Uddin et al. (2026) A Framework for Assessing the Impact of Climate Change on Rainfall Extremes and Urban Flooding Using GIS Based SCS-CN and HEC-RAS Model

Identification

• Journal: Lecture notes in civil engineering
• Year: 2026
• Date: 2026-01-01
• Authors: Md. Salah Uddin, Md. Rezaul Karim, Ataur Rahman
• DOI: 10.1007/978-3-032-18708-6_5

Research Groups

• Department of Civil and Environmental Engineering (CEE), Islamic University of Technology (IUT), Bangladesh
• School of Engineering, Design and Built Environment, Western Sydney University, Australia

Short Summary

This study proposes an integrated framework using Global Climate Models (GCMs), GIS-based SCS-CN, and HEC-RAS models to assess the impact of climate change on rainfall extremes and urban flooding in the Balu River catchment, Bangladesh. It projects significant increases in extreme rainfall and peak discharge under future Shared Socioeconomic Pathways (SSPs), leading to an expanded spatial extent of flooding.

Objective

• To propose a comprehensive framework for assessing the impact of climate change on rainfall extremes and urban flooding.
• To project future changes in annual maximum daily precipitation and corresponding peak discharge under SSP2–4.5 and SSP5–8.5 scenarios for the Balu River catchment, Bangladesh.
• To estimate the spatial extent of increased flooding resulting from these projected changes using hydrodynamic modeling.

Study Configuration

• Spatial Scale: Balu River catchment area, Bangladesh.
• Temporal Scale:
  • Historical: 1980–2023 (rainfall data).
  • Future Projections:
    • Near future: 2015–2044
    • Mid future: 2045–2074
    • Far future: 2075–2100

Methodology and Data

• Models used:
  • Global Climate Model (GCM) - Multi-Model Ensemble (MME) mean from 10 CMIP6 GCMs.
  • Gumbel Extreme Value Type-I distribution - for frequency analysis of extreme rainfall.
  • GIS-based SCS-CN method - for runoff and peak discharge estimation.
  • HEC-HMS model - used in conjunction with SCS-CN for runoff and peak discharge.
  • HEC-RAS model - for estimating the spatial extent of increased flooding.
• Data sources:
  • Historical rainfall data (1980–2023) from Bangladesh Meteorological Department (BMD).
  • Outputs from 10 CMIP6 GCMs for future projections under SSP2–4.5 and SSP5–8.5.

Main Results

• Under SSP2–4.5, extreme rainfall is projected to increase by 13.39% (near future), 24.09% (mid future), and 27.51% (far future).
• Under SSP5–8.5, extreme rainfall is projected to increase by 18.60% (near future), 33.94% (mid future), and 74.32% (far future).
• Correspondingly, under SSP2–4.5, peak discharge is expected to rise by 19.20% (near future), 34.74% (mid future), and 39.71% (far future).
• Under SSP5–8.5, peak discharge is expected to rise by 26.77% (near future), 49.23% (mid future), and 109.68% (far future).
• The HEC-RAS model will be utilized to estimate the spatial extent of increased flooding resulting from these projected changes.

Contributions

• Develops and applies a comprehensive, integrated framework combining GCMs, GIS-based SCS-CN, HEC-HMS, and HEC-RAS models for assessing climate change impacts on urban flooding.
• Provides quantitative projections of future extreme rainfall and peak discharge increases for a specific catchment in Bangladesh under CMIP6 SSP scenarios.
• Offers a practical methodology for evaluating future urban flood hazards, which is critical for climate change adaptation and urban planning in vulnerable regions.

Funding

• No specific funding projects, programs, or reference codes are mentioned in the provided paper text.

Citation

@article{Uddin2026Framework,
  author = {Uddin, Md. Salah and Karim, Md. Rezaul and Rahman, Ataur},
  title = {A Framework for Assessing the Impact of Climate Change on Rainfall Extremes and Urban Flooding Using GIS Based SCS-CN and HEC-RAS Model},
  journal = {Lecture notes in civil engineering},
  year = {2026},
  doi = {10.1007/978-3-032-18708-6_5},
  url = {https://doi.org/10.1007/978-3-032-18708-6_5}
}