IDEAS home Printed from https://ideas.repec.org/a/spr/waterr/v39y2025i6d10.1007_s11269-025-04091-z.html
   My bibliography  Save this article

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
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11269-025-04091-z
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s11269-025-04091-z?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:waterr:v:39:y:2025:i:6:d:10.1007_s11269-025-04091-z. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.