{
  "abstract": "Study region: Iran faces water bankruptcy driven by decades of overuse and mismanagement, threatening both its population and ecosystems. Study focus: This study quantifies long-term terrestrial water storage loss (TWSL) dynamics across Iran by integrating GRACE satellite observations, extensive ground-based hydroclimatic records, and an explainable Random Forest model enhanced with Nataf-based data augmentation. We used SHapley Additive exPlanations (SHAP) to identify the relative contributions of climatic variability and anthropogenic forcing. New hydrological insights for the region: Results show pronounced hydroclimatic change between 1973 and 2023, indicating a significant increase of 2.05°C in air temperature and a 43 mm reduction in average annual precipitation between 1973–2000 and 2001–2019. The average annual streamflow at unregulated stations decreased by 37% during 1998–2018 relative to 1970–1997. Groundwater storage deficit over 2003–2018 was 83 BCM. GRACE data indicate a TWSL of about 370 BCM from 2002 to 2023, with 61% occurring after 2016, reflecting accelerating depletion. SHAP analysis revealed that groundwater dynamics dominate TWSL, explaining 90.5%, 91.9%, and 92.3% of its variability during normal, dry, and wet conditions, respectively, whereas the influence of other factors remains limited under all climatic conditions. This dominance indicates a decoupling of TWSL from short-term climate variability and a transition toward groundwater-controlled storage dynamics. These findings highlight the need for demand management and effective control of groundwater abstraction from aquifers to ensure long-term sustainability.",
  "abstract_shown": true,
  "affiliations": [
    "Department of Civil Engineering, Sharif University of Technology, Tehran, Iran",
    "Correspondence to: 425 Civil Engineering Department, Sharif University of Technology, Azadi Ave., P.O. Box, Tehran 11155-9313, Iran"
  ],
  "article_type": null,
  "arxiv": null,
  "author_total": 3,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Fereshteh Shakeri"
    },
    {
      "affs": [
        0
      ],
      "name": "Amirhossein Haddadi"
    },
    {
      "affs": [
        1
      ],
      "name": "Mohammad Danesh-Yazdi"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/781m9bgxcz6jf.bib",
  "cited_by": 0,
  "doi": "10.1016/j.ejrh.2026.104131",
  "fulltext_url": "http://www.sciencedirect.com/science/article/pii/S2214581826010293",
  "id": "781m9bgxcz6jf",
  "issns": [
    "2214-5818"
  ],
  "landing_url": "https://doi.org/10.1016/j.ejrh.2026.104131",
  "language": "en",
  "licence": "CC-BY",
  "licence_label": "CC BY",
  "licence_source": "journal",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "lcc",
      "GB3-5030"
    ],
    [
      "lcc",
      "QE1-996.5"
    ],
    [
      "openalex",
      "1910|Geophysics and Gravity Measurements"
    ]
  ],
  "openalex": "W7223342668",
  "pdf_url": null,
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-30",
  "publisher": "Elsevier",
  "ris": "https://research.draconitic.com/paper/781m9bgxcz6jf.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T13:44:58Z",
      "native_id": "c41c6414ea6c451fb153c27194e750e7",
      "source": "doaj",
      "url": "https://doi.org/10.1016/j.ejrh.2026.104131"
    }
  ],
  "subjects": [
    {
      "field": "earth",
      "origin": "openalex:1910|Geophysics and Gravity Measurements",
      "subfield": "oceanography"
    }
  ],
  "title": "Dissecting the drivers of national terrestrial water storage alterations using non-parametric ensemble learning: The case of Iran",
  "title_text": "Dissecting the drivers of national terrestrial water storage alterations using non-parametric ensemble learning: The case of Iran",
  "type": "peer-reviewed",
  "updated_at": "2026-10-30T13:44:58Z",
  "url": "https://research.draconitic.com/paper/781m9bgxcz6jf",
  "venue": "Journal of Hydrology: Regional Studies",
  "versions": []
}