Studying the Effect of Climate Change on Drought Conditions and Climate Regions of Iran Using Aridity Index
Subject Areas : Water resources managementasghar azizian 1 , Marzieh Hosseini 2
1 - Associate Professor, Water engineering Dept., Imam Khomeini International University (IKIU), Qazvin, Iran
2 - MSc in Water Resources Engineering, Water engineering Dept., Imam Khomeini International University (IKIU), Qazvin, Iran.
Keywords: Aridity Index, Hottest quarter, Driest quarter, Coldest quarter, Wettest quarter,
Abstract :
Background and Aim: One of the consequences of climate change is the occurrence of extreme events such as drought, which is important to identify, monitor, evaluate, and inform about the occurrence conditions. In this study, the effects of climate change on the drought situation in the near future (2021-2040), mid-term (2041-2060), and long-term (2061-2080) have been discussed using the Aridity Index estimated by the Copernicus Climate Change Database with the use of GFDL-ESM2M climate model output under RCP4.5 and RCP8.5 scenarios.Method: In the current research, climate data simulated by the Copernicus database is used to calculate the Aridity Index of different parts in various time horizons. Mann-Kendall's test is applied to investigate the changes of drought indices in different time horizons. Also, the aridity index is used to determine the climatic condition of different parts of Iran in several time periods and its changes are analyzed and investigated.Results: The results illustrate that in the near future and based on the RCP4.5 scenario, the average annual dryness index has an increasing trend in most parts of the country, and these climate changes lead to a change in the climate of some parts of the north of the country from humid to semi-arid and semi-humid, and parts of the center and the southeast become dry to semi-arid. According to the RCP8.5 scenario, there is a downward trend in parts of the east and the center of the country, and an upward trend in parts of West Azerbaijan, East Azerbaijan, Chaharmahal Bakhtiari, and a part of Kermanshah, and climate change rises the spatial extent of dry climates in the country. Also, in the mid-term and based on the RCP4.5 scenario, a downward trend can be seen in most parts of the country, and climate change will increase the area of dry climate lands in the central and southeastern parts, while according to the RCP8.5 scenario, there is an upward trend in most of the country, and climate change causes a soar in semi-arid and dry climates in parts of the northwest, northeast, and parts of the center and south of the country. Finally, in the long-term and based on the RCP4.5 scenario, the mentioned trends will be almost true and climate change will lead to the expansion of areas with arid and semi-arid climates.Conclusion: The results obtained in the this research showed that the average drought index in the near future, mid-term and long-term according to the RCP4.5 scenario are 0.5, 2.2 and, 2.3%, respectively and according to the RCP8.5 scenario, 2, 4.2 and, 4.1% have risen compared to the primary period, respectively, and it rises by 1.4 percent compared to the base period, and it is a good indication that the reduction in rainfall and the increase in the temperature of the earth's surface will lead to a soaring in the dryness of different parts of the country. In addition to changing the climate of the region, this issue will have irreparable effects on the condition of water resources, agriculture, environment and urbanization. Therefore, in order to reduce the aforementioned effects, it is recommended that managers and officials consider appropriate measures, correspond to each clime region, to control the amount of water consumption in different parts of the country.
Ahani, H., Kherad, M., Kousari, M. R., Van Roosmalen, L., Aryanfar, R., & Hosseini, S. M. (2013). Non-parametric trend analysis of the aridity index for three large arid and semi-arid basins in Iran. Theoretical and applied climatology, 112(3): 553-564 (In Persian)
Amani, Z., Deihimfard, R., & Mokhtassi, B.A. (2016). Evalution of drought under increasing of temperature due to climate change in rainfed wheat-growing areas of Fars province using Aridity Index. Journal of Crop Production, 9(2), 151-174. (In Persian)
Bakhtiari, B., Mahdavi, N., & Sayari, N. (2021). Variations and Sensitivity Analysis on Aridity Index (AI) in Some Climate Samples in Iran. Iran-Water Resources Research, 17(1), 1-15. (In Persian)
Cannon, A. J., Sobie, S. R., & Murdock, T. Q. (2015). Bias correction of GCM precipitation by quantile mapping: how well do methods preserve changes in quantiles and extremes?. Journal of Climate, 28(17), 6938-6959.
Dehghan, S., Salehnia, N., Sayari, N., & Bakhtiari, B. (2020). Prediction of meteorological drought in arid and semi-arid regions using PDSI and SDSM: a case study in Fars Province, Iran. Journal of Arid Land, 12, 318-330. (In Persian)
Dehghani Tafti, A.A., Zare, M., Hosseini, S., & Arabi Aliabad, F. (2019). Investigating the Trend of Drought Changes and Its Relation with Climatic Elements. Desert Management, 7(13): 1-14. (In Persian)
Ekhtiarikhajeh, S., & Dinpazhoh, Y. (2018). Application of effective drought index (EDI) for studying dry periods (Tabriz, Bandar Anzali and Zahedan stations). Irrigation Science and Engineering, 41(1), 133-145. (In Persian)
Ghorbani, K., Valizadeh, E., & BararkhanPoor, S. (2018). Investigation of spatiotemporal trend of the bivariate meteorological drought index, SPEI, in Iran. Desert Management, 6(11), 25-38. (In Persian)
Goparaju, L., & Ahmad, F. (2019). Analysis of seasonal precipitation, potential evapotranspiration, aridity, future precipitation anomaly and major crops at district level of India. KN-Journal of Cartography and Geographic Information, 69(2), 143-154.
