{
  "abstract": "Global water scarcity intensifies the need for high-resolution groundwater assessment tools, yet traditional approaches struggle to reconcile qualitative expert weights with the extensive spatial coverage offered by remote sensing data. This study presents a comparative framework evaluating expert-driven Multi-Criteria Decision Analysis (a ten-layer Analytic Hierarchy Process (AHP)) against data-driven ensemble machine learning for groundwater potential mapping in the geologically complex terrain of Northwestern Nigeria. Standard thematic layers were integrated with embeddings from a pretrained remote sensing foundation model to train ensemble classifiers, with groundwater potential validated against Vertical Electrical Sounding (VES) data. The foundation-model-enhanced CAT-XGB ensemble achieved notable predictive performance, consistently outperforming standalone tree-based classifiers and traditional AHP. Spatial difference mapping revealed that the enhanced ensemble captured critical, localized hydrogeological anomalies smoothed over by expert-driven weighting. Bridging heuristic decision-making with foundation-model-enhanced machine learning significantly improves spatial precision and reliability, potentially providing a field-validated tool for optimizing borehole siting and sustainable aquifer management in data-scarce, geologically complex regions.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": null,
  "author_total": 4,
  "authors": [
    {
      "name": "Joseph Orojah Osumeje"
    },
    {
      "name": "Sachet Sandeep Utekar"
    },
    {
      "name": "Morli Li"
    },
    {
      "name": "Dani Jones"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/65q242ajk0sx1.bib",
  "cited_by": 0,
  "doi": "10.31223/x5mv5h",
  "fulltext_url": null,
  "id": "65q242ajk0sx1",
  "issns": [],
  "landing_url": "https://eartharxiv.org/repository/view/15434/",
  "language": null,
  "licence": "CC-BY-4.0",
  "licence_label": "CC BY 4.0",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/legalcode",
  "metadata_licence": null,
  "native_subjects": [
    [
      "bepress",
      "Analytic Hierarchy Process (AHP)"
    ],
    [
      "bepress",
      "CatBoost"
    ],
    [
      "bepress",
      "Earth Sciences"
    ],
    [
      "bepress",
      "Ensemble learning techniques"
    ],
    [
      "bepress",
      "Environmental Sciences"
    ],
    [
      "bepress",
      "GIS"
    ],
    [
      "bepress",
      "Galileo foundation model"
    ],
    [
      "bepress",
      "Geographic information systems"
    ],
    [
      "bepress",
      "Groundwater potential mapping"
    ],
    [
      "bepress",
      "Hydrology"
    ],
    [
      "bepress",
      "Machine Learning"
    ],
    [
      "bepress",
      "Northwestern Nigeria"
    ],
    [
      "bepress",
      "Physical Sciences and Mathematics"
    ],
    [
      "bepress",
      "Subsurface hydrology"
    ],
    [
      "bepress",
      "Vertical Electrical Sounding (VES)"
    ],
    [
      "bepress",
      "Water Resource Management"
    ],
    [
      "bepress",
      "Water scarcity"
    ],
    [
      "bepress",
      "XGBoost"
    ],
    [
      "openalex",
      "2305|Groundwater and Watershed Analysis"
    ]
  ],
  "openalex": "W7221088011",
  "pdf_url": "https://eartharxiv.org/repository/object/15434/download/26756/",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-09",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/65q242ajk0sx1.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:17:42Z",
      "native_id": "15434",
      "source": "eartharxiv",
      "url": "https://eartharxiv.org/repository/view/15434/"
    }
  ],
  "subjects": [
    {
      "field": "earth",
      "origin": "bepress:Environmental Sciences",
      "subfield": "environmental-science"
    },
    {
      "field": "earth",
      "origin": "bepress:Hydrology",
      "subfield": "hydrology-soils"
    }
  ],
  "title": "Groundwater Potential Mapping in Northwestern Nigeria: A Comparison of the Analytic Hierarchy Process and Galileo-Enhanced CAT-XGB",
  "title_text": "Groundwater Potential Mapping in Northwestern Nigeria: A Comparison of the Analytic Hierarchy Process and Galileo-Enhanced CAT-XGB",
  "type": "preprint",
  "updated_at": "2026-10-30T12:17:42Z",
  "url": "https://research.draconitic.com/paper/65q242ajk0sx1",
  "venue": "EarthArXiv",
  "versions": []
}