Meteorological Drought Risk Assessment Using Markov Chain Technique and Introducing a Forecasting Model of Future Periods Impacted by Climate Change (Case Study: Afrin Catchment)

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Article Type:
Case Study (دارای رتبه معتبر)
Abstract:

Drought is one of the natural and recurring climatic phenomena that has various effects on different economic, social and environmental sectors. Drought alone is not a challenge Rather It is the beginning of a crisis depending on the degree of vulnerability and impact it has on various sectors, including economic, social, and environmental factors. Therefore, this study has attempted to calculate the risk of drought for the baseline period using natural risk definition and estimate the best model for predicting its rate for future periods affected by different methods under climate change. Accordingly, was calculated drought risk using the two meteorological drought indices SPEI and eRDI the for years 1983-2015. Then, was determined the degree of vulnerability for the Afin area using a questionnaire. After estimating the risk during this time period, with the help of Markov chain statistical technique were obtained the drought risk characteristics of the region. Using the four modeling methods was determined the best drought risk prediction model and by using the meteorological variables studied from the three climate models of the CORDEX project was predicted the drought risk for the years 2020-2100. The results of this study showed a decrease in risk for 2020-2046 and an increase in 2047-2000 based on both RCP4.5 and RCP8.5 compared to the period 1983-1995.

Language:
Persian
Published:
Iranian Journal of Irrigation & Drainage, Volume:14 Issue: 4, 2020
Pages:
1107 to 1120
https://www.magiran.com/p2196820  
سامانه نویسندگان
  • Kavakebi، Ghazale
    Author (1)
    Kavakebi, Ghazale
    .Ph.D Department of Water Engineering, Ferdowsi University, مشهد, Iran
  • Mosaedi، Abolfazl
    Author (4)
    Mosaedi, Abolfazl
    Professor Water Science and Engineering Department, Ferdowsi University, مشهد, Iran
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