Impact of urban gray infrastructure on urban flooding : a city-scale drainage and surface water modeling framework

Abstract

Addressing urban floods is an escalating concern owing to the rising incidence of heavy precipitation events and the intricacies of urban drainage and hydrodynamics. This study introduces an advanced city-scale urban flood modeling framework that dynamically integrates the role of gray infrastructure (e.g., roads, buildings, and drainage systems) and real-time storage dynamics in urban drainage networks. The framework features innovative dual-mode flow equations for inlet systems—capturing both surface water inflow and drainage over spillage—alongside a dynamic storage model that adapts to real-time mass balance constraints. When applied to the Hong Kong case study, the proposed model demonstrates high predictive accuracy, as validated against historical flood records from the extreme rainfall event in September 2023 and Sentinel-1 satellite observations. The model yields a Mean Absolute Percentage Error (MAPE) of 14 % in spatial inundation mapping. The results reveal the critical role of gray infrastructure and drainage system design in shaping urban flood dynamics, offering insights into low pipe utilization, inlet density effects, and the efficacy of drainage tunnels in flood mitigation. Specifically, drainage tunnels are shown to reduce pipe stress and flood depths by up to 30 %, underscoring their importance in urban flood management strategies. These findings provide quantitative tools and practical guidance for planners and hydrologists aiming to develop flood-resilient infrastructure.