Benoît et al. (2026) A non-stationary trans-Gaussian model for daily rainfall over complex topography

Identification

• Journal: Hydrology and earth system sciences
• Year: 2026
• Date: 2026-07-29
• Authors: Lionel Benoît, Matthew P. Lucas, Denis Allard, Keri M. Kodama, Thomas W. Giambelluca
• DOI: 10.5194/hess-30-4799-2026

Research Groups

• Biostatistics and Spatial Processes (BioSP), INRAE, Avignon CEDEX 9, France
• Water Resources Research Center, University of Hawai‘i at M¯anoa, Honolulu, Hawaii, USA
• University of Hawai‘i Sea Grant College Program, University of Hawai‘i at M¯anoa, Honolulu, Hawaii, USA

Short Summary

This study presents a non-stationary trans-Gaussian model for daily rainfall over complex topography. The model combines the flexibility of a fully non-stationary framework with the ability to capture spatial dependencies through a Matérn covariance function.

Objective

• Develop a stochastic process that can accurately simulate daily rainfall fields over mountainous regions, accounting for strong horizontal gradients in rainfall statistics caused by orographic effects.

Study Configuration

• Spatial Scale: The study focuses on the Island of Hawai‘i (State of Hawaii, USA) with an area of 10,432 km2 and a highest point of 4207 m.
• Temporal Scale: Daily resolution

Methodology and Data

• Models used: Non-stationary trans-Gaussian geostatistical model
• Data sources: Rain gauge observations from the Island of Hawai‘i

Main Results

• The non-stationary trans-Gaussian model can skillfully reproduce orographic rainfall statistics as well as their variations in space.
• The model is able to capture the strong spatial gradients in rainfall caused by the orographic effect, including the wetter windward slopes and drier leeward slopes.

Contributions

• This study contributes to the development of a more accurate and flexible stochastic process for simulating daily rainfall fields over complex topography.
• The non-stationary trans-Gaussian model can be used to improve the accuracy of hydrological modeling in mountainous regions, including the Island of Hawai‘i.

Funding

• This research was funded by the University of Hawai‘i at M¯anoa and INRAE.

Citation

@article{Benoît2026nonstationary,
  author = {Benoît, Lionel and Lucas, Matthew P. and Allard, Denis and Kodama, Keri M. and Giambelluca, Thomas W.},
  title = {A non-stationary trans-Gaussian model for daily rainfall over complex topography},
  journal = {Hydrology and earth system sciences},
  year = {2026},
  doi = {10.5194/hess-30-4799-2026},
  url = {https://doi.org/10.5194/hess-30-4799-2026}
}