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Future outlook of monthly maximum daily precipitation in Pakistan’s hydroclimatic zones: high-resolution insights from CMIP6 multimodel data
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  • Published: 04 April 2026

Future outlook of monthly maximum daily precipitation in Pakistan’s hydroclimatic zones: high-resolution insights from CMIP6 multimodel data

  • Muhammad Adnan1,2,
  • Firdos Khan3,
  • Muhammad Abbas4,5,
  • Fahad Shahzad6 &
  • …
  • TianXiang Yue1,2 

Scientific Reports , Article number:  (2026) Cite this article

We are providing an unedited version of this manuscript to give early access to its findings. Before final publication, the manuscript will undergo further editing. Please note there may be errors present which affect the content, and all legal disclaimers apply.

Subjects

  • Climate sciences
  • Environmental sciences
  • Hydrology
  • Natural hazards
  • Water resources

Abstract

Extreme precipitation events are intensifying under climate change, driving escalating flood risks in some of the world’s most vulnerable regions. Pakistan is one of the most hydrologically diverse and flood-prone country, previous studies have largely emphasized seasonal or mean rainfall, leaving monthly maximum daily precipitation extremes (Rx1day at monthly resolution) underexplored, despite their direct role in triggering flash floods, landslides, and infrastructure failures. This study fills that gap by analyzing bias-corrected CMIP6 multi-model ensembles to project Rx1day-month precipitation extremes for SSP2-4.5 and SSP5-8.5 across seven hydroclimatic zones. Projections are assessed for the near future (2017–2044), mid-century (2045–2072), and late century (2073–2100), relative to the 1985–2014 baseline. Findings reveal strong spatial heterogeneity. Northern and northwestern highlands exhibit the largest absolute increases, with late-century monsoon monthly maxima of daily precipitation reaching approximately 130–150 mm, nearly double baseline values. Central and southern zones also experience pronounced amplification, intensifying flash-flood, riverine, and urban drainage hazards. By contrast, western arid and coastal regions show a decline in the magnitude of monthly maximum daily precipitation, punctuated by occasional high-intensity events. Intensification is most under SSP5-8.5, where both the magnitude and spatial footprint of extremes expand significantly over time. These high-resolution, zone-specific projections demonstrate that even localized shifts in extreme rainfall can compound hazard exposure, destabilize agriculture, and overwhelm water-management systems. The results provide actionable evidence for strengthening early-warning capacity, guiding resilient infrastructure planning, and informing targeted adaptation in one of the world’s most flood-exposed countries.

Data availability

The model data (CMIP6) is available online and can be accessed on the link: https://wcrp-cmip.org/cmip-phases/cmip6/. The observed data will be made available on request.

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Acknowledgements

This work was supported by the National Natural Science Foundation of China (42330707), National Key Research & Development Program of China (2024YFD1700904), the Science Fund for Creative Research Groups of the National Natural Science Foundation of China (72221002), the Strategic Priority Research Program of Chinese Academy of Sciences (XDB0740100), and National Key R&D Program of China (2021YFB3901300).

Funding

This work was supported by the National Natural Science Foundation of China (42330707), National Key Research & Development Program of China (2024YFD1700904), the Science Fund for Creative Research Groups of the National Natural Science Foundation of China (72221002), the Strategic Priority Research Program of Chinese Academy of Sciences (XDB0740100), and National Key R&D Program of China (2021YFB3901300).

Author information

Authors and Affiliations

  1. State Key Laboratory of Resources and Environmental Information System, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China

    Muhammad Adnan & TianXiang Yue

  2. College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, 101499, China

    Muhammad Adnan & TianXiang Yue

  3. School of Natural Sciences, National University of Sciences and Technology, H-12 Sector, Islamabad, 44000, Pakistan

    Firdos Khan

  4. Scuola Universitaria Superiore Studi Pavia IUSS, Pavia, Italy

    Muhammad Abbas

  5. University of Bergamo, Bergamo, Italy

    Muhammad Abbas

  6. Precision Forestry Key Laboratory of Beijing, Beijing Forestry University, Beijing, 100083, China

    Fahad Shahzad

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  2. Firdos Khan
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Contributions

**Muhammad Adnan: ** Conceptualization, Methodology, Software, Formal Analysis, Visualization, Data Curation, Original Draft Writing, Investigation, Validation, Review & Editing.**Firdos khan: ** Conceptualization, Methodology, Software, Visualization, Review & Editing, Supervision.**Muhammad Abbas** : Data Curation, Formal Analysis**Fahad Shahzad: ** Formal Analysis, Investigation, Review & Editing.**Tian Xiang Yue: ** Review & Editing, Supervision.

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Correspondence to TianXiang Yue.

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Adnan, M., Khan, F., Abbas, M. et al. Future outlook of monthly maximum daily precipitation in Pakistan’s hydroclimatic zones: high-resolution insights from CMIP6 multimodel data. Sci Rep (2026). https://doi.org/10.1038/s41598-026-45047-6

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  • Received: 09 September 2025

  • Accepted: 16 March 2026

  • Published: 04 April 2026

  • DOI: https://doi.org/10.1038/s41598-026-45047-6

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Keywords

  • Extreme precipitation
  • CMIP6 projections
  • Hydroclimatic zones
  • Clustering
  • Monsoon intensification
  • Climate adaptation.
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