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

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A simulation-optimization methodology to model urban catchments under non-stationary extreme rainfall events. / Jato-Espino, Daniel; Sillanpää, Nora; Charlesworth, Susanne M.; Rodriguez-Hernandez, Jorge.

In: Environmental Modelling and Software, Vol. 122, 103960, 01.12.2019.

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Jato-Espino, Daniel ; Sillanpää, Nora ; Charlesworth, Susanne M. ; Rodriguez-Hernandez, Jorge. / A simulation-optimization methodology to model urban catchments under non-stationary extreme rainfall events. In: Environmental Modelling and Software. 2019 ; Vol. 122.

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@article{7171646cb67549338a2d6d1ffb93c36a,
title = "A simulation-optimization methodology to model urban catchments under non-stationary extreme rainfall events",
abstract = "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.",
keywords = "climate change, design of experiments, geographic information system, stormwater modelling, urban h ydrology",
author = "Daniel Jato-Espino and Nora Sillanp{\"a}{\"a} and Charlesworth, {Susanne M.} and Jorge Rodriguez-Hernandez",
year = "2019",
month = "12",
day = "1",
doi = "10.1016/j.envsoft.2017.05.008",
language = "English",
volume = "122",
journal = "Environmental Modelling & Software",
issn = "1364-8152",

}

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TY - JOUR

T1 - A simulation-optimization methodology to model urban catchments under non-stationary extreme rainfall events

AU - Jato-Espino, Daniel

AU - Sillanpää, Nora

AU - Charlesworth, Susanne M.

AU - Rodriguez-Hernandez, Jorge

PY - 2019/12/1

Y1 - 2019/12/1

N2 - 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.

AB - 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.

KW - climate change

KW - design of experiments

KW - geographic information system

KW - stormwater modelling

KW - urban h ydrology

U2 - 10.1016/j.envsoft.2017.05.008

DO - 10.1016/j.envsoft.2017.05.008

M3 - Article

VL - 122

JO - Environmental Modelling & Software

JF - Environmental Modelling & Software

SN - 1364-8152

M1 - 103960

ER -

ID: 13637071