IPCC. (2014). Climate change 2014: Synthesis report contribution of working groups I II and III to the fifth assessment report of the intergovernmental panel on climate change [Core Writing Team R K Pachauri and L A Meyer (eds.)]. IPCC Geneva Switzerland 151
Kamruzzaman, M., Jang, M.W., Cho, J., & Hwang, S. (2019). Future changes in precipitation and drought characteristics over Bangladesh under CMIP5 climatological projections. Water, 11(11).
Kaviani, MR. (2001). Climatic investigation on aridity and drought index. Geographical Researches, 16(1): 71-89. (In Persian)
Kendall, MG. (1948). Rank correlation methods. Charles Griffin & Co, London, 272p
Li, M., Chu, R., Islam, A.R.M., Jiang, Y., & Shen, S. (2020). Attribution analysis of long-term trends of aridity index in the Huai River Basin, Eastern China. Journal of Sustainability, 12(5):1743.
Mann, HB. (1945). Nonparametric tests against trend. Econometrica: Journal of the Econometric Society, 13(3):245-259.
Mesbahzadeh, T., Mirakbari, M., Mohseni saravi, M., Khosravi, H., & Mortezaii, G. (2019). Study of Current and Future Meteorological Drought Conditions using the CMIP5 Model Under RCP scenarios. Iranian Journal of Watershed Management Science and Engineering, 13 (46) :11-21. (In Persian)
Naderianfar, M., & Heydari Gharae, E. (2021). Evaluation of drought impacts on irrigated and rainfed wheat yields in Bojnourd region. Crop Science Research in Arid Regions, 3(1), 163-176. (In Persian)
Nair, S. C., & Mirajkar, A. (2022). Drought vulnerability assessment across Vidarbha region, Maharashtra, India. Arabian Journal of Geosciences, 15(4), 355.
Nobakht, M., Saghafian, B., & Aminyavari, S. (2021). Skill assessment of Copernicus climate change service seasonal ensemble precipitation forecasts over Iran. Advances in Atmospheric Sciences, 38, 504-521. (In Persian)
Nouri, M., Homaee, M., & Bannayan, M. (2016). Assessing Trends of aridity index changes over 1966-2100 period in the Northwest of Iran. Watershed Engineering and Management, 8(4), 439-453. (In Persian)
Oliver, J.E. (2005). The Encyclopedia of World Climatology: Springer Netherlands.
Pouralkhas Nokandeie, M., Esmali-Ouri, A., Mostafazadeh, R., Hazbavi, Z., & Sharari, M. (2022). Indicators and components of assessing variations and changes in climate change. Disaster Prevention and Management Knowledge (quarterly), 12(1): 85-98. (In Persian)
Ranjbar, F., & Tabatabaii, H. (2022). Investigation of the trend of Aridity index in the northern stations of Iran during the period 1982-2019. Climate Change Research. (In Persian)
Rezaei, H., & Motamedi Rad, M. (2023). Assessing phenological growth stages of barberry tree growth and the effect of climate change on its water requirement in Iran. Water and Soil Management and Modelling, 3(2): 78-92. doi: 10.22098/mmws.2022.11189.1105. (In Persian)
Sharma, S., Hamal, K., Khadka, N., Ali, M., Subedi, M., Hussain, G., ... & Dawadi, B. (2021). Projected drought Conditions over Southern Slope of the Central Himalaya using CMIP6 models. Earth Systems and Environment, 5, 849-859.
Spinoni, J., Vogt, J., & Barbosa, P. (2015). European degree‐day climatologies and trends for the period 1951–2011. International Journal of Climatology, 35(1), 25-36.
Stefanidis, K., Kostara, A., & Papastergiadou, E. (2016). Implications of human activities, land use changes and climate variability in Mediterranean lakes of Greece. Water, 8(11), 483.
Switanek, M. B., Troch, P. A., Castro, C. L., Leuprecht, A., Chang, H. I., Mukherjee, R., & Demaria, E. (2017). Scaled distribution mapping: a bias correction method that preserves raw climate model projected changes. Hydrology and Earth System Sciences, 21(6): 2649-2666.
Wouters, H., Berckmans, J., Maes. R., Vanuytrecht, E., & De Ridder, K. Global bioclimatic indicators from 1950 to 2100 derived from climate projections, Copernicus Climate Change Service (C3S) Climate Data Store (CDS) (2021).
Zhang, Q., Li, J., Singh, V. P., & Bai, Y. (2012). SPI-based evaluation of drought events in Xinjiang, China. Natural hazards 64: 481-492.
