{
  "abstract": "Urbanisation increases surface runoff and recurrent flooding in cities, mainly by reducing infiltration capacity and shortening times of concentration. Rainwater harvesting tanks can store water to mitigate peak flows from urban development and support sustainable planning for new buildings. This study presents a hydrological routing approach for rainwater harvesting tanks, solved using the Rosenbrock method, combined with Monte Carlo analysis to generate a sufficiently large, representative set of hydrological scenarios. Based on these simulations, we developed multiple machine learning (ML) models to provide a simplified, efficient predictive framework. A total of 200 scenarios were generated using Latin Hypercube Sampling by varying key input parameters, including rainfall intensity, pipe length, internal pipe diameter, and tank surface area. In total, 28 ML regression models were evaluated to estimate peak outflow discharge. The Cubic Support Vector Machine (SVM) exhibited the best performance, achieving coefficients of determination ( $${R}^{2}$$ R 2 ) of 0.984 and 0.985 for the validation and testing stages, respectively. Sensitivity analysis revealed that the internal pipe diameter is the most influential parameter controlling peak discharge. The proposed methodology offers a computationally efficient, reliable tool for predicting the hydraulic performance of rainwater harvesting tanks, supporting decision-making for urban planners and local authorities in flood mitigation strategies.",
  "abstract_shown": true,
  "affiliations": [
    "Universidad Estatal Península de Santa Elena",
    "University of Cartagena",
    "Fundación Universitaria Tecnológico Comfenalco Cartagena",
    "University of the Coast"
  ],
  "article_type": null,
  "arxiv": null,
  "author_total": 5,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Teresa Guarda"
    },
    {
      "affs": [
        1
      ],
      "name": "Oscar E. Coronado-Hernández"
    },
    {
      "affs": [
        1
      ],
      "name": "Manuel Saba"
    },
    {
      "affs": [
        2
      ],
      "name": "Germán Herrera-Vidal"
    },
    {
      "affs": [
        3
      ],
      "name": "Jairo R. Coronado-Hernández"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/9bb0q9a9x5rrd.bib",
  "cited_by": 0,
  "doi": "10.1007/s44533-026-00089-7",
  "fulltext_url": "https://doi.org/10.1007/s44533-026-00089-7",
  "id": "9bb0q9a9x5rrd",
  "issns": [
    "2357-0008",
    "1110-4929"
  ],
  "landing_url": "https://doi.org/10.1007/s44533-026-00089-7",
  "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",
      "TC1-978"
    ],
    [
      "lcc",
      "TD1-1066"
    ],
    [
      "openalex",
      "2305|Urban Stormwater Management Solutions"
    ]
  ],
  "openalex": "W7223833534",
  "pdf_url": "https://link.springer.com/content/pdf/10.1007/s44533-026-00089-7.pdf",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-01",
  "publisher": "Springer Nature",
  "ris": "https://research.draconitic.com/paper/9bb0q9a9x5rrd.ris",
  "sources": [
    {
      "first_seen": "2026-11-01T14:21:23Z",
      "native_id": "0b48e32f821f4247b13da51beadf9fb7",
      "source": "doaj",
      "url": "https://doi.org/10.1007/s44533-026-00089-7"
    }
  ],
  "subjects": [
    {
      "field": "earth",
      "origin": "openalex:2305|Urban Stormwater Management Solutions",
      "subfield": "environmental-science"
    }
  ],
  "title": "Surrogate modelling approach for modelling peak discharge in rainwater harvesting tanks: case study in Quito, Ecuador",
  "title_text": "Surrogate modelling approach for modelling peak discharge in rainwater harvesting tanks: case study in Quito, Ecuador",
  "type": "peer-reviewed",
  "updated_at": "2026-11-03T14:20:50Z",
  "url": "https://research.draconitic.com/paper/9bb0q9a9x5rrd",
  "venue": "Water Science",
  "versions": []
}