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

被引:16
|
作者
Jato-Espino, Daniel [1 ]
Sillanpaa, Nora [2 ]
Charlesworth, Susanne M. [3 ]
Rodriguez-Hernandez, Jorge [1 ]
机构
[1] Univ Cantabria, GITECO Res Grp, Av Castros S-N, E-39005 Santander, Spain
[2] Aalto Univ, Dept Built Environm, Sch Engn, POB 15200, Aalto, Finland
[3] Coventry Univ, CAWR, Coventry CV1 5FB, W Midlands, England
关键词
Climate change; Design of experiments; Geographic information system; Stormwater modelling; Urban hydrology; REGIONAL CLIMATE MODEL; RUNOFF; FLOOD; IMPACTS; PRECIPITATION; BASIN; CALIBRATION; STREAMFLOW; SYSTEM; TRENDS;
D O I
10.1016/j.envsoft.2017.05.008
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
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. (c) 2017 Elsevier Ltd. All rights reserved.
引用
收藏
页数:15
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