Urban green infrastructure for flood resilience: Runoff sink-source regime shifts and vegetation structure influences

Abstract

Over the period of rainfall, urban green infrastructures (UGI) function like a sponge by absorbing surface runoff as sinks; however, they will shift to sources once their runoff reduction capacities are exceeded. This dynamic of sink-source shifts, and its dependence on the vegetation structure, remain poorly understood, limiting the action of flood-resilient UGI strategies. This study employs MIKE SHE/11 model coupled with statistical analysis for such resolution. Across four scenarios ranging from light to heavy rainfall, we identified regime shifts in UGI system through the decreasing to increasing trends of sink fractions, typically occurring around 13–18 h after rainfall starts. Based on these regime shifts, we categorized the UGI system into vulnerable, reliable, and recoverable components, highlighting its heterogeneous performance. In addition, by examining the influence of vegetation structure on sink–source dynamics, we found that a higher probability of sinks under light rainfalls was associated with a greater leaf area index (LAI) and vegetation height standard deviation (VH_STD), while green volume (GV) and canopy height (CH) played a more prominent role under heavier rainfalls. Threshold effect analysis further revealed that, a high proportion of the recoverable parts met the thresholds of CH (82 %) and GV (85 %), whereas fewer reached the thresholds of LAI (15 %–19 %) and VH_STD (3 %–6 %). These findings underscore the importance of enhancing 3D vegetation configuration for UGI to adapt to flood impacts. Our study expects to provide actionable knowledge for understanding, quantification, and management of the runoff sink-source dynamics, informing UGI design and planning to achieve urban flood resilience.

Keywords

Urban green infrastructure / Flood resilience / Runoff sink-source / Flood risk management / Vegetation structure effects / Urban ecosystem services

Data availability statement

The datasets were provided by local agency and were confidential. Access could be requested through an official data-sharing agreement.

CRediT authorship contribution statement

Kejing Zhou: Writing – review & editing, Writing – original draft, Visualization, Validation, Software, Methodology, Investigation, Funding acquisition, Formal analysis, Data curation, Conceptualization. Fanhua Kong: Writing – review & editing, Writing – original draft, Validation, Supervision, Resources, Project administration, Methodology, Funding acquisition, Conceptualization. Haiwei Yin: Writing – review & editing, Supervision, Resources, Methodology, Investigation, Data curation, Conceptualization. Georgia Destouni: Writing – review & editing, Software, Methodology, Funding acquisition, Conceptualization. Xueying Zhuang: Writing – original draft, Investigation, Formal analysis, Data curation. Yulong Ban: Validation, Resources, Investigation, Data curation. Liding Chen: Resources, Project administration, Funding acquisition.

Declaration of competing interests

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgements

This study is supported by the National Key R&D Program of China (Grant No. 2022YFF1303102), the Global Engagement for Strategic Partnership project of Nanjing University, the China Scholarship Council (Grant No. 202406190182), and the Swedish Research Council (VR, Grant No. 2022–04672). The authors would like to thank the Kunshan Water Bureau for supporting this study through the project cooperation.

Supplementary materials

Supplementary material associated with this article can be found, in the online version, at doi:10.1016/j.geosus.2025.100333.

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