Assessment of Climate Change Impacts on Drought Characteristics and Trivariate Return Period Risks in Western Iran

Document Type : Research Article

Authors

1 Aassistant Professor, Natural Engineering Department, Faculty of Natural Resources and Environment, Malayer University, Malayer, Iran. Author responsible:

2 PhD Graduated in Watershed Management, Faculty of Natural Resources, Urmia University, Urmia, Iran

3 PhD Graduated in Watershed Management, Faculty of Natural Resources and Geoscience, Kashan University, Kashan, Iran

Abstract

Objective: This study investigates the impact of climate change on drought characteristics in western Iran by analyzing trends in drought intensity, duration, and magnitude. The research aims to assess future drought risks under different climate scenarios to support water resource management strategies.
Method: Historical precipitation data (1966–2020) from six meteorological stations were analyzed using the Standardized Precipitation Index (SPI). Future climate projections were generated using the HadCM3 General Circulation Model (GCM) and downscaled with the LARS-WG model under SSP2-4.5 and SSP5-8.5 scenarios. Statistical trend analysis, probability distribution fitting, and copula functions were applied to evaluate the interdependence of drought characteristics and estimate joint return periods.
Results: The findings indicate an increasing trend in drought severity, particularly in Hamedan and Saqez, with SSP5-8.5 showing the most extreme conditions. Drought intensity and duration are projected to increase, with prolonged dry periods becoming more frequent. Joint return periods suggest that severe drought events, previously occurring every 20 years, may now happen every 10 years.
Conclusions: Climate change is intensifying drought risks in western Iran, requiring urgent adaptation strategies. Copula-based analysis highlights stronger dependencies between drought characteristics, increasing the likelihood of extreme events. Effective water management policies, including improved storage and irrigation systems, are essential to mitigate future drought impacts.

