Bae et al. (2026) On the Stability and Sensitivity of Climate‐Informed Flood Frequency Models

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

Identification

• Journal: Geophysical Research Letters
• Year: 2026
• Date: 2026-10-24
• Authors: Kichul Bae, Jeongwoo Hwang, Chandramauli Awasthi, A. Sankarasubramanian
• DOI: 10.1029/2026gl124039

Research Groups

Not explicitly mentioned in the abstract.

Short Summary

This study develops a semi-parametric statistical framework with a bounded logistic link function to project flood changes under climate change, demonstrating its superior stability and realism compared to conventional log-linear models, especially under high precipitation conditions.

Objective

• To develop and evaluate a semi-parametric statistical framework that constrains flood variability using a bounded logistic link function for more reliable flood change projections under climate change, addressing the limitations of conventional log-linear models.

Study Configuration

• Spatial Scale: 548 natural basins across the coterminous United States.
• Temporal Scale: Implied for future flood change projections, but specific temporal periods are not detailed in the abstract.

Methodology and Data

• Models used: Semi-parametric statistical framework, bounded logistic link function, log-linear formulations (for comparison).
• Data sources: Hydroclimatically analogous samples, data from 548 natural basins across the coterminous United States (implies hydrological and climate data, but specific types like satellite/observation/reanalysis are not detailed).

Main Results

• The proposed semi-parametric framework yields more stable and realistic flood quantile estimates.
• It performs particularly well under high precipitation conditions.
• It better preserves flood sensitivity to climate forcings.
• Conventional log-linear formulations can produce unrealistically large flood estimates.

Contributions

• Development of a novel semi-parametric statistical framework with a bounded logistic link function for flood change projections.
• Introduction of a method to constrain flood variability, leading to more realistic flood estimates.
• Demonstration of improved stability, realism, and preservation of flood sensitivity compared to conventional log-linear models.
• Highlights the value of bounded, locally informed statistical models for robust flood risk assessment.

Funding

Not mentioned in the abstract.

Citation

@article{Bae2026Stability,
  author = {Bae, Kichul and Hwang, Jeongwoo and Awasthi, Chandramauli and Sankarasubramanian, A.},
  title = {On the Stability and Sensitivity of Climate‐Informed Flood Frequency Models},
  journal = {Geophysical Research Letters},
  year = {2026},
  doi = {10.1029/2026gl124039},
  url = {https://doi.org/10.1029/2026gl124039}
}