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Resilience planning in hazards-humans-infrastructure nexus: A multi-agent simulation for exploratory assessment of coastal water supply infrastructure adaptation to sea-level rise.
- Source :
-
Environmental Modelling & Software . Mar2020, Vol. 125, pN.PAG-N.PAG. 1p. - Publication Year :
- 2020
-
Abstract
- Coastal water supply infrastructure systems are exposed to saltwater intrusion exacerbated by sea-level rise stressors. To enable assessing the long-term resilience of these systems to the impact of sea-level rise, this study developed a novel hazards-humans-infrastructure nexus framework that enables the integrated modeling of stochastic processes of hazard scenarios, decision-theoretic elements of adaptation planning processes of utility agencies, and dynamic processes of water supply infrastructure performance. Using the proposed framework and data collected from South Miami-Dade service area, a multi-agent simulation model was created to conduct exploratory assessments of the long-term resilience of water supply infrastructure under various sea-level rise scenarios and adaptation approaches. The results showed the capability of the proposed model for scenario landscape generation to discover robust adaptation pathways for enhanced infrastructure resilience under uncertainty. The analysis results could provide actionable scientific information to water infrastructure managers to improve their adaptation planning and investment decision-making processes. • Climatic hazard stressors are the most significant determinant of resilience in coastal water infrastructure systems. • Adaptive planning approach would increase the likelihood of achieving greater resilience. • Reactive planning approaches are unable to fully close the resilience gap induced by uncertainty. • Robust adaptation decision-making would enhance the long-term resilience of infrastructure systems. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 13648152
- Volume :
- 125
- Database :
- Academic Search Index
- Journal :
- Environmental Modelling & Software
- Publication Type :
- Academic Journal
- Accession number :
- 141735892
- Full Text :
- https://doi.org/10.1016/j.envsoft.2020.104636