A simulation-optimization methodology to model urban catchments under non-stationary extreme rainfall events.

Daniel Jato-Espino, Nora Sillanpaa, Sue Charlesworth, Jorge Rodriguez-Hernandez

    Research output: Contribution to journalArticlepeer-review

    13 Citations (Scopus)
    75 Downloads (Pure)


    Urban drainage is being affected by Climate Change, whose effects are likely to alter the intensity of rainfall events and result in variations in peak discharges and runoff volumes which stationary-based designs might not be capable of dealing with. Therefore, there is a need to have an accurate and reliable means to model the response of urban catchments under extreme precipitation events produced by Climate Change. This research aimed at optimizing the stormwater modelling of urban catchments using Design of Experiments (DOE), in order to identify the parameters that most influenced their discharge and simulate their response to severe storms events projected for Representative Concentration Pathways (RCPs) using a statistics-based Climate Change methodology. The application of this approach to an urban catchment located in Espoo (southern Finland) demonstrated its capability to optimize the calibration of stormwater simulations and provide robust models for the prediction of extreme precipitation under Climate Change.
    Original languageEnglish
    Article number103960
    Number of pages15
    JournalEnvironmental Modelling & Software
    Early online date7 Jun 2017
    Publication statusPublished - Dec 2019

    Bibliographical note

    NOTICE: this is the author’s version of a work that was accepted for publication in Environmental Modelling & Software. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Environmental Modelling & Software, (2017) DOI: 10.1016/j.envsoft.2017.05.008

    © 2017, Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/


    • Climate change
    • Design of experiments
    • Geographic information system
    • Stormwater modelling
    • Urban hydrology

    ASJC Scopus subject areas

    • Software
    • Environmental Engineering
    • Ecological Modelling


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