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Projection of Mean Annual and Maximum 24-h Precipitation under Future Climatic Scenarios in Semi-Arid Regions

Author

Listed:
  • Pezhman Allahbakhshian-Farsani

    (Tarbiat Modares University)

  • Mehdi Vafakhah

    (Tarbiat Modares University)

  • Hadi Khosravi-Farsani

    (Shahrekord University)

  • Elke Hertig

    (University of Augsburg)

Abstract

In this study, the capability of a statistical downscaling model (SDSM) is evaluated to simulate precipitation regarding 37 rain gauge stations (1985–2005) in the North Karun Watershed (NKW), DeZ Watershed (DZW), and KarKheh Watershed (KKW). The fifth generation ECMWF atmospheric reanalysis (ERA5) dataset for calibration (1985–1993) of the model and the outputs of the Norwegian Earth System Model (NorESM1-M) for validation over a historical period (1994–2005) was used. Representative concentration pathways (RCPs) 4.5 and 8.5 scenarios in the near (the 2030s) and mid-term future (the 2060s) using the NorESM1-M model to project precipitation was utilized. Maximum 24-h precipitation (MP24) over the future periods was derived from the projected annual mean precipitation series. The MP24 with generalized normal (GNO) and generalized logistic (GLO) probability distribution functions (PDFs) as the most suitable distribution was then regionalized. The results of the selection predictor stage indicate that precipitation is mainly affected by relative humidity, precipitation rate, and wind in the whole region. Moreover, the results evaluating the performance of the SDSM model at all the stations reveal that the model is classified into good and very good categories. Over both calibration and validation periods, the simulated series are almost close to the observed series. Hence, the SDSM model can potentially downscale future precipitation in the region. The annual precipitation under all scenarios is projected to increase except for scenario RCP8.5 in the 2060s. Comparing the MP24 under scenario RCP4.5 with the baseline period shows a rise in precipitation by about 8% in the 2030s and roughly 9.4% in the 2060s, while under scenario RCP8.5, it will increase by approximately 7.5% and 5.6%, respectively, over the same periods. Overall, the future MP24 in the eastern parts, especially in the northeast and center of the study area, is considerable, which could be due to increased elevation. The MP24 as an extreme event also shows more noticeable changes than annual precipitation under future climatic conditions. In general, extreme precipitation will see a growth in the future, leading to an increase in flood risk in this region.

Suggested Citation

  • Pezhman Allahbakhshian-Farsani & Mehdi Vafakhah & Hadi Khosravi-Farsani & Elke Hertig, 2025. "Projection of Mean Annual and Maximum 24-h Precipitation under Future Climatic Scenarios in Semi-Arid Regions," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 39(6), pages 2785-2817, April.
    • Handle: RePEc:spr:waterr:v:39:y:2025:i:6:d:10.1007_s11269-025-04091-z
    DOI: 10.1007/s11269-025-04091-z
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    References listed on IDEAS

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    1. Mahdi Valikhan Anaraki & Saeed Farzin & Sayed-Farhad Mousavi & Hojat Karami, 2021. "Uncertainty Analysis of Climate Change Impacts on Flood Frequency by Using Hybrid Machine Learning Methods," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(1), pages 199-223, January.
    2. R. Manzanas & L. Fiwa & C. Vanya & H. Kanamaru & J. M. Gutiérrez, 2020. "Statistical downscaling or bias adjustment? A case study involving implausible climate change projections of precipitation in Malawi," Climatic Change, Springer, vol. 162(3), pages 1437-1453, October.
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    4. Nigel Arnell & Simon Gosling, 2016. "The impacts of climate change on river flood risk at the global scale," Climatic Change, Springer, vol. 134(3), pages 387-401, February.
    5. Pezhman Allahbakhshian-Farsani & Mehdi Vafakhah & Hadi Khosravi-Farsani & Elke Hertig, 2020. "Regional Flood Frequency Analysis Through Some Machine Learning Models in Semi-arid Regions," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(9), pages 2887-2909, July.
    6. Elahe Fallah-Mehdipour & Omid Bozorg-Haddad & Xuefeng Chu, 2021. "Environmental demand effects on the energy generation of Karkheh reservoir: Base and climate change conditions," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(9), pages 13165-13181, September.
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