Bakhrel et al. (2025) Identifying Urban Pluvial Frequency Flooding Hotspots Using the Topographic Control Index and Remote Sensing Radar Images for Early Warning Systems

⚠️ Warning: This summary was generated from the abstract only, as the full text was not available.

Identification

• Journal: Water
• Year: 2025
• Date: 2025-12-10
• Authors: Unique Bakhrel, Nicholas Brake, Mahdi Feizbahr, Yong Je Kim, Hossein Hariri Asli, Liv Haselbach, Slater J. Macon
• DOI: 10.3390/w17243500

Research Groups

Not specified in the provided text.

Short Summary

This study integrates Sentinel-1 radar imagery and the Topographic Control Index (TCI) to identify and prioritize urban areas frequently experiencing post-rainfall ponding in Beaumont, Texas, revealing 99 natural flood-vulnerable depressions, with 74 identified as high-priority nuisance flooding hotspots.

Objective

• To identify urban areas that frequently experience post-rainfall ponding for effective flood mitigation and planning.

Study Configuration

• Spatial Scale: Urban depressions within Beaumont, Texas.
• Temporal Scale: Analysis of 6 major rainfall events (out of 159) where Sentinel-1 radar imagery was acquired within 6 hours of peak rainfall.

Methodology and Data

• Models used: Topographic Control Index (TCI).
• Data sources: Sentinel-1 radar imagery, ground-based flood sensor data, Beaumont’s two-year inundation map.

Main Results

• 378 flood-prone urban depressions were initially identified.
• A flood frequency map was generated using Sentinel-1 radar imagery acquired within 6 hours of peak rainfall for 6 out of 159 major rainfall events.
• Validation of radar-detected water pixels showed 100% precision, 70.87% recall, an F1-score of 82.95%, and 71.32% overall accuracy.
• Approximately 84% of medium-to-high TCI depressions overlapped with Beaumont’s two-year inundation map, confirming a strong relationship between TCI and observed flooding.
• A total of 124 depressions retained significant water; after excluding 25 engineered detention ponds, 99 natural depressions remained flood vulnerable.
• Among these, 74 depressions with medium or high TCI were identified as the highest-priority nuisance flooding hotspots.

Contributions

• Provides a reliable and cost-effective approach for identifying areas prone to frequent urban ponding by combining the Topographic Control Index (TCI) with radar imagery.
• Offers a practical framework to support decision-making for drainage improvements, hotspot identification, and early-warning system development in urban flood-prone regions.

Funding

Not specified in the provided text.

Citation

@article{Bakhrel2025Identifying,
  author = {Bakhrel, Unique and Brake, Nicholas and Feizbahr, Mahdi and Kim, Yong Je and Asli, Hossein Hariri and Haselbach, Liv and Macon, Slater J.},
  title = {Identifying Urban Pluvial Frequency Flooding Hotspots Using the Topographic Control Index and Remote Sensing Radar Images for Early Warning Systems},
  journal = {Water},
  year = {2025},
  doi = {10.3390/w17243500},
  url = {https://doi.org/10.3390/w17243500}
}