Ensemble urban flood simulation in comparison with laboratory-scale experiments: Impact of interaction models for manhole, sewer pipe, and surface flow

被引:46
作者
Noh, Seong Jin [1 ]
Lee, Seungsoo [2 ]
An, Hyunuk [3 ]
Kawaike, Kenji [4 ]
Nakagawa, Hajime [4 ]
机构
[1] Univ Texas Arlington, Dept Civil Engn, Arlington, TX 76019 USA
[2] APEC Climate Ctr, Climate Change Res Team, Centum 7 Ro, Busan 48058, South Korea
[3] Chungnam Natl Univ, Dept Agr & Rural Engn, Deahak Ro 99, Daejeon 305764, South Korea
[4] Kyoto Univ, Disaster Prevent Res Inst, Fushimi Ku, Kyoto 6128235, Japan
基金
美国国家科学基金会;
关键词
Urban flood; Ensemble method; Interaction model; Laboratory experiment; Parameter uncertainty; UNCERTAINTY ESTIMATION; CLIMATE-CHANGE; INUNDATION; DRAINAGE; URBANIZATION; CALIBRATION; MANAGEMENT; RESOLUTION; HYDROLOGY; STEP;
D O I
10.1016/j.advwatres.2016.08.015
中图分类号
TV21 [水资源调查与水利规划];
学科分类号
081501 ;
摘要
An urban flood is an integrated phenomenon that is affected by various uncertainty sources such as input forcing, model parameters, complex geometry, and exchanges of flow among different domains in surfaces and subsurfaces. Despite considerable advances in urban flood modeling techniques, limited knowledge is currently available with regard to the impact of dynamic interaction among different flow domains on urban floods. In this paper, an ensemble method for urban flood modeling is presented to consider the parameter uncertainty of interaction models among a manhole, a sewer pipe, and surface flow. Laboratory-scale experiments on urban flood and inundation are performed under various flow conditions to investigate the parameter uncertainty of interaction models. The results show that ensemble simulation using interaction models based on weir and orifice formulas reproduces experimental data with high accuracy and detects the identifiability of model parameters. Among interaction-related parameters, the parameters of the sewer-manhole interaction show lower uncertainty than those of the sewer-surface interaction. Experimental data obtained under unsteady-state conditions are more informative than those obtained under steady-state conditions to assess the parameter uncertainty of interaction models. Although the optimal parameters vary according to the flow conditions, the difference is marginal. Simulation results also confirm the capability of the interaction models and the potential of the ensemble-based approaches to facilitate urban flood simulation. (C) 2016 Elsevier Ltd. All rights reserved.
引用
收藏
页码:25 / 37
页数:13
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