PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
March 19, 2026Water Research2 citationsOpen Access

How can hydrological connectivity inform catchment scale stormwater flood management?

View Full Paper
YYYuxuan YaoGFGuangtao FuJWJames Webber

Key Points

  • The research aims to assess how hydrological connectivity, through the Index of Hydrological Connectivity, influences urban flooding dynamics.
  • Applied a spatially explicit Index of Hydrological Connectivity to urban flooding scenarios
  • Used a validated 2D hydrodynamic model to simulate flooding under various storm designs
  • Employed XGBoost machine-learning to analyze multi-scale IHC features and their impact on flood representation
  • IHC features improved the understanding of flooding patterns, especially at a 240 m neighborhood scale
  • Identified a depth-dependent shift where shallow floods are storage-limited and deep floods are conveyance-limited
  • Revealed how weak connectivity and neighborhood bottlenecks can amplify flood hazards

Abstract

• Hydrological connectivity (HC) controls catchment-scale flooding patterns. • Develops novel application of a HC index (IHC) to stormwater management. • IHC demonstrates best performance when a multi-scale analysis window is applied. • Shallow flooding is storage-limited; deep flooding is conveyance-limited. • IHC can align site-scale interventions with catchment flooding dynamics. Landscape-based stormwater solutions can attenuate runoff locally, yet translating hydrological benefits into catchment-scale flood mitigation often remains difficult. This shortfall reflects a current site-focused paradigm that overlooks the role of hydrological connectivity (HC) in organising flood inundation. HC has long informed process understanding in fluvial hydrology, but it has been less frequently operationalised as a spatial diagnostic for urban stormwater flooding. This study applies the spatially explicit, event-aware Index of Hydrological Connectivity (IHC) to diagnose connectivity controls on urban flooding at the catchment scale and to inform strategic planning. Flood inundation patterns were generated using a validated 2D hydrodynamic model under 10-, 30-, and 100-year design storms. An interpretable machine-learning method (XGBoost) was then trained on these simulated flood scenarios to evaluate the explanatory power of multi-scale IHC features. Results show that spatial aggregation of IHC features markedly improved the representation of the spatial patterns of flooding, with the best performance at a neighbourhood scale of 240 m. The analysis reveals a depth-dependent regime shift. Shallow flooding is storage-limited and governed by local heterogeneity, whereas hazardous depths are conveyance-limited, driven by slope energised inflow interacting with corridor continuity and bottlenecks. The inferred dependence is nonlinear and interaction-rich, with hazard amplified when slope-energised inflow coincides with neighbourhood bottlenecks and weak or highly heterogeneous connectivity, while strong corridor continuity can produce threshold-like reductions in hazard. Overall, IHC offers a diagnostic basis for delineating flood conveyance corridors, connectivity bottlenecks, and slope energised inflow feeders that govern where hazardous inundation initiates, concentrates, and propagates. It therefore helps prioritise intervention locations, enabling site-scale measures to operate as a coherent, catchment-scale system.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Yao et al. (2026) studied this question.

synapsesocial.com/papers/69bb9212496e729e6297f531https://doi.org/10.1016/j.watres.2026.125767
Ask AI
Helpful
Bookmark
Share
View Full Paper