Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor | School of Design | en_US |
| dc.contributor.advisor | Hasdell, Peter (SD) | en_US |
| dc.creator | Liu, Yu | - |
| dc.identifier.uri | https://theses.lib.polyu.edu.hk/handle/200/14471 | - |
| dc.language | English | en_US |
| dc.publisher | Hong Kong Polytechnic University | en_US |
| dc.rights | All rights reserved | en_US |
| dc.title | Modeling complex flood risks in urban deltas : a morpho-social-ecological framework approach | en_US |
| dcterms.abstract | Urban deltas, characterized by low-lying topography, dense populations, and complex socio-ecological interactions, faced escalating flood risks due to the combined pressures of climate change and rapid urbanization. Sea-level rise, intensified rainfall patterns, and cascading typhoon impacts further exacerbated flood vulnerability. These factors contributed to non-stationary flood dynamics resulting from the interaction between anthropogenic modifications (e.g., increased impervious surfaces) and natural processes (e.g., sea-level rise). The increasing interconnectedness and complexity of expanding cities and regions, alongside the need to adapt to dynamic social and environmental conditions, posed additional challenges. | en_US |
| dcterms.abstract | In response to the escalating challenges posed by emerging processes within the coupled complex systems of urban deltas, social-ecological systems (SES) frameworks have been increasingly adopted to reconcile the dichotomy between urban and ecological models. Originating from critiques of traditional siloed approaches, SES frameworks theoretically recognized cities as coupled systems in which biophysical processes and socioeconomic activities co-evolved through feedback mechanisms. This stood in sharp contrast to conventional flood modeling paradigms, which reductively isolated individual system components when assessing flood drivers. Simultaneously, advancements in risk hazard theory and modeling techniques enhanced the understanding of complex feedback pathways. | en_US |
| dcterms.abstract | However, critical gaps persisted in existing studies, which predominantly: (1) failed to integrate elements of social-ecological systems across temporal, spatial, and functional scales in flood risk contexts; (2) overlooked intricate non-linear connections and complex feedback pathways among parameters; and (3) lacked the practical application of advanced modeling techniques to explore interrelationships, despite their widespread use in hydrologic modeling. | en_US |
| dcterms.abstract | In response to this gap in knowledge and its application, this research investigated the spatiotemporal interplay between social-ecological systems and resultant flood risk within an urbanizing delta by addressing four research objectives. First, it identified critical parameters governing ecological processes, social dynamics, and flood event characteristics in selected areas. Second, it developed theoretical frameworks that integrated multiscale indicators to measure and quantify these parameters. Third, it empirically tested the complex relationships between identified parameters and flood events through iterative analyses. Finally, the research synthesized the findings into adaptive planning strategies and principles. | en_US |
| dcterms.abstract | This research employed four iterative studies to progressively address the stated objectives, with findings and limitations from earlier studies informing the hypotheses and methodologies of subsequent ones. The first three studies applied integrated assessment methods, derived from a comprehensive literature review, to identify relevant parameters across multiple temporal and spatial scales, establish a comprehensive index system, and refine a morpho-social-ecological-flood framework. This framework integrated functional and morphological aspects of social, ecological, and geographic elements that contributed to flood characteristics. The final study employed Bayesian Belief Networks (BBNs) to test the framework in selected study areas, assessing the transformation of spatial adaptive potentials by attribute, evaluating transferability across districts, and extracting principles to enhance spatial adaptive capacity for flood resilience. | en_US |
| dcterms.abstract | Key findings included, on the one hand, the establishment and refinement of the morpho-social-ecological-flood framework, which encompassed 26 indicators and corresponding maps that quantified spatiotemporal dynamics. The research produced over 120 interrelationship maps and more than 160 bubble plots, which not only served as quantitative assessments of spatiotemporal qualities by attribute and their interrelationships over time, but also functioned as visual tools for exploring how these attributes contributed to flood risk. Analysis of these maps and plots revealed interrelationships among indicators, demonstrating the influence of both ecological and urbanization processes, as well as their morphological transformations (e.g., size, density, centrality, continuity, and complexity), on flood risk within a metropolitan delta. Critically, the results highlighted the mutual reinforcement of these processes through complex, non-linear dynamics, including synergies, trade-offs, and time lags. These intricate interactions underscored the complexity of coupled systems and supported the application of machine learning methods such as BBNs, which leveraged computational power to analyze geometric and configurational characteristics and their interrelationships. | en_US |
| dcterms.abstract | On the other hand, the application of the morpho-social-ecological-flood framework in Zhuhai City not only assessed location-specific flood risk and identified attributes influencing spatial adaptive potential at a static time point, but also developed a machine learning-based simulation to identify and predict future flood risk in dynamic temporal contexts. This predictive capability informed top-down strategies and adaptive pathways for the selected areas. | en_US |
| dcterms.extent | xix, 212 pages : color illustrations | en_US |
| dcterms.isPartOf | PolyU Electronic Theses | en_US |
| dcterms.issued | 2026 | en_US |
| dcterms.educationalLevel | Ph.D. | en_US |
| dcterms.educationalLevel | All Doctorate | en_US |
| dcterms.accessRights | open access | en_US |
Copyright Undertaking
As a bona fide Library user, I declare that:
- I will abide by the rules and legal ordinances governing copyright regarding the use of the Database.
- I will use the Database for the purpose of my research or private study only and not for circulation or further reproduction or any other purpose.
- I agree to indemnify and hold the University harmless from and against any loss, damage, cost, liability or expenses arising from copyright infringement or unauthorized usage.
By downloading any item(s) listed above, you acknowledge that you have read and understood the copyright undertaking as stated above, and agree to be bound by all of its terms.
Please use this identifier to cite or link to this item:
https://theses.lib.polyu.edu.hk/handle/200/14471