Keywords

Main Subjects


Abassi, F., Habibi Nokhandan, M., Goli Mokhtari, L., & Malbousi, S. (2010). Climate Change Assessment over Iran in the Future Decades Using MAGICC-SCENGEN Model. Physical Geography Research42(72), 91-110 (In persian).
Abbaspour, K. C., Faramarzi, M., Ghasemi, S. S., & Yang, H. (2009). Assessing the impact of climate change on water resources in Iran. Water resources research45(10).
Ahmadi, H., & Azizzadeh, J. (2020). The impacts of climate change based on regional and global climate models (RCMs and GCMs) projections (case study: Ilam province). Modeling Earth Systems and Environment6(2), 685-696.
Akaike, H. (1974). A new look at the statistical model identification. IEEE transactions on automatic control19(6), 716-723.
Alvankar, S. R., Nazari, F., & Fattahi, E. (2016). The Intensity and Return Periods of Drought under Future Climate Change Scenarios in Iran. Journal of Spatial Analysis Environmental Hazards, 3 (2): 99-120. (In persian).
Araghinejad, S., Hosseini-Moghari, S. M., & Eslamian, S. (2017). Application of data-driven models in drought forecasting. In Handbook of drought and water scarcity (pp. 423-440). CRC Press.
Azhdari, Z., Bazrafshan, O., Shekari, M., & Zamani, H. (2020). Analysis of Hydrological Drought Severity, Duration and Magnitude Using Copula Functions (Case study: Bandar-Sedij and Kol-Mehran Watershed). Journal of Ecohydrology7(1), 237-249. doi: 10.22059/ije.2020.295823.1270 (In persian).
Bahrehmand. A.R., Alvandi, E., Bahrami, M., Dashti, M., Heravi, H., Khosravi, G.R., Kornezhadi, A., Samadi arghini, H., Tajiki, M., & Teymouri, M. (2016). Copula functions and their application in stochastic hydrology, Scientific Journal of Conservation and Exploitation of Natural Resources, 4(2), 1-20. doi: 10.22069/ejang.2016.2793 (In persian).
Barati, A. A., Pour, M. D., & Sardooei, M. A. (2023). Water crisis in Iran: A system dynamics approach on water, energy, food, land and climate (WEFLC) nexus. Science of the Total Environment, 882, 163549.
Bayatavrkeshi, M., Imteaz, M. A., Kisi, O., Farahani, M., Ghabaei, M., Al-Janabi, A. M. S., ... & Yaseen, Z. M. (2023). Drought trends projection under future climate change scenarios for Iran region. Plos one18(11), e0290698.
Bazrafshan, O., Mahmoudzadeh, F., Asgari Nezhad, A., & Bazrafshan, J. (2019). Adaptive evaluation of SPI, RDI, and SPEI indices in analyzing the trend of intensity, duration, and frequency of drought in arid and semi-arid regions of Iran. Irrigation Sciences and Engineering42(3), 117-131.
Bazrafshan, O., Mahmudzadeh, F., & Bazrafshan, J. (2017). Evaluation of temporal trends of the drought indices SPI and SPEI in the Southern Coast of Iran. Desert Management4(8), 54-69.
Bazrafshan, O., Zamani, H., & Shekari, M. (2020). A copula‐based index for drought analysis in arid and semi-arid regions of Iran. Natural Resource Modeling33(1), e12237.
Bazrafshan, O., Zamani, H., Mozaffari, E., Azhdari, Z., & Shekari, M. (2023). Trivariate risk analysis of meteorological drought in Iran under climate change scenarios. Meteorology and Atmospheric Physics135(6), 52.
Behzadi, F., Yousefi, H., Javadi, S., Moridi, A., Shahedany, S. M. H., & Neshat, A. (2022). Meteorological drought duration–severity and climate change impact in Iran. Theoretical and Applied Climatology149(3), 1297-1315.
Burnham, K. P., & Anderson, D. R. (2004). Multimodel inference: understanding AIC and BIC in model selection. Sociological methods & research33(2), 261-304.
Choobeh, S., Farrokhzadeh, B., Bazrafshan, O., & Hasanvand, H. (2025). Impact of Climate Change on Precipitation Extremes Indices over Iran. Watershed Management Research37(4), 34-53. doi: 10.22092/wmrj.2024.364521.1565 (In persian).
Delghandi, M., Joorablou, S., & Ganji Nowroozi, Z. (2023). The Impact of Climate Change on Severity, Duration and Magnitude of Drought using SPI and RDI in Semnan Region. Journal of Drought and Climate change Research1(1), 1-18. doi: 10.22077/jdcr.2023.5909.1004 (In persian).
Diego, Armando, Urrea, Méndez., Dina, Vanessa, Gomez, Rave., Manuel, del, Jesús. (2024). Exploring Multivariate Return Periods: Enhancing Accuracy in Hydrological Analysis for Flood Prediction .   doi: 10.5194/egusphere-egu24-5685
Doesken, N. J., & Garen, D. (1991, September). Drought monitoring in the Western United States using a surface water supply index. In Proceedings of the 7th Conference on Applied Climatology, Salt Lake City, UT, USA (pp. 10-13).
