A Multi-Dimensional Contribution-Based Framework for Evaluating Urban Stormwater Management Efficiency
Urbanization and climate change amplify urban flooding risks, demanding efficient, data-minimal tools to strengthen flood resilience. This study presents a pioneering multi-dimensional framework that quantifies the contributions of source reduction, stormwater pipes, and drainage/flood control systems, circumventing the need for intricate hydrological models. Leveraging rainfall depth (mm), runoff volume (m3), and peak flow rate (m3/h) provides a comprehensive evaluation of stormwater management efficacy. Applied to a hypothetical city, City A, under 30- and 50-year rainfall scenarios, the framework reveals efficiencies of 91.0% for rainfall depth and runoff volume, and 90.8% for peak flow in the 30-year case (9% shortfall), declining to 75.7% peak flow efficiency with a 24.3% deficit in the 50-year scenario, underscoring constraints in extreme-event response. Contributions analysis shows stormwater pipes (42.8–47.6%, mean: 46.0%) and drainage/flood control (40.8–43.2%, mean: 41.6%) predominate, while source reduction adds 11.6–14.0% (mean: 12.4%). A primary contribution lies in reducing data demands by approximately 70% compared to traditional approaches, rendering this framework a practical, scalable solution for flood management and sponge city design in data-limited settings. These findings elucidate system vulnerabilities and offer actionable strategies, advancing urban flood resilience both theoretically and practically.
Authors
- Junqi Li (ORCID: https://orcid.org/0000-0002-6874-6795)
- Kun Mao
- Jiawei Li (ORCID: https://orcid.org/0000-0001-5193-3239)
Institutions
- University of British Columbia (CA)
- Energy Foundation (CN)
- Beijing University of Civil Engineering and Architecture (CN)
Publication Details
- Journal
- Water
- Published
- 2025-04-22
- DOI
- https://doi.org/10.3390/w17091246
- Citations
- 1
- Primary Topic
- Urban Stormwater Management Solutions
- Type
- article
- Field-Weighted Citation Impact
- 0.80
Funders
- National Key Research and Development Program of China