Yu et al. (2026) Coupled Bayesian inversion of time-lapse dispersive ground penetrating radar data to estimate soil hydraulic parameters

Identification

• Journal: Journal of Hydrology
• Year: 2026
• Date: 2026-04-01
• Authors: Yi Yu, Johan Alexander Huisman, Anja Klotzsche, Xiao Tao, Kun Zhang
• DOI: 10.1016/j.jhydrol.2026.135435

Research Groups

The specific affiliations of the authors (Yi Yu, Johan Alexander Huisman, Anja Klotzsche, Xiao Tao, Kun Zhang) are not provided in the snippet. However, based on the topic, the research likely originates from groups specializing in geophysics, hydrology, or environmental engineering.

Short Summary

This study introduces a coupled Bayesian inversion framework to estimate soil hydraulic parameters by analyzing time-lapse dispersive ground penetrating radar data.

Objective

• To develop and apply a coupled Bayesian inversion method for the estimation of soil hydraulic parameters using time-lapse dispersive ground penetrating radar (GPR) data.

Study Configuration

• Spatial Scale: Not explicitly mentioned, but typically plot to field scale for GPR applications.
• Temporal Scale: Time-lapse measurements, implying repeated observations over periods relevant to soil moisture dynamics (e.g., hours to days).

Methodology and Data

• Models used: Coupled Bayesian inversion framework; likely incorporates GPR forward models and hydrological models (specific models not named in snippet).
• Data sources: Time-lapse dispersive ground penetrating radar (GPR) data.

Main Results

• Not available in the provided pre-proof snippet, but the paper aims to demonstrate the successful estimation of soil hydraulic parameters using the proposed coupled Bayesian inversion of time-lapse dispersive GPR data.

Contributions

• Development of a novel coupled Bayesian inversion framework specifically tailored for integrating time-lapse dispersive GPR data to estimate soil hydraulic parameters, offering an advanced approach for characterizing subsurface hydrological properties.

Funding

• Not available in the provided pre-proof snippet.

Citation

@article{Yu2026Coupled,
  author = {Yu, Yi and Huisman, Johan Alexander and Klotzsche, Anja and Tao, Xiao and Zhang, Kun},
  title = {Coupled Bayesian inversion of time-lapse dispersive ground penetrating radar data to estimate soil hydraulic parameters},
  journal = {Journal of Hydrology},
  year = {2026},
  doi = {10.1016/j.jhydrol.2026.135435},
  url = {https://doi.org/10.1016/j.jhydrol.2026.135435}
}