期刊论文详细信息
Water
Stochastic Urban Pluvial Flood Hazard Maps Based upon a Spatial-Temporal Rainfall Generator
Nuno Eduardo Simཞs3  Susana Ochoa-Rodríguez4  Li-Pen Wang1  Rui Daniel Pina3  Alfeu Sá Marques3  Christian Onof4  João P. Leitão2 
[1] Department of Civil Engineering, KU Leuven, Heverlee (Leuven) 3001, Belgium; E-Mail:;Eawag, Swiss Federal Institute of Aquatic Science and Technology, Dübendorf 8600, Switzerland; E-Mail:;MARE, Department of Civil Engineering, University of Coimbra, Coimbra 3030-788, Portugal; E-Mails:;Department of Civil and Environmental Engineering, Imperial College London, London SW7 2AZ, UK; E-Mails:
关键词: urban pluvial flooding;    flood hazard mapping;    flood risk mapping;    stochastic;    rainfall radar;    spatial-temporal;   
DOI  :  10.3390/w7073396
来源: mdpi
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【 摘 要 】

It is a common practice to assign the return period of a given storm event to the urban pluvial flood event that such storm generates. However, this approach may be inappropriate as rainfall events with the same return period can produce different urban pluvial flooding events, i.e., with different associated flood extent, water levels and return periods. This depends on the characteristics of the rainfall events, such as spatial variability, and on other characteristics of the sewer system and the catchment. To address this, the paper presents an innovative contribution to produce stochastic urban pluvial flood hazard maps. A stochastic rainfall generator for urban-scale applications was employed to generate an ensemble of spatially—and temporally—variable design storms with similar return period. These were used as input to the urban drainage model of a pilot urban catchment (~9 km2) located in London, UK. Stochastic flood hazard maps were generated through a frequency analysis of the flooding generated by the various storm events. The stochastic flood hazard maps obtained show that rainfall spatial-temporal variability is an important factor in the estimation of flood likelihood in urban areas. Moreover, as compared to the flood hazard maps obtained by using a single spatially-uniform storm event, the stochastic maps generated in this study provide a more comprehensive assessment of flood hazard which enables better informed flood risk management decisions.

【 授权许可】

CC BY   
© 2015 by the authors; licensee MDPI, Basel, Switzerland.

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