Draper, N. R. (1998). Applied regression analysis. McGraw-Hill. Inc.
Esit, M., & Yuce, M. I. (2023). Copula-based bivariate drought severity and duration frequency analysis considering spatial–temporal variability in the Ceyhan Basin, Turkey. Theoretical and Applied Climatology151(3), 1113-1131.
Genest, C., & Favre, A. C. (2007). Everything you always wanted to know about copula modeling but were afraid to ask. Journal of hydrologic engineering12(4), 347-368.
Ghaemi, A.R., Hashemi Monfared, S. A., Bahrpeyma, A., Mahmoudi, P., & Zounemat-Kermani, M. (2022). Spatiotemporal variation of projected drought characteristics of Iran under the climate change scenarios. Journal of Meteorology and Atmospheric Science5(1), 68-80. doi: 10.22034/jmas.2023.390166.1199 (In persian).
Ghorbani H, vali A A, zarepour H. (2019). Analysis of the Climatological Drought Trend Variations Using Mann-Kendall, Sen and Pettitt Tests in Isfahan Province. Journal of Spatial Analysis Environmental Hazards, 6(2), 129-146 (In persian).
Goodarzi, M., Hosseini, A., & Mesgari, E. (2016). Weather and Meteorological Models. Zanjan, Azar kelk press (In persian).
Haile, G. G., Tang, Q., Hosseini-Moghari, S. M., Liu, X., Gebremicael, T. G., Leng, G., ... & Yun, X. (2020). Projected impacts of climate change on drought patterns over East Africa. Earth's Future8(7), e2020EF001502.
Hamed, K. H., & Rao, A. R. (1998). A modified Mann-Kendall trend test for autocorrelated data. Journal of hydrology204(1-4), 182-196.
Hashmi, M. Z., Shamseldin, A. Y., & Melville, B. W. (2011). Comparison of SDSM and LARS-WG for simulation and downscaling of extreme precipitation events in a watershed. Stochastic Environmental Research and Risk Assessment25, 475-484.
Hassan, Z., Shamsudin, S., & Harun, S. (2014). Application of SDSM and LARS-WG for simulating and downscaling of rainfall and temperature. Theoretical and applied climatology116, 243-257.
Hayes, M. J., Svoboda, M. D., Wardlow, B. D., Anderson, M. C., & Kogan, F. (2012). Drought monitoring: Historical and current perspectives.
Jahangir, M. H. & Rouzbahani, F. (2024). Simulation of Climatic Parameters using Statistical Microscale Models of SDSM and LARS in West Azerbaijan Province. Journal of Ecohydrology11(3), 374-394. doi: 10.22059/ije.2024.373803.1805 (In persian).
Jahangiri, E., Motamedvaziri, B., & Kiadaliri, H. (2024) Investigating the Impact of Climate Change on Drought with SPI and SPEI Indices (Case Study of Karun 3 Watershed). Iran-Watershed Management Science & Engineering, 18(65), 85-97 (In persian).
Joe, H. (1997). Multivariate models and multivariate dependence concepts. CRC press.
Kenawy, A. E., Al-Awadhi, T., Abdullah, M., Ostermann, F. O., & Abulibdeh, A. (2025). A Multidecadal Assessment of Drought Intensification in the Middle East and North Africa: The Role of Global Warming and Rainfall Deficit. Earth Systems and Environment, 1-20.
Kendall, M. G. (1948). Rank correlation methods.
Koohi, S., & Ramezani Etedali, H. (2023). Future meteorological drought conditions in southwestern Iran based on the NEX-GDDP climate dataset. Journal of Arid Land15(4), 377-392.
Kousari, M., Ekhtesasi, M., & Malekinezhad, H. (2017). Investigation of long term drought trend in semi-arid, arid and hyper-arid regions of the world. Desert Management4(8), 36-53.
Labudová, L., Ivaňáková, G., Faško, P., Kajaba, P., & Labuda, M. (2024). Changes in drought occurrence and intensity in the context of climate change in Slovakia. Theoretical and Applied Climatology, 1-14.
Lelieveld, J., Hadjinicolaou, P., Kostopoulou, E., Chenoweth, J., El Maayar, M., Giannakopoulos, C., ... & Xoplaki, E. (2012). Climate change and impacts in the Eastern Mediterranean and the Middle East. Climatic change114, 667-687.
Lotfi, M., Kamali, G. A., Meshkatee, A. H., & Varshavian, V. (2022). Performance analysis of LARS-WG and SDSM downscaling models in simulating temperature and precipitation changes in the West of Iran. Modeling Earth Systems and Environment8(4), 4649-4659.
Lotfinasabasl, S., Dargahian, F., Gohardoost, A., Hatam Baharvand, A., & Razavizadeh, S. (2023). Analysis of drought status and its relationship with climate change, Case study: Sarableh oak decline sites, Ilam province. Iranian Journal of Range and Desert Research30(2), 335-354. doi: 10.22092/ijrdr.2023.129905 (In persian).
