Challenges and opportunities of modelling carbon dioxide sequestration potential in Ukrainian soils

Authors

  • V. R. Cherlіnka Yuriy Fedkovych Chernivtsi National University
  • Y. M. Dmytruk Yuriy Fedkovych Chernivtsi National University
  • V. І. Sobko Chernivtsi branch of the State Institution "Soils Protection Institute of Ukraine"
  • M. V. Gunchak Chernivtsi branch of the State Institution "Soils Protection Institute of Ukraine"
  • T. І. Balan Yuriy Fedkovych Chernivtsi National University
  • L. V. Cherlіnka Yuriy Fedkovych Chernivtsi National University

DOI:

https://doi.org/10.31073/acss92-07

Keywords:

GSOCseq; carbon dioxide sequestration; predicative algorithms; modelling

Abstract

The article examines approaches to modelling carbon dioxide sequestration by soils at different scale levels and describes a number of problems encountered in this process. The main problems in the modelling of organic carbon reserves for the territory of Ukraine have been identified, among which: lack of high-resolution data (hard to access), including types of land use; need for harmonization of existing data; the need for predicative modelling of indicators (clay and organic carbon content) for areas where data are not available; significant amounts of machine time for actual modelling. The need for open access to archived data (technical reports) from large-scale soil surveys 1957-1990 is highlighted. Also, the need to access large-scale topographic data as in the form of scanned topographic maps M 1:10000 and vectorized isolines are substantiated. It is shown that calculations of areas based on rasters in the geographical coordinate system to ensure the same pixel size, regardless of the location within Ukraine, it is proposed to use the “Ukraine Albers conic equal area” projection based on the Datum Pulkovo 1942 for which the error in the lengths of the lines is only 0.1%. Within areas can be used as a proposed projection, as well as precise Gauss-Kruger projections (EPSG 28404-28407, 5565-5583). In this case, it is necessary to take into account the likelihood of finding individual areas in several of the listed zones. It is demonstrated that simulation allows to establish territories in which even the best practices of management do not provide neutralization of emission of organic carbon from soils. However, it is necessary to introduce a priority introduction of adaptive management of the soil resources of agro-landscapes that will contribute to carbon sequestration or minimization of its emission.

 

References

References

United Nations, and Canada. (1992). United Nations Framework Convention on Climate Change. [New York]: United Nations, General Assembly,

Kyoto Protocol to the United Nations Framework Convention on Climate Change. (1997). Dec. 10, 1997. 2303 U.N.T.S. 162.

Paris Agreement to the United Nations Framework Convention on Climate Change.(2015) Dec. 12, 2015. T.I.A.S. No. 16-1104.

Graham, F. (2021). COP26: Glasgow Climate Pact signed into history. Nature. DOI: 10.1038/d41586-021-03464-9.

IPCC. 2018. Global Warming of 1.5°C. An IPCC Special Report on the impacts of global warming of 1.5°C above pre-industrial levels and related global greenhouse gas emission pathways, in the context of strengthening the global response to the threat of climate change, sustainable development, and efforts to eradicate poverty [Masson-Delmotte, V., P. Zhai, H.-O. Pörtner, D. Roberts, J. Skea, P.R. Shukla, A. Pirani, W. Moufouma-Okia, C. Péan, R. Pidcock, S. Connors, J.B.R. Matthews, Y. Chen, X. Zhou, M.I. Gomis, E. Lonnoy, T. Maycock, M. Tignor, and T. Waterfield (Eds.)].

Boincean, B. P. & Dent, D. L. (2019). Farming the black earth. Sustainable and Climate-Smart Management of Chernozem Soil. Spring Nature, Cham, Switherland AG. doi: 10.1007/978-3-030-22533-9.

Lal, R. (2004). Soil carbon sequestration impacts on global climate change and food security. Science, 304(5677), 1623-1627. doi: 10.1126/science.1097396.

Vargas-Rojas, R., Cuevas-Corona, R., Yigini Y., Tong, Y., Bazza, Z. & Wiese L. (2018). International Yearbook of Soil Law and Policy. In Ginzky H., Dooley E., Heuser I.L., Kasimbazi E., Markus T., Qin T. (Eds.). International Yearbook of Soil Law and Policy. Cham, Springer International Publishing. pp. 373–395. doi: 10.1007/978-3-030-00758-4_18.

