Preprints
https://doi.org/10.5194/essd-2025-134
https://doi.org/10.5194/essd-2025-134
14 Oct 2025
 | 14 Oct 2025
Status: this preprint is currently under review for the journal ESSD.

Thermo-hydrological observatory in a permafrost river valley landscape in Syrdakh, Central Yakutia

Eric Pohl, Christophe Grenier, Antoine Séjourné, Frédéric Bouchard, Emmanuel Léger, Albane Saintenoy, Pavel Konstantinov, Amélie Cuynet, Catherine Ottlé, Christine Hatté, Aurélie Noret, Kensheri Danilov, Kirill Bazhin, Ivan Khristoforov, Daniel Fortier, Alexander Fedorov, and Emmanuel Mouche

Abstract. Permafrost thaw affects the global carbon cycle and can significantly alter landscape morphology and associated processes of mass and energy transfer. An understudied aspect of affected permafrost landscapes are ubiquitous rivers connecting thermokarst lakes. These ubiquitous features of Arctic landscapes exhibit particularly high variability in water and energy transfer, and thus provide an excellent field laboratory for analyzing how expected changes in meteorological forcing under climate change affect permafrost dynamics and carbon exchange within the land- and limnoscape. This paper presents a database from 2012 through 2022 for one such small stream connecting two thermokarst lakes. First, two main stream cross sections were instrumented with multiple thermistor chains to record temperature evolution from the surface to different soil depths. The cross sections covered different topography and vegetation cover. One was located near the upper, and one in between the two thermokarst lakes. The main focus was set on the cross section midway between the two lakes due to the absence of a thermal imprint from the lake. Air, water, and ground temperatures, as well as river water parameters, and soil properties of the surrounding environment were measured as time series or single tests during annual field campaigns. The data are organized in three main categories: atmosphere, water and ground, and are complemented by a GIS including a digital surface model and an ortho-mosaic photo of the entire river valley to facilitate the search for measurements of interest. The database comes with a complete set of scripts to process any of the data, which are provided in CSV or other easily accessible standard file formats. Ultimately, the data can be used to develop models and validate numerical codes for improving the representation of permafrost processes in land surface and climate models where climate change induces significant changes in heat and mass transfer. All data and processing scripts are available through an online repository (https://doi.org/10.5281/zenodo.14619854; Pohl et al. (2025)).

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Eric Pohl, Christophe Grenier, Antoine Séjourné, Frédéric Bouchard, Emmanuel Léger, Albane Saintenoy, Pavel Konstantinov, Amélie Cuynet, Catherine Ottlé, Christine Hatté, Aurélie Noret, Kensheri Danilov, Kirill Bazhin, Ivan Khristoforov, Daniel Fortier, Alexander Fedorov, and Emmanuel Mouche

Status: open (until 20 Nov 2025)

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Eric Pohl, Christophe Grenier, Antoine Séjourné, Frédéric Bouchard, Emmanuel Léger, Albane Saintenoy, Pavel Konstantinov, Amélie Cuynet, Catherine Ottlé, Christine Hatté, Aurélie Noret, Kensheri Danilov, Kirill Bazhin, Ivan Khristoforov, Daniel Fortier, Alexander Fedorov, and Emmanuel Mouche

Data sets

Thermo-hydrological observatory in a permafrost river valley landscape in Syrdakh, Central Yakutia E. Pohl et al. https://doi.org/10.5281/zenodo.14619854

Eric Pohl, Christophe Grenier, Antoine Séjourné, Frédéric Bouchard, Emmanuel Léger, Albane Saintenoy, Pavel Konstantinov, Amélie Cuynet, Catherine Ottlé, Christine Hatté, Aurélie Noret, Kensheri Danilov, Kirill Bazhin, Ivan Khristoforov, Daniel Fortier, Alexander Fedorov, and Emmanuel Mouche
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Latest update: 14 Oct 2025
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Short summary
Permafrost is widespread in the Northern Hemisphere and is thawing due to climate warming, impacting energy and mass transfers. Small streams emerge alongside lakes when ice in the ground melts away, potentially accelerating thawing and biogeochemical activity in a positive feedback cycle. This study provides a comprehensive dataset on these little-studied streams, including thermally and hydrologically important variables essential for improving numerical models.
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