A rapid cellular-automata screening study of green infrastructure (GI) strategies in Melbourne City Centre (Webber et al. 2020) found that intensive GI application substantially reduces pluvial flood depth and velocity but leaves residual risk, that effectiveness declines as rainfall intensity increases, and that many local strategies accumulate towards catchment-scale benefits. The authors posed an explicit future research question: where does the tipping point for those catchment-scale benefits lie, and how does it depend on what the screening framework omitted — pipe-network hydraulics (surcharge and throttling), heterogeneous combinations of interventions, and antecedent soil-moisture conditions. Follow-up work through 2026 has upscaled the screening framework, optimised GI placement with detailed 2D hydrodynamic models, examined green–grey network interactions on synthetic catchments, and diagnosed connectivity-controlled regime shifts, but no study has identified the tipping point or its dependence on placement, rainfall intensity, network hydraulics, and antecedent wetness, so the question remains open.

Background

Surface water (pluvial) flooding is inundation caused by intense rainfall generating runoff that exceeds the capacity of urban drainage and ponding of that runoff in low-lying areas, independent of river or coastal flooding. Green infrastructure (GI), also called sustainable drainage systems (SuDS) or nature-based solutions, comprises decentralised measures such as green roofs, rain gardens (shallow planted basins that retain and filter runoff), tree pits, and rainwater capture tanks that store or infiltrate rainfall near where it falls, in contrast to piped ('grey') drainage. Whether GI can meaningfully reduce flooding at the scale of a whole urban catchment — rather than only at the individual site — is contested, because the piped network, topography, and the timing (synchronisation) of runoff from many small storage units jointly control flood peaks. Webber, Fletcher, Cunningham, Fu, Butler and Burns (2020) applied a rapid scenario-screening framework to a 4.4 × 3.4 km catchment in Melbourne City Centre, Australia. The framework used CADDIES, a cellular-automata overland-flow model in which grid cells exchange water through simple rules instead of solving the full shallow-water equations, giving roughly a 5- to 20-fold speed-up over conventional hydrodynamic models at the cost of simplified physics. Rainfall events were described by annual exceedance probability (AEP), the probability in any year that rainfall of a given intensity is equalled or exceeded; 30 design events (five AEPs from 18% down to 1% × six durations) were screened. The underground drainage network was represented only as a constant water-removal rate per cell, so hydraulic phenomena such as pipe surcharge (pressurised flow backing water up into streets) and throttling (flow restriction at network bottlenecks) could not be simulated, a simplification validated for preliminary screening by Webber, Booth, Gunasekara, Fu and Butler (2019). GI measures were represented as cell-scale storage volumes and roughness changes; for rain gardens, likely antecedent soil moisture (the wetness of the soil before the storm, which controls how much additional storage is available) was lumped into a single static effective-porosity factor. The study found that no strategy completely prevented flooding, that decentralised rainwater capture performed best, that intervention effectiveness declined monotonically as events became more intense (strategies fill and then stop attenuating the peak), and that multiple smaller strategies accumulate towards catchment-scale benefits. This accumulation finding 'poses a future research question regarding where the tipping point for catchment-scale benefits lies' — the threshold of cumulative intervention beyond which local measures reduce, rather than merely delay or relocate, the catchment-scale flood peak. The framework's documented simplifications — drainage-network hydraulics beyond a constant removal rate (surcharge and throttling), uniform rather than heterogeneous combinations of interventions, and static rather than explicit representation of antecedent conditions — are limitations of the screening framework relevant to this question; the same group's follow-up work explicitly notes the lack of a full 1D pipe-flow simulation as a limitation for detailed design (Webber et al. 2021). Independent work frames the same context: McPhillips, Matsler, Rosenzweig and Kim (2021) showed that green stormwater infrastructure in US cities is mostly sized for small, frequent storms, so its behaviour near and beyond design extremes is exactly where knowledge is thin.

Problem Statement

For an urban catchment subject to intense rainfall, determine the tipping point at which cumulative green infrastructure interventions produce catchment-scale reductions in surface-water flood peaks — net reductions in peak flood depth and velocity across the catchment, rather than only local protection, delayed peaks, or displaced water. This determination requires jointly characterizing all of the following: (1) how the location of the threshold (in cumulative intervention extent) shifts with the spatial configuration and placement of interventions, including heterogeneous combinations of intervention types (e.g. green roofs, rain gardens, tree pits, decentralised rainwater capture) rather than uniform strategies in isolation; (2) how it shifts with rainfall intensity (annual exceedance probability) and with drainage-network hydraulics, including the pipe surcharge and throttling that the rapid screening framework did not represent; and (3) how it varies with antecedent soil-moisture conditions, rather than with static single-value storage assumptions.

References

  1. Webber, J. L., Fletcher, T. D., Cunningham, L., Fu, G., Butler, D., & Burns, M. J. (2020). Is green infrastructure a viable strategy for managing urban surface water flooding? Urban Water Journal 17(7), 598–608. DOI: 10.1080/1573062X.2019.1700286. https://doi.org/10.1080/1573062X.2019.1700286
  2. Webber, J. L., Fu, G., & Butler, D. (2019). Comparing cost-effectiveness of surface water flood management interventions in a UK catchment. Journal of Flood Risk Management 12(S2), e12523. DOI: 10.1111/jfr3.12523. https://doi.org/10.1111/jfr3.12523
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