belayneh, A., Adamowski, J., 2012. Standard Precipitation Index Drought Forecasting Using Neural Networks, Wavelet Neural Networks, and Support Vector Regression. Applied Computational Intelligence and Soft Computing 2012, 1-13. 3. Belayneh, A., Adamowski, J., Khalil, B., Ozga-Zielinski, B., 2014. Long-term SPI drought forecasting in the Awash River Basin in Ethiopia using wavelet neural network and wavelet support vector regression models. Journal of Hydrology 508, 418-429. 4. de Martonne, E., 1926. L'indice d'aridité. Bulletin de l'Association de géographes français 3, 3-5. 5. Dracup, J. A., Lee, K. S., Paulson, E. G., 1980. On the statistical characteristics of drought events. Water resources research 16, 289-296. 6. Edossa, D. C., Babel, M. S., Gupta, A. D., 2010. Drought analysis in the Awash river basin, Ethiopia. Water resources management 24, 1441-1460. 7. Ghorbani, M. (2013). The economic geology of Iran: mineral deposits and natural resources: Springer Science & Business Media. 8. Hao, Z., AghaKouchak, A., 2013. Multivariate standardized drought index: a parametric multi-index model. Advances in Water Resources 57, 12-18. 9. Hayes, M. J., Svoboda, M. D., Wilhite, D. A., Vanyarkho, O. V., 1999. Monitoring the 1996 drought using the standardized precipitation index. Bulletin of the American Meteorological Society 80, 429-438. 10. Illeperuma, G., Sonnadara, U., 2009. Forecasting Droughts using Artificial Neural Networks. Promoting Knowledge Transfer to Strengthen Disaster Risk Reduction & Climate Change Adaptation, 100. 11. Jiang, T., Su, B., Hartmann, H., 2007. Temporal and spatial trends of precipitation and river flow in the Yangtze River Basin, 1961–2000. Geomorphology 85, 143-154. 12. Kendall, M., 1975. Rank Correlation Methods. Griffin & Co, London: ISBN 0-85264-199-0. 13. Kousari, M. R., Dastorani, M. T., Niazi, Y., Soheili, E., Hayatzadeh, M., Chezgi, J., 2014. Trend detection of drought in arid and semi-arid regions of Iran based on implementation of reconnaissance drought index (RDI) and application of non-parametrical statistical method. Water resources management 28, 1857-1872. 14. Mahajan, D., Dodamani, B., 2015. Trend Analysis of Drought Events Over Upper Krishna Basin in Maharashtra. Aquatic Procedia 4, 1250-1257. 15. Mann, H., 1945. Non-Parametric Tests against Trend. Econmetrica, 13, 245-259. 16. McKee, T. B., Doesken, N. J., Kleist, J. (1993). The relationship of drought frequency and duration to time scales. Paper presented at the Proceedings of the 8th Conference on Applied Climatology. 17. Mishra, A., Desai, V., Singh, V., 2007. Drought forecasting using a hybrid stochastic and neural network model. Journal of Hydrologic Engineering. 18. Mishra, A. K., Singh, V. P., 2010. A review of drought concepts. Journal of Hydrology 391, 202-216. 19. Moradi Dashtpagerdi, M., Kousari, M. R., Vagharfard, H., Ghonchepour, D., Hosseini, M. E., Ahani, H., 2014. An investigation of drought magnitude trend during 1975–2005 in arid and semi-arid regions of Iran. Environmental Earth Sciences 73, 1231-1244. 20. Naderi, M., Raeisi, E., 2015. Climate change in a region with altitude differences and with precipitation from various sources, South-Central Iran. Theoretical and Applied Climatology. 21. Ntale, H. K., Gan, T. Y., 2003. Drought indices and their application to East Africa. International Journal of Climatology 23, 1335-1357. 22. Patel, N. R., Chopra, P., Dadhwal, V. K., 2007. Analyzing spatial patterns of meteorological drought using standardized precipitation index. Meteorological Applications 14, 329-336. 23. Raziei, T., Saghafian, B., Paulo, A. A., Pereira, L. S., Bordi, I., 2009. Spatial patterns and temporal variability of drought in western Iran. Water Resources Management 23, 439-455. 24. Sepulcre-Canto, G., Horion, S., Singleton, A., Carrao, H., Vogt, J., 2012. Development of a Combined Drought Indicator to detect agricultural drought in Europe. Natural Hazards and Earth System Science 12, 3519-3531. 25. Sneyers, R., 1990. Onstatistical analysisofseriesof observations: Technical note 143, WMO. 26. Sousa, P., Trigo, R., Aizpurua, P., Nieto, R., Gimeno, L., García Herrera, R., 2011. Trends and extremes of drought indices throughout the 20th century in the Mediterranean. Natural Hazards and Earth System Sciences 11, 33-51. 27. Tabari, H., Abghari, H., Hosseinzadeh Talaee, P., 2012. Temporal trends and spatial characteristics of drought and rainfall in arid and semiarid regions of Iran. Hydrological Processes 26, 3351-3361. 28. Tan, C., Yang, J., Li, M., 2015. Temporal-Spatial Variation of Drought Indicated by SPI and SPEI in Ningxia Hui Autonomous Region, China. Atmosphere 6, 1399-1421. 29. Zhai, L., Feng, Q., 2009. Spatial and temporal pattern of precipitation and drought in Gansu Province, Northwest China. Natural hazards 49, 1-24. 30. Zhang, X., Vincent, L. A., Hogg, W., Niitsoo, A., 2000. Temperature and precipitation trends in Canada during the 20th century. Atmosphere-ocean 38, 395-429.