Meteorological drought monitoring in order to sustainability in RCP scenarios Case study: Doiraj watershed

Document Type : Research Article

Authors

1 Assistant Professor at Razi University, Water Engineering Department

2 MSC student of water resources engineering, Razi university

Abstract

The aim of this study is to preserve the sustainability of the Doiraj watershed in RCP scenarios. The observation and future period in this study is (1987-2015) and (2044-2016). For this purpose, the combined weight of 5 models of Fifth Report (AR5), rcp8.5 scenario, used to assess changes in temperature and precipitation in the coming period. MOTP weighting method to reduce uncertainty of GCM models were used Meteorological drought monitoring in monthly, Seasonal and yearly intervals using Markov chain, frequency analysis and drought indexes SIAP, SPI, Z score and BMDI was calculated. The results showed that long-term average monthly rainfall and temperature at a rate of 14 percent and 2.1 degrees Celsius as compared to the baseline. Markov chain probability of uncertainty precipitation showed, two months without precipitation in winter, spring and autumn, respectively 56, 63 and 52 percent and the chance of precipitation after a month of dry seasons, respectively 44, 35 and 47 percent. Based on the analysis of the indices during the years 2017-2018 than in 2016-2017 wetter and future years in the period 2024-2025 and 2025-2026 wettest years on the basis of this research.

