Sensitivity of flood loss estimates to building representation and flow depth attribution methods in micro-scale flood modelling

被引:54
作者
Bermudez, Maria [1 ]
Zischg, Andreas Paul [2 ]
机构
[1] Univ A Coruna, Water & Environm Engn Grp, La Coruna, Spain
[2] Univ Bern, Inst Geog, Oeschger Ctr Climate Change Res, Mobiliar Lab Nat Risks, CH-3012 Bern, Switzerland
基金
瑞士国家科学基金会;
关键词
Inundation modelling; Micro-scale; Building representation; Flood loss estimation; DAMAGE ASSESSMENT; CLIMATE-CHANGE; URBAN; SIMULATION; EXPOSURE; QUANTIFICATION; VULNERABILITY; UNCERTAINTY; SYSTEM; AREAS;
D O I
10.1007/s11069-018-3270-7
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
Thanks to modelling advances and the increase in computational resources in recent years, it is now feasible to perform 2-D urban flood simulations at very high spatial resolutions and to conduct flood risk assessments at the scale of single buildings. In this study, we explore the sensitivity of flood loss estimates obtained in such micro-scale analyses to the spatial representation of the buildings in the 2D flood inundation model and to the hazard attribution methods in the flood loss model. The results show that building representation has a limited effect on the exposure values (i.e. the number of elements at risk), but can have a significant impact on the hazard values attributed to the buildings. On the other hand, the two methods for hazard attribution tested in this work result in remarkably different flood loss estimates. The sensitivity of the predicted flood losses to the attribution method is comparable to the one associated with the vulnerability curve. The findings highlight the need for incorporating these sources of uncertainty into micro-scale flood risk prediction methodologies.
引用
收藏
页码:1633 / 1648
页数:16
相关论文
共 55 条
[1]   Improved methodology for processing raw LiDAR data to support urban flood modelling - accounting for elevated roads and bridges [J].
Abdullah, A. F. ;
Vojinovic, Z. ;
Price, R. K. ;
Aziz, N. A. A. .
JOURNAL OF HYDROINFORMATICS, 2012, 14 (02) :253-269
[2]   Spatial Global Sensitivity Analysis of High Resolution classified topographic data use in 2D urban flood modelling [J].
Abily, Morgan ;
Bertrand, Nathalie ;
Delestre, Olivier ;
Gourbesville, Philippe ;
Duluc, Claire-Marie .
ENVIRONMENTAL MODELLING & SOFTWARE, 2016, 77 :183-195
[3]   Two-Dimensional Dam-Break Flood Analysis in Data-Scarce Regions: The Case Study of Chipembe Dam, Mozambique [J].
Alvarez, Manuel ;
Puertas, Jeronimo ;
Pena, Enrique ;
Bermudez, Maria .
WATER, 2017, 9 (06)
[4]   Improving flood damage assessment models in Italy [J].
Amadio, Mattia ;
Mysiak, Jaroslav ;
Carrera, Lorenzo ;
Koks, Elco .
NATURAL HAZARDS, 2016, 82 (03) :2075-2088
[5]   A probabilistic modelling system for assessing flood risks [J].
Apel, H ;
Thieken, AH ;
Merz, B ;
Blöschl, G .
NATURAL HAZARDS, 2006, 38 (1-2) :79-100
[6]   Flood risk analyses-how detailed do we need to be? [J].
Apel, H. ;
Aronica, G. T. ;
Kreibich, H. ;
Thieken, A. H. .
NATURAL HAZARDS, 2009, 49 (01) :79-98
[7]   Quantification of uncertainties in flood risk assessments [J].
Apel, Heiko ;
Merz, Bruno ;
Thieken, Annegret H. .
INTERNATIONAL JOURNAL OF RIVER BASIN MANAGEMENT, 2008, 6 (02) :149-162
[8]   Urban micro-scale flood risk estimation with parsimonious hydraulic modelling and census data [J].
Arrighi, C. ;
Brugioni, M. ;
Castelli, F. ;
Franceschini, S. ;
Mazzanti, B. .
NATURAL HAZARDS AND EARTH SYSTEM SCIENCES, 2013, 13 (05) :1375-1391
[9]   Comparing Various Methods of Building Representation for 2D Flood Modelling In Built-Up Areas [J].
Bellos, Vasilis ;
Tsakiris, George .
WATER RESOURCES MANAGEMENT, 2015, 29 (02) :379-397
[10]   Development and Comparison of Two Fast Surrogate Models for Urban Pluvial Flood Simulations [J].
Bermudez, Maria ;
Ntegeka, Victor ;
Wolfs, Vincent ;
Willens, Patrick .
WATER RESOURCES MANAGEMENT, 2018, 32 (08) :2801-2815