FAO. (2017). Unlocking the potential of soil organic carbon. Food and Agriculture Organization of the United Nations. Rome, Italy.

FAO. (2020). A protocol for measurement, monitoring, reporting and verification of soil organic carbon in agricultural landscapes – GSOC-MRV Protocol. Rome. doi: 10.4060/cb0509en.

FAO. (2021). Global Soil Organic Carbon Sequestration Potential Map (GSOCseq). URL: https://www.fao.org/global-soil-partnership/gsocseq-map/en.

FAO. (2020). Technical specifications and country guidelines for Global Soil Organic Carbon Sequestration Potential Map (GSOCseq). Rome, Italy. URL: https://www.fao.org/documents/card/ru/c/cb0353en.

Jenkinson, D. S. & Rayner, J. H. (1977). The turnover of soil organic matter in some of the Rothamsted classical experiments. Soil science, 123(5), 298-305. doi: 10.1097/00010694-197705000-00005.

Jenkinson, D. S. (1990). The turnover of organic carbon and nitrogen in soil. Philosophical Transactions of the Royal Society of London. Series B: Biological Sciences, 329, 361-368. doi: 10.1098/rstb.1990.0177.

Sierra, C. A., Müller, M. & Trumbore, S. E. (2012). Models of soil organic matter decomposition: the SoilR package, version 1.0. Geoscientific Model Development, 5.4, 1045-1060. doi: 10.5194/gmd-5-1045-2012.

Coleman, K. & Jenkinson, D. S. (1996). RothC-26.3-A Model for the turnover of carbon in soil. In: Powlson D.S., Smith P., Smith J.U. (Eds.). Evaluation of Soil Organic Matter Models. NATO ASI Series (Series I: Global Environmental Change). Vol. 38. Springer, Berlin, Heidelberg. doi: 10.1007/978-3-642-61094-3_17.

Falloon, P. & Smith, P. (2009). Modeling Soil Carbon Dynamics. In: Kutsch W. L., Bahn M., Heinemeyer A. (Eds.). Soil carbon dynamics: an integrated methodology. Cambridge University Press. doi: 10.1017/CBO9780511711794.

Mіtášová, H. & Mіtáš, L. (1993). Іnterpolatіon by regularіzed splіne wіth tensіon: І. Theory and іmplementatіon. Mathematіcal Geology, 25(6), 641-655.

GRASS Development Team. Geographіc Resources Analysіs Support System (GRASS GІS) Software. (2021). Versіon 7.8.6. Open Source Geospatіal Foundatіon, 2021. URL: http://grass.osgeo.org (onlіne; accessed: 1.09.2021).

R Development Core Team. (2021). R: A language and environment for statistical computing. R Foundation for Statistical Computing. URL: http://www.r-project.org.

Breiman, L., (2001). Random forests. Machine learning, 45(1), 5-32. doi: 10.1023/A:1010933404324.

NASA JPL. (2013). NASA Shuttle Radar Topography Mission Global 1 arc second. Distributed by NASA EOSDIS Land Processes DAAC. doi: 10.5067/MEaSUREs/SRTM/SRTMGL1.003. Accessed 2021-06-01.

Dmytruk, Y., Cherlinka, V. & Demyd, I. (2019). Predicative soil cartographic materials as an element of modern large-scale surveys. Visnyk of Lviv National Agrarian University: Agronomy, 23, 202-206. doi: 10.31734/agronomy2019.01.202. [in Ukrainian]

Iatsuk, I., Dmytruk, Y., Cherlinka, V. & Dent, D. (2021). Status and Problems of Normative Monetary Valuation of Land in Ukraine. In: Dmytruk, Y. & Dent, D. (Eds.). Soils Under Stress: More Work for Soil Science in Ukraine. Cham: Springer International Publishing. pp. 17-26. doi: 10.1007/978-3-030-68394-8_2.

