Pei et al. (2026) Flooding algorithm combining hydrology and dynamic seed growth

Identification

• Journal: Natural Hazards
• Year: 2026
• Date: 2026-02-23
• Authors: Wenjie Pei, Yonggang Chen, Zhenkun Shi, Lifeng Du
• DOI: 10.1007/s11069-026-08033-9

Research Groups

• College of Environmental and Resource Sciences, Zhejiang A&F University, Hangzhou, China
• Hangzhou Tongji Surveying & Mapping Co., Ltd, Hangzhou, China

Short Summary

This study develops and validates an improved GIS-based seed propagation algorithm for rapid and accurate flood inundation simulation in data-scarce small and medium-sized river basins, demonstrating superior spatial accuracy (F1 score of 0.76) compared to HEC-RAS models.

Objective

• To develop and validate an efficient, GIS-based seed propagation algorithm for accurate and rapid flood inundation simulation in data-scarce small and medium-sized river basins, capable of deriving essential hydrological parameters and delineating inundation areas for multiple return periods.

Study Configuration

• Spatial Scale: Daoshi Town (139.1 km²) in Linan District, Hangzhou City, Zhejiang Province, China (study area); Shuiyang River and Dongjin River basins in Ningguo City, Anhui Province, China (validation area). Simulations were conducted at various Digital Elevation Model (DEM) resolutions (12.5 m, 30 m, 90 m).
• Temporal Scale: Flood inundation simulations for multiple return periods (5-year, 10-year, 20-year, 50-year, and 100-year floods). Rainfall durations of 6 hours and 24 hours were considered for hydrological parameter derivation. Validation was performed using a 100-year return period flood event (Typhoon Lekima, 10 August 2019).

Methodology and Data

• Models used:
  • Proposed: Improved Seed Propagation Algorithm (integrating GIS, hydrology, and hydraulics, with basin division using the D8 algorithm).
  • Hydrological calculations: Iterative reasoning formula method for peak flood flow, Manning-Strickler equation for peak flood water level.
  • Benchmark models: HEC-RAS 1D steady-flow model, HEC-RAS 2D unsteady-flow model.
• Data sources:
  • Digital Elevation Model (DEM) (12.5 m, 30 m, 90 m resolutions).
  • Zhejiang Province Atlas (for average point rainfall, variation coefficient, and point and area coefficients).
  • Sentinel-2 optical data (for background imagery).
  • Sentinel-1B Synthetic Aperture Radar (SAR) image (10 August 2019) for observed flood inundation extent.
  • Measured hydrological observations (peak water level records from Ningguo, Helixi, and Shabu stations).
  • Ningguo Hydrological Manual.
  • Geographic Information System (GIS) for spatial analysis and parameter derivation.

Main Results

• The maximum peak water level in Daoshi Town can reach 24.75 m during extreme flood events.
• Simulated inundated areas for Daoshi Town ranged from 11.19 km² (5-year flood) to 13.15 km² (100-year flood), with the increase in area being moderate due to terrain constraints.
• The proposed seed propagation algorithm achieved an F1-score of 0.76, demonstrating superior overall spatial accuracy compared to the HEC-RAS 1D steady-flow model (F1-score ~0.4) and the HEC-RAS 2D unsteady-flow model (F1-score ~0.6) in the validation area.
• The HEC-RAS 1D model tended to underestimate flood extent, while the HEC-RAS 2D model showed a tendency towards overestimation in wide valley areas.
• DEM resolution critically impacts simulation accuracy: 12.5 m and 30 m DEMs yielded similar high accuracy (F1-scores ~0.75-0.76), while the 90 m DEM resulted in a significant decline in accuracy (F1-score ~0.65) and localized overexpansion.
• The method effectively derives key hydrological parameters in data-scarce environments and enables rapid multi-scenario flood simulations with high computational efficiency (within minutes).

Contributions

• Developed an efficient, open-source framework for flood inundation simulation in data-scarce small and medium-sized river basins, integrating hydrological-hydraulic theories with GIS technologies.
• Automated the generation of essential hydrological parameters (storm attenuation index, design rainfall intensity, peak flow volume, peak water level) without requiring pre-prepared hydrological datasets.
• Introduced an improved seed propagation algorithm that incorporates basin division to enhance simulation continuity and accuracy by preventing cross-basin interference in complex river basins.
• Demonstrated superior spatial accuracy and balanced representation of flood spreading compared to HEC-RAS 1D and 2D models, making it a practical tool for flood assessment.
• Quantified the significant impact of DEM resolution on inundation simulation accuracy, highlighting the importance of high-resolution DEMs for capturing microtopographic features.

Funding

• Key Project of Science and Technology of Zhejiang (2019C03121)
• National Natural Science Foundation of China (41201408)
• Zhejiang Province Natural Science Foundation of China (LY16D010009)

Citation

@article{Pei2026Flooding,
  author = {Pei, Wenjie and Chen, Yonggang and Shi, Zhenkun and Du, Lifeng},
  title = {Flooding algorithm combining hydrology and dynamic seed growth},
  journal = {Natural Hazards},
  year = {2026},
  doi = {10.1007/s11069-026-08033-9},
  url = {https://doi.org/10.1007/s11069-026-08033-9}
}