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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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. |
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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 |
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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 |
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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 |
_version_ |
1703971255041916928 |