EGU General Assembly 2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Standardized automated data collection for soil C model parametrization at the regional scale of Russia

Taras Vasiliev, Artem Vladimirov, Alexander Pashkov, and Nadezda Vasilyeva
Taras Vasiliev et al.
  • V.V. Dokuchaev Soil Science Institute, Interdisciplinary Laboratory for Mathematical Modeling of Soil Systems, Russian Federation (

The aim of the study is to perform a regional scale (Russia) soil type-specific soil C models calibration with ESMs using Russian National Soil database. Particularly, to obtain temperature  and moisture dependencies of soil C cycle reaction rates, the model can be fitted to soil profiles of the same soil type in different climatic conditions. For this aim historical climate data, carbon concentration profiles and soil profile descriptions (soil type,  texture and other properties that can provide additional information to constrain model parameter values) are needed in different spatial locations. 

The regional soil database consists of standardized detailed descriptions of soil profiles for each soil type encountered in Russia, including soil carbon content and organic matter composition proxies, profile distribution of soil texture, nitrogen and pH.

We introduced a data collection system with a tool for field soil description according to the standard as well as a tool for soil determination which includes Kohonen algorithm to predict soil type based on the determined soil profile sequence of horizon indexes. Further the system allows automated RunaWFE based request for soil sample analysis (national method standards) which is obligatory accompanied with standard soil profile and samples descriptions. The system collects all data for expansion of regional soil database.

How to cite: Vasiliev, T., Vladimirov, A., Pashkov, A., and Vasilyeva, N.: Standardized automated data collection for soil C model parametrization at the regional scale of Russia, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-21414,, 2020


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