Statistical Estimation of Soil Carbon Stocks in Chungcheong Province through Digital Soil Mapping and Multiple Linear Regression

Abstract

Digital soil mapping (DSM) is a statistical technique that utilizes soil characteristics and environmental factors to create spatial distribution maps representing soil properties. The SCORPAN model, consisting of soil (S), climate (C), organisms (O), relief (R), parent materials (P), age (A) and space (N), describes the environmental factors used in DSM techniques. The objectives of this study were to assess the spatial distribution map of soil carbon stocks in Chungcheong province and predict soil carbon stocks within the 0 - 30 cm depth using DSM technique. The minimum and maximum predicted carbon stocks were 25.11 ton C ha-1 and 183.55 ton C ha-1, respectively, with a mean of 46.92 ± 13.66 ton C ha-1. The spatial distribution map of soil carbon stocks revealed higher carbon stock in Chungcheongbuk-do, particularly in Danyang-gun, while lower carbon stocks were observed in the coastal areas of Chungcheongnam-do. The estimated economic value of soil carbon stocks in Chungcheong province was 406.3 billion won, based on the average soil carbon stock, agricultural land area and carbon offset trading price. The validation outcomes of the DSM are summarized as follows: the model achieved a coefficient of determination (R2) of 0.15, indicating the 15% confidence levels to the validation data. The mean absolute error (MAE) was 20.78, and the root mean square error (RMSE) was 29.51, respectively. The scatter plot between observed and predicted soil carbon stocks revealed that the predicted values were lower than the observed values, indicating a need for improvement in the model’s predictive performance. Therefore, the estimated soil carbon stocks and its spatial distribution map in this study can serve as fundamental information for assessing the potential carbon sequestration capacity of agricultural soils and contributing to climate change mitigation and carbon neutrality efforts.Spatial distribution map for agricultural soil carbon stock (0 - 30 cm) and scatter plot between observed and predicted values.