Feng et al. (2026) Flood modeling incorporating spatially heterogeneous rainfall and nonlinear routing mechanisms

Identification

• Journal: Journal of Hydrology
• Year: 2026
• Date: 2026-10-01
• Authors: Jing Feng, Keke Zhou, Jianzhu Li, Hongdong Song, Benlong Zhao, Hao Wang
• DOI: 10.1016/j.jhydrol.2026.136511

Research Groups

Jing Feng, Keke Zhou, Jianzhu Li, Hongdong Song, Benlong Zhao, Hao Wang (Specific institutional affiliations are not provided in the given text.)

Short Summary

This paper focuses on developing and applying flood models that integrate spatially heterogeneous rainfall and nonlinear routing mechanisms to improve flood prediction accuracy.

Objective

• To develop and apply flood modeling incorporating spatially heterogeneous rainfall and nonlinear routing mechanisms.

Study Configuration

• Spatial Scale: Not specified in the provided text.
• Temporal Scale: Not specified in the provided text.

Methodology and Data

• Models used: Flood modeling framework incorporating nonlinear routing mechanisms (specific model names not provided).
• Data sources: Spatially heterogeneous rainfall data (specific sources, e.g., satellite, observation, reanalysis, not provided).

Main Results

Not available in the provided text.

Contributions

The article aims to advance flood modeling by explicitly integrating the complexities of spatially varying rainfall and nonlinear hydrological routing, potentially leading to more accurate and realistic flood predictions compared to models that simplify these aspects.

Funding

Not available in the provided text.

Citation

@article{Feng2026Flood,
  author = {Feng, Jing and Zhou, Keke and Li, Jianzhu and Song, Hongdong and Zhao, Benlong and Wang, Hao},
  title = {Flood modeling incorporating spatially heterogeneous rainfall and nonlinear routing mechanisms},
  journal = {Journal of Hydrology},
  year = {2026},
  doi = {10.1016/j.jhydrol.2026.136511},
  url = {https://doi.org/10.1016/j.jhydrol.2026.136511}
}