Yang et al. (2026) Impacts of spatial-temporal rainfall structures and antecedent wetness on flood variability at the catchment scale

Identification

• Journal: Journal of Hydrology
• Year: 2026
• Date: 2026-01-29
• Authors: Wencong Yang, Changming Li, Hanbo Yang
• DOI: 10.1016/j.jhydrol.2026.135019

Research Groups

• Department of Hydraulic Engineering, Tsinghua University, Beijing 100084, China
• State Key Laboratory of Hydro-Science and Engineering, Tsinghua University, Beijing 100084, China

Short Summary

This study introduces a novel approach to quantify flood variability by analyzing the impacts of spatial-temporal rainfall structures and antecedent wetness, while holding rainfall intensity constant, across 140 catchments in China. It reveals that antecedent wetness is the dominant factor influencing flood peak variability, underscoring the necessity of incorporating these factors into flood risk assessments.

Objective

• To develop a new approach to derive and quantify flood variability using different combinations of "event indicators" (describing spatial-temporal rainfall dynamics and antecedent wetness) at the catchment scale, while holding rainfall intensity fixed.
• To uncover the effects of these event indicators on event flood variability and flood quantile uncertainty across diverse catchments.

Study Configuration

• Spatial Scale: 140 catchments across the Eastern Monsoon Region of China, with areas ranging from 304 square kilometers to 86,475 square kilometers.
• Temporal Scale: Daily flood events, focusing on event-scale variability.

Methodology and Data

• Models used:
  • Multivariate distribution (Copula) for generating synthetic event indicators.
  • Data-driven runoff model (likely incorporating Machine Learning techniques) for predicting flood peaks.
• Data sources:
  • Historical high-rainfall events.
  • Observations from 140 catchments in the Eastern Monsoon Region of China.

Main Results

• Single-peak temporal rainfall and spatially uniform rainfall are prevalent across events.
• Antecedent wetness has the greatest impact on flood peak variability, with an attributable coefficient of variance (CV) of 0.23.
• Temporal rainfall structures contribute a CV of 0.16 to flood peak variability.
• Spatial rainfall structures contribute a CV of 0.05 to flood peak variability.
• Spatial-temporal rainfall correlation has minimal effects on flood peak variability.
• Antecedent wetness and spatial rainfall structures exhibit greater impact in drier catchments.
• Temporal structures have less impact in larger, elongated catchments.
• For flood quantiles, variability in event indicators results in a mean CV of 0.15 across catchments for 50-year flood estimates.
• Uncertainty associated with unobserved hydrologic conditions accounts for 79% of total sampling uncertainty for flood quantiles.

Contributions

• Presents a novel approach to isolate and quantify the impacts of spatial-temporal rainfall structures and antecedent wetness on flood variability, controlling for rainfall intensity.
• Provides quantitative insights into the relative importance of different event indicators on flood peak variability and flood quantile uncertainty across a large and diverse set of catchments.
• Emphasizes the critical need to integrate spatial-temporal rainfall variability and antecedent wetness into flood risk estimation and hydrological process understanding.

Funding

• Not specified in the provided text.

Citation

@article{Yang2026Impacts,
  author = {Yang, Wencong and Li, Changming and Yang, Hanbo},
  title = {Impacts of spatial-temporal rainfall structures and antecedent wetness on flood variability at the catchment scale},
  journal = {Journal of Hydrology},
  year = {2026},
  doi = {10.1016/j.jhydrol.2026.135019},
  url = {https://doi.org/10.1016/j.jhydrol.2026.135019}
}