A probabilistic risk modelling chain for analysis of regional flood events

A probabilistic flood risk modelling chain is proposed for flood risk analysis with consideration of spatial spreading and temporal clustering of the flood events. The proposed method consists of (1) a continuous simulation of long-term climatic and hydrologic fields, (2) Monte-Carlo simulations of...

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Main Authors: Oliver, Julien, Qin, Xiaosheng, Madsen, Henrik, Rautela, Piyoosh, Joshi, Girish Chandra, Jorgensen, Gregers
Other Authors: School of Civil and Environmental Engineering
Format: Article
Language:English
Published: 2021
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Online Access:https://hdl.handle.net/10356/150550
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1505502021-06-14T08:56:44Z A probabilistic risk modelling chain for analysis of regional flood events Oliver, Julien Qin, Xiaosheng Madsen, Henrik Rautela, Piyoosh Joshi, Girish Chandra Jorgensen, Gregers School of Civil and Environmental Engineering Interdisciplinary Graduate School (IGS) Nanyang Environment and Water Research Institute Engineering::Environmental engineering Flood Risk Analysis Continuous Simulation A probabilistic flood risk modelling chain is proposed for flood risk analysis with consideration of spatial spreading and temporal clustering of the flood events. The proposed method consists of (1) a continuous simulation of long-term climatic and hydrologic fields, (2) Monte-Carlo simulations of a 1D river and inundation model and (3) a probabilistic loss model. In the first stage, three multisite multivariate weather generators were tested and a K-nearest neighbor weather generator (KNN-CAD v4) was found most suitable to reproduce hydrological extremes. The methodology was then applied to identify variations in risk between spatially coherent and simplified event sets generated from 5000 years of synthetic data across four river basins in Uttarakhand, India. The results showed that preserving the spatial coherency of regional events lead to a spreading of the T-year local event distributions on both sides of a uniform regional T-year return period. The specificity of the exposure and the correlations between local events translated into minimal (4%) differences in losses at high return periods (> 50 year) but larger difference (20%) at low return periods (5 to 10-year). The redistribution of loss frequencies led to negligible differences in the Annual Average Losses between the different event sets. In this application, a simplified event set structure with uniform but appropriate T-year return periods proved to capture reasonably well the averaged risk metrics regionally. This study illustrates the complexity of estimating regional flood risk accumulation and exemplifies how a probabilistic risk model chain with continuous simulation can provide a more detailed picture of flood risks. Economic Development Board (EDB) Nanyang Technological University The study was funded by the Economic Development Board (EDB) of Singapore (IPP Scholarship) and the DHI-NTU Research Centre and Education Hub. The work is closely affiliated with the Disaster Risk Assessment of Uttarakhand, an initiative of the Uttarakhand Disaster Recovery Programme (UDRP) funded by the World Bank. 2021-06-14T08:56:44Z 2021-06-14T08:56:44Z 2019 Journal Article Oliver, J., Qin, X., Madsen, H., Rautela, P., Joshi, G. C. & Jorgensen, G. (2019). A probabilistic risk modelling chain for analysis of regional flood events. Stochastic Environmental Research and Risk Assessment, 33, 1057-1074. https://dx.doi.org/10.1007/s00477-019-01681-3 1436-3240 https://hdl.handle.net/10356/150550 10.1007/s00477-019-01681-3 2-s2.0-85065718682 33 1057 1074 en Stochastic Environmental Research and Risk Assessment © 2019 Springer-Verlag GmbH Germany, part of Springer Nature. All rights reserved.
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Environmental engineering
Flood Risk Analysis
Continuous Simulation
spellingShingle Engineering::Environmental engineering
Flood Risk Analysis
Continuous Simulation
Oliver, Julien
Qin, Xiaosheng
Madsen, Henrik
Rautela, Piyoosh
Joshi, Girish Chandra
Jorgensen, Gregers
A probabilistic risk modelling chain for analysis of regional flood events
description A probabilistic flood risk modelling chain is proposed for flood risk analysis with consideration of spatial spreading and temporal clustering of the flood events. The proposed method consists of (1) a continuous simulation of long-term climatic and hydrologic fields, (2) Monte-Carlo simulations of a 1D river and inundation model and (3) a probabilistic loss model. In the first stage, three multisite multivariate weather generators were tested and a K-nearest neighbor weather generator (KNN-CAD v4) was found most suitable to reproduce hydrological extremes. The methodology was then applied to identify variations in risk between spatially coherent and simplified event sets generated from 5000 years of synthetic data across four river basins in Uttarakhand, India. The results showed that preserving the spatial coherency of regional events lead to a spreading of the T-year local event distributions on both sides of a uniform regional T-year return period. The specificity of the exposure and the correlations between local events translated into minimal (4%) differences in losses at high return periods (> 50 year) but larger difference (20%) at low return periods (5 to 10-year). The redistribution of loss frequencies led to negligible differences in the Annual Average Losses between the different event sets. In this application, a simplified event set structure with uniform but appropriate T-year return periods proved to capture reasonably well the averaged risk metrics regionally. This study illustrates the complexity of estimating regional flood risk accumulation and exemplifies how a probabilistic risk model chain with continuous simulation can provide a more detailed picture of flood risks.
author2 School of Civil and Environmental Engineering
author_facet School of Civil and Environmental Engineering
Oliver, Julien
Qin, Xiaosheng
Madsen, Henrik
Rautela, Piyoosh
Joshi, Girish Chandra
Jorgensen, Gregers
format Article
author Oliver, Julien
Qin, Xiaosheng
Madsen, Henrik
Rautela, Piyoosh
Joshi, Girish Chandra
Jorgensen, Gregers
author_sort Oliver, Julien
title A probabilistic risk modelling chain for analysis of regional flood events
title_short A probabilistic risk modelling chain for analysis of regional flood events
title_full A probabilistic risk modelling chain for analysis of regional flood events
title_fullStr A probabilistic risk modelling chain for analysis of regional flood events
title_full_unstemmed A probabilistic risk modelling chain for analysis of regional flood events
title_sort probabilistic risk modelling chain for analysis of regional flood events
publishDate 2021
url https://hdl.handle.net/10356/150550
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