Lotfirad, M., Esmaeili-Gisavandani, H., & Adib, A. (2022). Drought monitoring and prediction using SPI, SPEI, and random forest model in various climates of Iran. Journal of Water and Climate Change13(2), 383-406.
Ma, L., Huang, Q., Huang, S., Liu, D., Leng, G., Wang, L., & Li, P. (2022). Propagation dynamics and causes of hydrological drought in response to meteorological drought at seasonal timescales. Hydrology Research53(1), 193-205.
Madani, K. (2014). Water management in Iran: what is causing the looming crisis?. Journal of environmental studies and sciences4, 315-328.
Mann, H., 1945. Non-Parametric Tests against Trend. Econmetrica, 13, 245-259.
Massey Jr, F. J. (1951). The Kolmogorov-Smirnov test for goodness of fit. Journal of the American statistical Association46(253), 68-78.
McKee, T. B., Doesken, N. J., & Kleist, J. (1993, January). The relationship of drought frequency and duration to time scales. In Proceedings of the 8th Conference on Applied Climatology (Vol. 17, No. 22, pp. 179-183).
Mesbahzadeh, T., Mirakbari, M., Mohseni Saravi, M., Soleimani Sardoo, F., & Miglietta, M. M. (2020). Meteorological drought analysis using copula theory and drought indicators under climate change scenarios (RCP). Meteorological Applications27(1), e1856.
Mirabbasi, R., Fakheri-Fard, A., & Dinpashoh, Y. (2012). Bivariate drought frequency analysis using the copula method. Theoretical and applied climatology108, 191-206.
Mirdar Soltani, S. (2023). Modeling analysis of 21st century climate change projections and their impacts on the hydrology of the Karaj-Jajrood basin, Iran (Doctoral dissertation).
Mishra, A. K. & Singh, V. P. (2010). A review of drought concepts. Journal of hydrology391(1-2), 202-216.
Modarres, R. & Sarhadi, A. (2009). Rainfall trends analysis of Iran in the last half of the twentieth century. Journal of Geophysical Research: Atmospheres114(D3).
Mohammed, Z. M. & Hassan, W. H. (2022). Climate change and the projection of future temperature and precipitation in southern Iraq using a LARS-WG model. Modeling Earth Systems and Environment8(3), 4205-4218.
Mozaffari, E., Moradi, N., & Bazrafshan, O. (2021). Spatio-Temporal Variability of Characteristics of Meteorological Drought in Iran under Climate Change Scenarios. Desert Management8(16), 153-163. doi: 10.22034/jdmal.2021.243146 (In persian).
Nelsen, R. B. (2006). An introduction to copulas. Springer.
O'Neill, B. C., Tebaldi, C., Van Vuuren, D. P., Eyring, V., Friedlingstein, P., Hurtt, G., ... & Sanderson, B. M. (2016). The scenario model intercomparison project (ScenarioMIP) for CMIP6. Geoscientific Model Development9(9), 3461-3482.
Patel, R. & Patel, A. (2024). Evaluating the impact of climate change on drought risk in semi-arid region using GIS technique. Results in Engineering21, 101957.
Pourhaghverdi, F., Bazrafshan, O., Gholami, H., Shekari, M., & Zamani, H. (2023). Application of copula function in multivariate analysis of stream flow drought index (case study: Minab Esteghlal Dam Basin). Journal of Arid Biome13(1), 97-110. doi: 10.29252/aridbiom.2023.20698.1962 (In persian).
Prudhomme, C., Giuntoli, I., Robinson, E. L., Clark, D. B., Arnell, N. W., Dankers, R., ... & Wisser, D. (2014). Hydrological droughts in the 21st century, hotspots and uncertainties from a global multimodel ensemble experiment. Proceedings of the National Academy of Sciences111(9), 3262-3267.
Rastegaripour, F., Tavassoli, A., Babaeian, M., Fernández-Gálvez, J., & Caballero-Calvo, A. (2024). Assessing the impacts of climate change on water resource management and crop patterns in Eastern Iran. Agricultural Water Management295, 108774.
Riahi, K., Van Vuuren, D. P., Kriegler, E., Edmonds, J., O’neill, B. C., Fujimori, S., ... & Tavoni, M. (2017). The Shared Socioeconomic Pathways and their energy, land use, and greenhouse gas emissions implications: An overview. Global environmental change42, 153-168.
Rostami, F. & Moridi, A. (2025). Investigating the impact of climate change on drought intensity, duration, and recurrence period in the Ardabil study area. Water and Irrigation Management, 14(4), 877-895 (In persian).
Salas, J. D. & Obeysekera, J. (2014). Revisiting the concepts of return period and risk for nonstationary hydrologic extreme events. Journal of hydrologic engineering19(3), 554-568.
