Open AccessEnhanced efficiency of pluvial flood risk estimation in urban areas using spatial–temporal rainfall simulations
Author(s) -
Blanc J.,
Hall J.W.,
Roche N.,
Dawson R.J.,
Cesses Y.,
Burton A.,
Kilsby C.G.
Publication year - 2012
Publication title -
journal of flood risk management
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.049
H-Index - 36
ISSN - 1753-318X
DOI - 10.1111/j.1753-318x.2012.01135.x
Subject(s) - pluvial , flood myth , environmental science , flood risk assessment , flooding (psychology) , hydrology (agriculture) , 100 year flood , sampling (signal processing) , flood mitigation , urban area , water resource management , geography , geology , computer science , geotechnical engineering , psychology , oceanography , economy , archaeology , filter (signal processing) , economics , psychotherapist , computer vision
Urban areas are concentrations of flood risk because of the density of development and because they tend to be constructed in low‐lying areas. They may be subject to flooding from rivers or the sea but are also vulnerable to the effects of intense direct rainfall, which can overwhelm urban drainage systems, and cause complex and often localised patterns of pluvial flooding. The risk from pluvial flooding is particularly difficult to assess because it is sensitive to the spatial–temporal characteristics of rainfall, local run‐off and surface flow processes, the performance of urban drainage systems, and the exact location of buildings. Sampling the variability or uncertainty in all of these processes in order to generate accurate flood risk estimates quickly becomes computationally prohibitive, especially for large urban areas. In this paper, we evaluate alternative approaches for making use of high‐resolution spatial–temporal rainfall simulations in urban flood risk analysis. Flood depths are computed with a coupled sewer and surface flood model, and flood damage is estimated using standard depth‐damage criteria. Efficient sampling of rainfall events and judicious use of response surfaces that relate rainfall event properties to flood volumes and damages are evaluated and shown to reduce the computational expense of risk analysis by more than 70%. The risk analysis methodology is successfully demonstrated for two contrasting urban locations in the UK .