A Micro-Catchment Block-to-Inlet Framework for Diagnosing Nuisance Flood Failure Mechanisms under Dual Storm Typologies
Abstract
Tefera Shibeshi and Temesgen Mekuriaw Manderso
Urban neighborhoods, such as Kensington in Philadelphia, frequently encounter nuisance flooding, which is characterized by shallow surface ponding around street inlets during moderate rainfall events. These recurrent low-depth floods disrupt mobility, damage infrastructure, and disproportionately impact vulnerable communities, often occurring below conventional stormwater design thresholds. This study introduces an uncalibrated, diagnostic micro-catchment block-to-inlet modeling framework aimed at identifying localized hydraulic failure mechanisms, rather than replicating observed flood depths. High-resolution elevation data and parcel-scale impervious surface mapping were employed to delineate inlet-based micro-catchments, each approximately 5 ha in size. These micro-catchments were integrated into a comprehensive EPA SWMM (v5.2) hydraulic-hydrologic model of a 3.5 km2 urban drainage network located in Kensington, Philadelphia, USA. Two synthetic storm typologies were utilized to isolate contrasting failure modes: (i) a short-duration, high-intensity convective storm representing peak-limited conditions and (ii) a long-duration, high- volume frontal storm representing volume-driven surcharge. The findings suggest that short-duration intense storms lead to rapid inlet exceedance and transient hydraulic instability, whereas long-duration storms result in sustained system pressurization and prolonged surface flooding. In both storm scenarios, a consistent set of junctions and downstream corridors emerged as significant structural bottlenecks, with limited external discharge capacities constraining system performance. Although the framework is not calibrated to observed events, it offers actionable diagnostic insights into inlet-scale vulnerabilities and supports targeted infrastructure upgrades and real-time flood management strategies in densely populated urban neighborhoods.