A simulation-optimization methodology to model urban catchments under non-stationary extreme rainfall events. (December 2019)

• Record Type: Journal Article
• Authors: Jato-Espino, Daniel; Sillanpää, Nora; Charlesworth, Susanne M.; Rodriguez-Hernandez, Jorge
• Is Part Of: Environmental modelling & software. Volume 122(2019)
• Publication Date: 2019-12
• Subjects: Climate change -- Design of experiments -- Geographic information system -- Stormwater modelling -- Urban hydrology; Environmental monitoring -- Computer programs -- Periodicals; Ecology -- Computer simulation -- Periodicals; Digital computer simulation -- Periodicals; Computer software -- Periodicals; Environmental Monitoring -- Periodicals; Computer Simulation -- Periodicals; Environnement -- Surveillance -- Logiciels -- Périodiques; Écologie -- Simulation, Méthodes de -- Périodiques; Simulation par ordinateur -- Périodiques; Logiciels -- Périodiques; Computer software; Digital computer simulation; Ecology -- Computer simulation; Environmental monitoring -- Computer programs; Periodicals; Electronic journals; 363.70015118
• DOI: 10.1016/j.envsoft.2017.05.008
• Languages: English
• ISSNs: 1364-8152

Abstract

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. Highlights: A methodology to model urban catchments under Climate Change is developed. Design of Experiments is used to optimize the calibration of stormwater simulations. Descriptive statistics are applied to project non-stationary extreme precipitation. The proposed approach is tested through a real catchment located in Espoo, Finland. Flood risk in the study catchment increased up to five times due to Climate Change.