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Main Subjects

References

[1]-Mansouri B, Ahmadzadeh, Hojat. Masah Bavani, Alireza. Morid Said. Delavar, Saeeid. The effects of climate change on water resources basin model SWAT. Journal of Agricultural Science and Technology. 2014; 28(6): 1191-1203. [Persian].
[2]- Li Z, Liu WZ,Zhang X C, and Zheng F. Impact of land use change and climate variability on hydrology in an agriculture cathment on the Loess Plateau of China. Journal of Hydrology.2009; 377: 35-42.
[3]- Masah Bavani A. Risk assessment of climate change and its impact on water resources, watershed case study of Zayandehrood. Ph.D. Thesis. Said Morid (Help). School of Agriculture. Tarbiat Modares University.2006 [Persian].
 [4]- Gellens D, and Roulin E. Stream flow response of Belgian to IPCC climate change scenarios. J.Hydrol, 1998. PP: 210-258.
[5]-Asefjah B, Fanian Z, Abollhasani A, Paktinat H, Naghilou M, Molaei A, Asadollahi M, Babakhani M, Kouroshniya A, Salehi F. Meteological drought monitoring using several drought indices case study: Salt Lake Basin in Iran. Desert 19-2. 2014. pp155-165
[6]- Sayari N, Bannayan M, Alizadeh A, and Farid A. Using drought indices to assess climate change impacts on drought conditions in the northeast of Iran(case study: Kashafrood basin). Meteorological Applications Meteorol. Appl. 2013; 20: 115-127.
[7]-Jong T.A,Yuk F, Hung YongJ.T, Mirzaei M, Z. Drought Forecaasting Using SPI and EDI under RCP8.5 Climate Change Scenarios for Langat River Basin, Procedia Engineering. 2016; 154: 710–717.
[8]-Nozar GH, Babaeian I, Tabatabai, SMR. After evaluating the data output processing dynamic climate models to estimate potential evapotranspiration changes in radiative forcing scenarios (Case Study: Mashhad plain). Journal of Earth and Space Physics. 2016; 42(3): 687-696. [Persian].
[9]-NozarGH, Babaeian I, Tabatabai SMR. The effects of climate change on water requirement and duration of growth of the sugarcane under radiative forcing scenarios. Journal of Water and Soil Conservation. Year 6. 2016; (1). [Persian].
[10]-Aghakhani A, Hassanzadeh AH, Bsalt Pour Y, Pour Reza AA, Bilandi M. Seasonal changes in precipitation and temperature explore the river basin approach in future periods circulation models CMIP5. Journal Agricultural Science and Technology.2016; 30(5): 1732-1718. [Persian]
[11]- Sorin LD, Madalina G, Roxana B, Marius VB, Roxana C, Ruxandra V, Mary JA, Viorel CH. Drought-related variables over the Bârlad basin (Eastern Romania) under climate change scenarios, Elsevier. doi.org/10.1016/j.catena.2016.02.018. 2016; 141: 92-99
 [12]-Siahi S, Shahbazi A, Khademi k. The prediction of the effect of variation on monthly runoff of the Dez Dam basin using the IHACRES model. Quarterly journal of water science and engineering. Islamic Azad University of Ahvaz. Seventh year. 2017; 15.
[13]- Kotsuki S, Tanaka K, and Watanabe S. Projected hydrological change and their consistency under future climate in the Cho Phrya River Basin using multi-model and multi scenario of CMIP5 dataset. Hydrological Research Letters. 2014; 8(1): 27-32.
[14]-Aich V, Liersch S, Vetter T, Huang S, Tecklenburg J, Hoffmann P, Koch H, Fournet S, Krysanoval V, Muller EN, and Hattermann FF. Comparing impact of climate change on streamflow in four large African river basins. Hydrology and Eratth System Sciences, 2014; 18(4):1305-1321.
[15]- Chiyuan M, Qingyun D, Qiaohong S, Huang Yong H, Kong D, Tiantian Y, Aizhong Ye, Zhenhua Di, Gong W. Assessment of CMIP5 climate models and projected temperature changes over Northern Eurasia.Environmental Research Letters. 2014; (9):5.
[16]-Alizadeh A, Principles Applied Hydrology. Published twenty-fifth. Press Astan Quds Razavi. 2008. [Persian].
[17]-Mohammadi H, KHazaei M, Mahonchi E, Abasi MH. Analysis of the Frequency and duration of rainy days in Shiraz using Markov chain model. Journal of Geographic Information. 2015; 24(93): 77-90. [Persian].
[18]-Khalili D. Challenges facing the management of water resources in drought conditions in Iran. Journal of Agricultural Sciences and Natural Resources strategy. 2016. PP: 164-149. [Persian].
[19]-Gol Mohammadi M, Masah Bavani A. Assessment of changes in the intensity and recurrence of drought in the basin Soo future periods affected by climate change. Water and Soil magazine (Science and Agriculture). 2011; 5(2): 315-326. [Persian].
[20]-Saligheh M, Alijani B, DelAra GH. Wet Season is spatial analysis using Markov Chain Model (Case Study of Ardebil). Applied Geographical Sciences Research. 2011. PP: 25-44. [Persian].
[21]-Hanafi A, Khosh Akhlagh F, Soltani M. Drought analysis and forecast of Tehran using SPI index upon Markov chain model. Journal of Geography and environmental sustainability. 2012; (3): 87-100. [Persian].
[22]-Raziee T. Predicted droughts in arid and semiarid regions of Iran using time series models and Markov chain. Journal of Research Engineering and watershed management. 2016. PP: 454-477. [Persian].
[23]- Teymoori J, Teymoori M. Check the interactions between climate change and drought in Ilam province (Case study: city DEHLORAN). First National Conference on Agriculture, Environment and Food Security. Jiroft University. 2014. [Persian]
[24]- Borna R, Azimi F, Saeedi D. Markers SIAP, PN and RAI review droughts in Abadan and Dezful in Khuzestan province with an emphasis on stations. Journal natural geography. third year. 2010; (9): 88-77. [Persian].
[25]- Heidary H, Moradi H, Asghar S, Mohammad Nejad V. Examine temporal trends of temperature and precipitation in the region of Ilam using the non parametric Mann-Kendall method. First National Conference on Geography, tourism, natural resources and sustainable development. 2014. [Persian].
[26]-Kamari H, Nori A. Assessment return period rainfall using data from annual precipitation (case study: the city of Kermanshah). Journal of Research in Science, Engineering and Technology. 2016. PP: 25-35. [Persian].
Iranian journal of Ecohydrology
Volume 4, Issue 4
January 2018
Pages 1227-1239

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History

  • Receive Date: 04 April 2017
  • Revise Date: 16 August 2017
  • Accept Date: 21 August 2017
  • First Publish Date: 22 December 2017
  • Publish Date: 22 December 2017

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