Advancements in Soil Organic Carbon Mapping and Interpolation Techniques: A Case Study from Lithuania’s Moraine Plains

Monitoring soil organic carbon (SOC) is essential for assessing the sustainability of soil usage. This study explores the spatial variability and mapping of SOC in Lithuania’s Nevėžis Plain using various interpolation methods, with an emphasis on understanding the impacts of soil typological units,...

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Bibliographic Details
Published in:Sustainability 2024-06, Vol.16 (12), p.5157
Main Authors: Volungevicius, Jonas, Žydelis, Renaldas, Amaleviciute-Volunge, Kristina
Format: Article
Language:English
Subjects:
Accuracy
Agricultural land
Analysis
Carbon
Carbon content
Case studies
Classification
Land use planning
Machine learning
Methods
Remote sensing
Soil erosion
Soils
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Summary:Monitoring soil organic carbon (SOC) is essential for assessing the sustainability of soil usage. This study explores the spatial variability and mapping of SOC in Lithuania’s Nevėžis Plain using various interpolation methods, with an emphasis on understanding the impacts of soil typological units, moisture regimes, and erosion on SOC distribution. A total of 275 soil samples were collected from agricultural croplands at depths of 0–10 cm, supplemented by 38 samples from previous studies. The SOC map was created based on the contours of the Lithuanian soil geodatabase. Statistical analysis revealed that the distribution of SOC in the studied area was significantly influenced by soil moisture and the degree of erosion. Based on these findings, SOC mapping was conducted according to the contours of Lithuanian soils. Comparing the interpolation methods that were analyzed, it was found that the kriging, RBF, and EBK methods fail to adequately capture the minimum and maximum values of SOC, while the IDW fails to adequately capture only the minimum values. In summary, the integrated geographical approach is complex but applicable to SOC mapping. This method facilitates the creation of adaptable SOC maps that are both geographically and pedologically informed. Key principles to apply this approach for future research and practical application should include establishing a statistically reliable data foundation, categorizing samples based on contrasting soil moisture regime, degrees of erosion, and land use patterns, and developing contouring principles along with a criteria algorithm that enables accurate spatial interpolation of average SOC values.
ISSN:2071-1050
2071-1050
DOI:10.3390/su16125157