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March 29, 2026Water0 citationsOpen Access

Everything Comes Down to Timing: Optimal Green Infrastructure Placement and the Effect of Within-Storm Variability

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SNSeonwoo NamPusan National UniversityMKMinseok KimPusan National University

Key Points

  • The study aims to evaluate how the timing of rainfall affects the effectiveness of green infrastructure in mitigating urban flooding.
  • Developed a timescale-based framework linking peak reduction to storm timing and network response.
  • Analyzed runoff generation, interception, and routing using a convolution representation.
  • Evaluated 2351 observed hourly storm events across various catchment responses.
  • Demonstrated that peak reduction efficiency varies with storm duration and network response time.
  • Found that highly concentrated storms can significantly alter optimal infrastructure placement.
  • Quantified the impact of realistic storm structures on effectiveness compared to a uniform design storm.

Abstract

Urban flood peak mitigation by green infrastructure (GI) is fundamentally a timing problem. Because GI storage is finite, interception occurs only within a brief active window; whether it reduces the outlet peak depends on GI placement in the network, routing lags, and rainfall timing. Here, we develop a timescale-based framework that links outlet peak reduction to the alignment among within-storm temporal structure, network response, and GI filling dynamics, providing a compact way to interpret when different network positions become most effective under a fixed GI design. Starting from a general convolution representation of runoff generation, interception, and routing, we show that peak reduction efficiency and location ranking can be organized by two nondimensional ratios—comparing storm duration and network response time to a characteristic GI filling time—plus simple descriptors of within-storm temporal structure. Under uniform rainfall, these ratios yield an interpretable regime diagram with analytical transition curves between downstream-, mid-network-, and upstream-optimal placement for a generic dispersive routing representation. Relaxing the uniform-rainfall assumption shows that within-storm variability can substantially reorganize these regimes because storm timing controls both how long GI storage remains available before it fills and which routed contributions overlap to form the outlet peak. Highly concentrated storms and storms with early internal peaks are especially likely to reorder the ranking of candidate locations relative to the uniform-rainfall baseline. Using 2351 observed hourly storm events evaluated across virtual catchments spanning fast to slow network responses, we quantify how often realistic event structure alters the optimal location and the regret associated with adopting a uniform design storm. The results motivate robustness-oriented placement strategies based on ensembles of plausible storm temporal structures, organized within the proposed timescale diagram rather than reliance on a single design hyetograph.

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Cite This Study

Nam et al. (2026) studied this question.

synapsesocial.com/papers/69c8c3bdde0f0f753b39eacfhttps://doi.org/10.3390/w18070790
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