Building level flood exposure analysis using a hydrodynamic model

被引:16
作者
Bertsch, Robert [1 ]
Glenis, Vassilis [1 ]
Kilsby, Chris [1 ,2 ]
机构
[1] Newcastle Univ, Sch Engn, Newcastle Upon Tyne NE1 7RU, Northumberland, England
[2] Willis Towers Watson Res Network, 51 Lime St, London EC3M 7DQ, England
基金
英国工程与自然科学研究理事会;
关键词
Urban flooding; Flood exposure; Model validation; Open -source code; Hydrodynamic flood modelling; CLIMATE-CHANGE; DAMAGE; VULNERABILITY; IMPACTS; CITIES;
D O I
10.1016/j.envsoft.2022.105490
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
The advent of detailed hydrodynamic model simulations of urban flooding has not been matched by improved capabilities in flood exposure analysis which rely on validation against observed data. This work introduces a generic, building-level flood exposure analysis tool applying high resolution flood data and building geometries derived from hydrodynamic simulations performed with the 2D hydrodynamic flood modelling software CityCAT. Validation data were obtained from a survey of affected residents following a large pluvial flood event in Newcastle upon Tyne, UK. Sensitivity testing was carried out for different hydrodynamic model and exposure tool settings and between 68% and 75% of the surveyed buildings were correctly modelled as either flooded or not flooded. The tool tends to underrepresent flooding with a better performance in identifying true negatives (i. e. no flooding observed with no flooding modelled) compared to true positives. As higher true positive rates were accompanied by higher false positive rates, no single scenario could be identified as the optimal solution. However, the results suggest a greater sensitivity of the results to the classification scheme than to the buffer distance applied. Overall, if applied to high resolution flood depth maps, the method is efficient and suitable for application to large urban areas for flood risk management and insurance analysis purposes.
引用
收藏
页数:8
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共 34 条
  • [1] [Anonymous], 2013, Islam and Democracy: Perspectives on the Arab Spring
  • [2] Flood risk analyses-how detailed do we need to be?
    Apel, H.
    Aronica, G. T.
    Kreibich, H.
    Thieken, A. H.
    [J]. NATURAL HAZARDS, 2009, 49 (01) : 79 - 98
  • [3] Urban micro-scale flood risk estimation with parsimonious hydraulic modelling and census data
    Arrighi, C.
    Brugioni, M.
    Castelli, F.
    Franceschini, S.
    Mazzanti, B.
    [J]. NATURAL HAZARDS AND EARTH SYSTEM SCIENCES, 2013, 13 (05) : 1375 - 1391
  • [4] Characterising performance of environmental models
    Bennett, Neil D.
    Croke, Barry F. W.
    Guariso, Giorgio
    Guillaume, Joseph H. A.
    Hamilton, Serena H.
    Jakeman, Anthony J.
    Marsili-Libelli, Stefano
    Newham, Lachlan T. H.
    Norton, John P.
    Perrin, Charles
    Pierce, Suzanne A.
    Robson, Barbara
    Seppelt, Ralf
    Voinov, Alexey A.
    Fath, Brian D.
    Andreassian, Vazken
    [J]. ENVIRONMENTAL MODELLING & SOFTWARE, 2013, 40 : 1 - 20
  • [5] Bertsch R., 2019, EXPLORING NEW TECHNO
  • [6] Urban Flood Simulation Using Synthetic Storm Drain Networks
    Bertsch, Robert
    Glenis, Vassilis
    Kilsby, Chris
    [J]. WATER, 2017, 9 (12)
  • [7] Statistical model for economic damage from pluvial floods in Japan using rainfall data and socioeconomic parameters
    Bhattarai, Rajan
    Yoshimura, Kei
    Seto, Shinta
    Nakamura, Shinichiro
    Oki, Taikan
    [J]. NATURAL HAZARDS AND EARTH SYSTEM SCIENCES, 2016, 16 (05) : 1063 - 1077
  • [8] Urban water management in cities: historical, current and future regimes
    Brown, R. R.
    Keath, N.
    Wong, T. H. F.
    [J]. WATER SCIENCE AND TECHNOLOGY, 2009, 59 (05) : 847 - 855
  • [9] Butler H, 2016, RTREE
  • [10] Projected changes in extreme precipitation over Scotland and Northern England using a high-resolution regional climate model
    Chan, Steven C.
    Kahana, Ron
    Kendon, Elizabeth J.
    Fowler, Hayley J.
    [J]. CLIMATE DYNAMICS, 2018, 51 (9-10) : 3559 - 3577