4.5 Article

Digital soil mapping of soil organic carbon stocks in Western Ghats, South India

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GEODERMA REGIONAL
卷 25, 期 -, 页码 -

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ELSEVIER
DOI: 10.1016/j.geodrs.2021.e00387

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Digital soil mapping; SOC stock; Western Ghats; Quantile Regression Forest; Cross validation; Multiple soil classes

资金

  1. [ANR-16-CE03-0006]

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Spatial information on soil carbon storage is crucial for soil quality and environmental management. A study mapping soil organic carbon stock in a region of South India found better prediction for surface layer compared to deeper layers, with high-resolution maps outperforming existing products. The total estimated soil organic carbon stock was 917 Tg in the area studied, aiding in soil health assessment and land use planning.
Spatial information of soil carbon storage at national and global level is essential for soil quality and environmental management. Improved knowledge on the amount and spatial distribution of the carbon stock in soils is crucial in estimating changes in the terrestrial carbon dynamics and management options for carbon-storing. A study was conducted to map the soil organic carbon stock (SOC) over 56,763 km(2) area of Western Ghats of south India using a digital soil mapping approach. Landsat data, terrain attributes, and bioclimatic variables were used as covariates. Equal-area quadratic splines were fitted to soil profile datasets to estimate soil organic carbon stock at six standard soil depths (0-5, 5-15, 15-30, 30-60, 60-100 and 100-200 cm) and Quantile Regression Forest (QRF) algorithmwas used to predict the SOC stocks. Prediction of SOC stockwas better for surface layer (R-2 = 31-43%) and the performance was decreasing with depth (R-2 = 7-21%). The modal performance was also compared with SoilGrids products. Although the spatial patterns were similar, the present predicted SOC maps outperformed SoilGrids products in terms of both R-2 and RMSE. The predicted total soil organic stock in the Western Ghats ranged from 7.1 kg m(-2) to 30.9 kg m(-2) and the total estimated SOC was 917 Tg. The present high resolution SOC maps help to assess and monitor the soil health and preparation of proper land use planning. (C) 2021 Elsevier B.V. All rights reserved.

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