Multi-objective optimal design for flood risk management with resilience objectives
In flood risk management, the divergent concept of resilience of a flood defense system cannot be fully defined quantitatively by one indicator and multiple indicators need to be considered simultaneously. In this paper, a multi-objective optimization (MOO) design framework is developed to determine...
| Main Authors: | , , |
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| Other Authors: | |
| Format: | Journal Article |
| Language: | English |
| Published: |
2020
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| Online Access: | https://hdl.handle.net/10356/139600 |
| _version_ | 1826123391633981440 |
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| author | Su, Hsin-Ting Cheung, Sai Hung Lo, Edmond Yat-Man |
| author2 | School of Civil and Environmental Engineering |
| author_facet | School of Civil and Environmental Engineering Su, Hsin-Ting Cheung, Sai Hung Lo, Edmond Yat-Man |
| author_sort | Su, Hsin-Ting |
| collection | NTU |
| description | In flood risk management, the divergent concept of resilience of a flood defense system cannot be fully defined quantitatively by one indicator and multiple indicators need to be considered simultaneously. In this paper, a multi-objective optimization (MOO) design framework is developed to determine the optimal protection level of a levee system based on different resilience indicators that depend on the probabilistic features of the flood damage cost arising under the uncertain nature of rainfalls. An evolutionary-based MOO algorithm is used to find a set of non-dominated solutions, known as Pareto optimal solutions for the optimal protection level. The objective functions, specifically resilience indicators of severity, variability and graduality, that account for the uncertainty of rainfall can be evaluated by stochastic sampling of rainfall amount together with the model simulations of incurred flood damage estimation for the levee system. However, these model simulations which usually require detailed flood inundation simulation are computationally demanding. This hinders the wide application of MOO in flood risk management and is circumvented here via a surrogate flood damage modeling technique that is integrated into the MOO algorithm. The proposed optimal design framework is applied to a levee system in a central basin of flood-prone Jakarta, Indonesia. The results suggest that the proposed framework enables the application of MOO with resilience objectives for flood defense system design under uncertainty and solves the decision making problems efficiently by drastically reducing the required computational time. |
| first_indexed | 2024-10-01T06:03:54Z |
| format | Journal Article |
| id | ntu-10356/139600 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T06:03:54Z |
| publishDate | 2020 |
| record_format | dspace |
| spelling | ntu-10356/1396002020-05-20T07:47:37Z Multi-objective optimal design for flood risk management with resilience objectives Su, Hsin-Ting Cheung, Sai Hung Lo, Edmond Yat-Man School of Civil and Environmental Engineering Institute of Catastrophe Risk Management (ICRM) Engineering::Civil engineering Flood Risk Management Multi-objective Optimization In flood risk management, the divergent concept of resilience of a flood defense system cannot be fully defined quantitatively by one indicator and multiple indicators need to be considered simultaneously. In this paper, a multi-objective optimization (MOO) design framework is developed to determine the optimal protection level of a levee system based on different resilience indicators that depend on the probabilistic features of the flood damage cost arising under the uncertain nature of rainfalls. An evolutionary-based MOO algorithm is used to find a set of non-dominated solutions, known as Pareto optimal solutions for the optimal protection level. The objective functions, specifically resilience indicators of severity, variability and graduality, that account for the uncertainty of rainfall can be evaluated by stochastic sampling of rainfall amount together with the model simulations of incurred flood damage estimation for the levee system. However, these model simulations which usually require detailed flood inundation simulation are computationally demanding. This hinders the wide application of MOO in flood risk management and is circumvented here via a surrogate flood damage modeling technique that is integrated into the MOO algorithm. The proposed optimal design framework is applied to a levee system in a central basin of flood-prone Jakarta, Indonesia. The results suggest that the proposed framework enables the application of MOO with resilience objectives for flood defense system design under uncertainty and solves the decision making problems efficiently by drastically reducing the required computational time. MOE (Min. of Education, S’pore) 2020-05-20T07:47:36Z 2020-05-20T07:47:36Z 2018 Journal Article Su, H.-T., Cheung, S. H., & Lo, E. Y.-M. (2018). Multi-objective optimal design for flood risk management with resilience objectives. Stochastic Environmental Research and Risk Assessment, 32(4), 1147-1162. doi:10.1007/s00477-017-1508-7 1436-3240 https://hdl.handle.net/10356/139600 10.1007/s00477-017-1508-7 2-s2.0-85043262403 4 32 1147 1162 en Stochastic Environmental Research and Risk Assessment © 2018 Springer-Verlag GmbH Germany, part of Springer Nature. All rights reserved. |
| spellingShingle | Engineering::Civil engineering Flood Risk Management Multi-objective Optimization Su, Hsin-Ting Cheung, Sai Hung Lo, Edmond Yat-Man Multi-objective optimal design for flood risk management with resilience objectives |
| title | Multi-objective optimal design for flood risk management with resilience objectives |
| title_full | Multi-objective optimal design for flood risk management with resilience objectives |
| title_fullStr | Multi-objective optimal design for flood risk management with resilience objectives |
| title_full_unstemmed | Multi-objective optimal design for flood risk management with resilience objectives |
| title_short | Multi-objective optimal design for flood risk management with resilience objectives |
| title_sort | multi objective optimal design for flood risk management with resilience objectives |
| topic | Engineering::Civil engineering Flood Risk Management Multi-objective Optimization |
| url | https://hdl.handle.net/10356/139600 |
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