Hofierka, J., Parajka, J., Mitasova, H. & Mitas, L. (2002). Multivariate interpolation of precipitation using regularized spline with tension, Transactions in GIS, 6(2), 135-150. doi: 10.1111/1467-9671.00101.

Cherlinka, V. R. (2019). Digital elevation models in soil science: theoretical and methodological bases and practical application: Extended Abstract of Dr. Biol. Sciences: 03.00.18. Dissertation, Chernivtsi, Yuriy Fedkovych Chernivtsi National University, 538 p. URL: https://drive.google.com/open?id=1TZubbaD3fNIk7FQUkSyZOdK_dPpozqpN [in Ukrainian].

Cherlinka, V. R. (2017). Influence of resolution of digital relief models on the quality of predicative simulation of soil cover. Soil Science. 18(1-2), 79-95. [in Ukrainian].

Cherlinka, V. R. & Dmytruk, Y. M. (2018). Solving existing problems with soil maps in Ukraine. Biological systems, 10(1), 298-308. URL: http://biosystems-journal.chnu.edu.ua/index.php?journal=BioSystems&page=article&op=view&path%5B%5D=https%3A%2F%2Fdoi.org%2F10.31861%2Fbiosystems2018.01.094.

Cherlinka, V. (2017). Using Geostatistics, DEM and remote sensing to clarify soil cover maps of Ukraine. In: Dent, D., Dmytruk, Y. (Eds.), Soil Science Working for a Living: Applications of soil science to present-day problems. Springer-Verlag GmbH, Cham, Switzerland, Ch. 7, pp. 89–100. doi: 10.1007/978-3-319-45417-7_7.

Cherlinka, V. R. (2017). Variations of predictive efficiency of soil maps depending on the methods of constructing educational samples of predicative algorithms. Ecology and noospherology, 28(3-4), 55-71. URL: http://erae.dp.ua/index.php/erae/article/view/20. [in Ukrainian].

Shein, E. V. (2009). Granulometric composition of soils: problems of investigation methods, interpretation of results and classifications. Pochvovedenie, 3, 309-317. URL: https://elibrary.ru/item.asp?id=11722362. [in Russian].

Viatkin, K., Zalavskyi, Y, Bihun, О., Lebed, V., Sherstiuk, O., Plisko, I. & Nakisko, S. (2018). Creation of the Ukrainian national soil organic carbon stocks map using digital soil mapping methods. Pochvovedenie i agrohimiya, 2, 5-17. URL: https://cyberleninka.ru/article/n/sozdanie-natsionalnoy-karty-zapasov-organicheskogo-ugleroda-v-pochvah-ukrainy-s-ispolzovaniem-tsifrovyh-metodov-pochvennogo. [in Russian].

Laktionova, T. M., Medvedev, V. V., Savchenko, K. V., Bigun, O. M., Nakisko, S. G. & Sheiko S. M. (2012). Soil properties of Ukraine database (structure & operating procedure). 2nd edition. Kharkiv: Apostrof. 150 p. URL: http://www.issar.com.ua/uk/vydannya/baza-dannyh-svoystva-pochv-ukrayny-struktura-y-poryadok-yspolzovanyya [in Russian].

Smith, J. O., Smith, P., Wattenbach, M., Gottschalk, P. I. A., Romanenkov V. A., Shevtsova, L. K., … Lisovoi, N. V. (2007). Projected changes in the organic carbon stocks of cropland mineral soils of European Russia and the Ukraine, 1990–2070. Global Change Biology, 13(2), 342-356. doi: 10.1111/j.1365-2486.2006.01297.x.

FAO. (2021). The EX-Ante Carbon-balance Tool (EX-ACT). Economic and Policy Analysis of Climate Change. URL: https://www.fao.org/in-action/epic/ex-act-tool/suite-of-tools/ex-act/en.

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Published

2021-12-20

How to Cite

Cherlіnka V. R., Dmytruk, Y. M., Sobko V. І., Gunchak, M. V., Balan T. І., & Cherlіnka L. V. (2021). Challenges and opportunities of modelling carbon dioxide sequestration potential in Ukrainian soils. AgroChemistry and Soil Science, 92, 62-70. https://doi.org/10.31073/acss92-07