Salvadori, G. & De Michele, C. (2004). Frequency analysis via copulas: Theoretical aspects and applications to hydrological events. Water resources research40(12).
Salvadori, G. & De Michele, C. (2007). On the use of copulas in hydrology: theory and practice. Journal of Hydrologic Engineering12(4), 369-380.
Samantaray, A. K., Ramadas, M., & Panda, R. K. (2021). Assessment of impacts of potential climate change on meteorological drought characteristics at regional scales. International Journal of Climatology41, E319-E341.
Schwarz, G. (1978). Estimating the dimension of a model. The annals of statistics, 461-464.
Semenov, M. A., Barrow, E. M., & Lars-Wg, A. (2002). A stochastic weather generator for use in climate impact studies. User Man Herts UK, 1-27.
Shayeghi, A., Ziveh, A. R., Bakhtar, A., Teymoori, J., Hanel, M., Godoy, M. R. V., ... & AghaKouchak, A. (2024). Assessing drought impacts on groundwater and agriculture in Iran using high-resolution precipitation and evapotranspiration products. Journal of Hydrology631, 130828.
Sheffield, J. & Wood, E. F. (2008). Projected changes in drought occurrence under future global warming from multi-model, multi-scenario, IPCC AR4 simulations. Climate dynamics31, 79-105.
Shiau, J. T. (2003). Return period of bivariate distributed extreme hydrological events. Stochastic environmental research and risk assessment17, 42-57.
Shiau, J. T. (2006). Fitting drought duration and severity with two-dimensional copulas. Water resources management20, 795-815.
Snedecor, G. W. & Cochran, W. G. (1989). Statistical methods, 8thEdn. Ames: Iowa State Univ. Press Iowa54, 71-82.
Song, S. & Singh, V. P. (2010). Frequency analysis of droughts using the Plackett copula and parameter estimation by genetic algorithm. Stochastic Environmental Research and Risk Assessment24, 783-805.
Suo, N., Xu, C., Cao, L., Song, L., & Lei, X. (2024). A copula-based parametric composite drought index for drought monitoring and applicability in arid Central Asia. Catena235, 107624.
Teimouri, M., Asadi Nalivan, O., & Elahi, S. (2023). The Probabilistic Analysis of Drought Severity- Duration in North Khorasan Province using Copula Functions. Watershed Management Research36(2), 36-52. doi: 10.22092/wmrj.2022.359052.1479 (In persian).
Trenberth, K. E., Dai, A., Van Der Schrier, G., Jones, P. D., Barichivich, J., Briffa, K. R., & Sheffield, J. (2014). Global warming and changes in drought. Nature Climate Change4(1), 17-22.
Turgay P., & Ercan K. 2005. Trend Analysis in Turkish Precipitation data. Hydrological processes published online in Wiley Inter-science. 20:2011-2026.
Vali, A. & Roustaei, F. (2022). A time series analysis of drought for the last five decades in Central Iran. Desert Ecosystem Engineering5(11), 79-92 (In persian).
Vicente-Serrano, S. M., Beguería, S., & López-Moreno, J. I. (2010). A multiscalar drought index sensitive to global warming: the standardized precipitation evapotranspiration index. Journal of climate23(7), 1696-1718.
Wilks, D. S. (2011). Statistical methods in the atmospheric sciences. Academic press.
Wu, C., Yeh, P. J. F., Chen, Y. Y., Lv, W., Hu, B. X., & Huang, G. (2021). Copula-based risk evaluation of global meteorological drought in the 21st century based on CMIP5 multi-model ensemble projections. Journal of Hydrology598, 126265.
Yao, N., Li, L., Feng, P., Feng, H., Li Liu, D., Liu, Y., ... & Li, Y. (2020). Projections of drought characteristics in China based on a standardized precipitation and evapotranspiration index and multiple GCMs. Science of the Total Environment704, 135245.
Yousefi, H., Ahani, A., Moridi, A., & Razavi, S. (2024). The future of droughts in Iran according to CMIP6 projections. Hydrological Sciences Journal69(7), 951-970.
Yue, S., Pilon, P., Phinney, B., & Cavadias, G. (2002). The influence of autocorrelation on the ability to detect trend in hydrological series. Hydrological processes16(9), 1807-1829.
Zarch, M. A. A., Sivakumar, B., & Sharma, A. (2015). Droughts in a warming climate: A global assessment of Standardized precipitation index (SPI) and Reconnaissance drought index (RDI). Journal of hydrology526, 183-195.
Volume 12, Issue 1
March 2025
Pages 635-656
  • Receive Date: 31 January 2025
  • Revise Date: 24 February 2025
  • Accept Date: 14 March 2025
  • First Publish Date: 14 March 2025
  • Publish Date: 21 March 2025