The prediction of flood damage in coastal urban areas

被引:4
|
作者
Pariartha, G. [1 ]
Goonetilleke, A. [2 ]
Egodawatta, P. [2 ]
Mirfenderesk, H. [3 ]
机构
[1] Udayana Univ, Engn Fac, Badung, Bali, Indonesia
[2] Queensland Univ Technol QUT, Sci & Engn Fac, GPO Box 2434, Brisbane, Qld 4001, Australia
[3] Gold Coast Nat Hazards Planning & Environm Div, POB 5042 GCMC 9726, Gold Coast, Qld, Australia
关键词
RISK-MANAGEMENT; UNCERTAINTY;
D O I
10.1088/1755-1315/419/1/012136
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The increase of impervious surfaces in the urban area triggers a flood. A flood occurs area with a dense population that will result in a lot of damage. The flood simulation itself is not adequate to calculate the flood damage, as it only shows the flood depth and extent. It needs the capability of mapping software to map the vulnerable area. Accordingly, the research study's aim is to propose the methodology to predict the flood damage on the coastal urban area by combining the flood simulation model with GIS mapping software. MIKE FLOOD and ArcGIS were used to represent the flood simulation model and mapping software. The flood depth and inundation area were calculated with MIKE FLOOD; meanwhile, the residential house was mapped using ArcGIS. Both of MIKE FLOOD and ArcGIS were then combined to obtain the flood depth in each residential house. Moreover, to value the flood damage in monetary terms, the depth-damage curve and average house prices were applied. The result shows that the majority of the inundation caused by riverine flood and coastal area is the place where the largest inundation area occurs. As the flood appears in a residential area, the flood damage of the residential building in terms of annual average damage (AAD) was obtained with the amount of $8,716,227.67 calculated from six AEPs (50%, 20%, 10%, 5%, 2%, and 1%).
引用
收藏
页数:10
相关论文
共 50 条
  • [31] Gaseous mercury in coastal urban areas
    Soerensen, Anne L.
    Skov, Henrik
    Johnson, Matthew S.
    Glasius, Marianne
    ENVIRONMENTAL CHEMISTRY, 2010, 7 (06) : 537 - 547
  • [32] Groundwater flooding in coastal urban areas
    Prigiobbe, Valentina
    ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY, 2019, 258
  • [33] Modelling flash flood risk in urban areas
    Xia, Junqiang
    Falconer, Roger A.
    Lin, Binliang
    Tan, Guangming
    PROCEEDINGS OF THE INSTITUTION OF CIVIL ENGINEERS-WATER MANAGEMENT, 2011, 164 (06) : 267 - 282
  • [34] A framework for flood impact assessment in urban areas
    Hammond, Michael J.
    Chen, Albert S.
    Butler, David
    Djordjevic, Slobodan
    Manojlovic, Natasa
    FLOODS: FROM RISK TO OPPORTUNITY, 2013, 357 : 41 - +
  • [35] Reduction of flood damages in urban areas of Canada
    Watt, E
    URBAN WATER MANAGEMENT: SCIENCE TECHNOLOGY AND SERVICE DELIVERY, 2003, 25 : 105 - 114
  • [36] Rationale for flood prediction in karst endorheic areas
    Iacobellis, Vito
    Castorani, Antonio
    Di Santo, Antonio Rosario
    Gioia, Andrea
    JOURNAL OF ARID ENVIRONMENTS, 2015, 112 : 98 - 108
  • [37] Assessing adaptation strategies against flood risk in urban coastal areas through Izmir Karsiyaka coastline case
    Ercanli, Cagla
    Savasir, Gokcecicek
    MEGARON, 2022, 17 (02): : 274 - 291
  • [38] Development of flood probability charts for urban drainage network in coastal areas through a simplified joint assessment approach
    Archetti, R.
    Bolognesi, A.
    Casadio, A.
    Maglionico, M.
    HYDROLOGY AND EARTH SYSTEM SCIENCES, 2011, 15 (10) : 3115 - 3122
  • [39] Characterization of Coastal Flood Damage States for Residential Buildings
    Baradaranshoraka, Mohammad
    Pinelli, Jean-Paul
    Gurley, Kurt
    Zhao, Mingwei
    Peng, Xinlai
    Paleo-Torres, Andres
    ASCE-ASME JOURNAL OF RISK AND UNCERTAINTY IN ENGINEERING SYSTEMS PART A-CIVIL ENGINEERING, 2019, 5 (01):
  • [40] Coastal Flood Modeling Challenges in Defended Urban Backshores
    Gallien, Timu W.
    Kalligeris, Nikos
    Delisle, Marie-Pierre C.
    Tang, Bo-Xiang
    Lucey, Joseph T. D.
    Winters, Maria A.
    GEOSCIENCES, 2018, 8 (12)