Exploring the Potential of Unmanned Aerial System‐Based Topographic Indices Maps to Evaluate Storm Drain Positioning

ABSTRACT

Urbanisation, climate uncertainty, and limited city budgets have heightened the need for efficient urban drainage management. While advanced hydrodynamic models assess the performance of drainage networks, they are computationally intensive, time‐consuming, and expensive. This study introduces a spatial analysis framework that integrates the Topographic Wetness Index (TWI) and the Topographic Control Index (TCI), derived from high‐resolution Digital Surface Models (DSMs) captured using Unmanned Aerial Systems (UAS), to evaluate storm drain positioning relative to surface‐water flowpaths and microtopographic controls; however, it does not account for subsurface pipe capacity or sewer network performance. TWI was used to assess whether storm drains align with surface flow paths, while TCI identified drains located within topographic depressions. The optimal TWI threshold (90th percentile) was determined by comparing it with the 1‐in‐100‐year Environment Agency flood map. Using this threshold, TWI‐based classification achieved 53% accuracy and 75% precision in identifying drains along flow paths, while TCI‐based analysis demonstrated 92% accuracy and 79% precision for detecting drains within depressions. The combined framework enables the identification of drainage inefficiencies at street level, informing maintenance prioritisation and the integration of nature‐based solutions. By using UAS‐derived geospatial data and topographic modelling, this approach provides a Tier 1 screening tool that is cost‐effective, scalable, and proactive for adaptive stormwater planning.