Kokko et al. (2026) High resolution modelling of temporal and spatial dynamics in soil conditions in subarctic Finland using HydroBlocks model

Identification

• Journal: Hydrology and earth system sciences
• Year: 2026
• Date: 2026-08-11
• Authors: Emma-Riikka Kokko, Nathaniel W. Chaney, Daniel Guyumus, Luiz Carlos Salgueiro Donato Bacelar, Laura Torres‐Rojas, Jarkko Okkonen
• DOI: 10.5194/hess-30-5049-2026

Research Groups

• Oulu Mining School, University of Oulu (Finland)
• Environmental and Civil Engineering Department, Duke University (USA)
• Atmospheric and Oceanic Sciences, Princeton University (USA)
• Geological Survey of Finland (Finland)

Short Summary

This study configures the HydroBlocks model in subarctic and arctic Finland to estimate soil temperature and soil ice content at different depths with high spatial and temporal resolution. The results show that using local soil data from the Geological Survey of Finland improves the modeling accuracy.

Objective

• To develop a methodology for assessing small magnitude, ice-induced earthquakes (frost quakes) in subarctic Finland by estimating thermal stresses in the soil.
• To evaluate the performance of the HydroBlocks model in simulating soil conditions in Finland using local and global soil data.

Study Configuration

• Spatial Scale: Country-wide scale, with a spatial resolution of 90 m.
• Temporal Scale: Daily to hourly time steps, with a spin-up period of 5 years.

Methodology and Data

• Models used: HydroBlocks model, which uses the Noah-MP land surface scheme within the HRU framework.
• Data sources: Meteorological data from ERA5 LAND dataset, soil thickness and texture classes from SoilGrids database, and local soil data from Geological Survey of Finland.

Main Results

• The results show that using local soil data improves the modeling accuracy of snow water equivalent (SWE), soil temperature, and soil water content.
• The average RMSE and KGE values for SWE were 29 mm and 0.34, respectively, when using GTK's soil data.
• The average RMSE and KGE values for soil temperature were 1.3 °C and 0.7, respectively, when using GTK's soil data.

Contributions

• This study demonstrates the importance of using local soil data in land surface modeling to improve accuracy.
• The results show that the HydroBlocks model can be used to estimate soil conditions in Finland with high spatial and temporal resolution.

Funding

• Not specified in the paper.

Citation

@article{Kokko2026High,
  author = {Kokko, Emma-Riikka and Chaney, Nathaniel W. and Guyumus, Daniel and Bacelar, Luiz Carlos Salgueiro Donato and Torres‐Rojas, Laura and Okkonen, Jarkko},
  title = {High resolution modelling of temporal and spatial dynamics in soil conditions in subarctic Finland using HydroBlocks model},
  journal = {Hydrology and earth system sciences},
  year = {2026},
  doi = {10.5194/hess-30-5049-2026},
  url = {https://doi.org/10.5194/hess-30-5049-2026}
}