Delineation of high‐resolution soil carbon management zones using digital soil mapping: A step towards mitigating climate change in the Northeastern Himalayas, India

Abstract

AbstractDelineation of carbon management zones (CMZs) by capturing geospatial distribution of soil organic carbon (SOC) stock down the profile is an effective strategy for precision agriculture and climate change mitigation. Satellite (Landsat OLI 8), terrain (SRTM 30 m DEM) and bioclimatic (WorldClim dataset) factors were used as covariables in this digital soil mapping approach. Depth harmonization using the quadratic spline method (equal‐area) was carried out prior to quantile regression forest (QRF) algorithm‐based modelling to estimate SOC stock at six standard soil depths (0–5, 5–15, 15–30, 30–60, 60–100 and 100–200 cm). Soil depth and SOC stock for the whole soil profile were used for the delineation of CMZs using fuzzy k‐means clustering. The predicted SOC stock, varied from 14.68 to 42.35 Mg ha−1 in the top layer (0–5 cm depth), while 17.91 to 36.88, 14.15 to 34.70, 12.55 to 35.59, 10.30 to 28.52 and 7.26 to 20.16 Mg ha−1 in the depths of 5–15, 15–30, 30–60, 60–100 and 100–200 cm, respectively. The QRF algorithm performed well in predicting SOC stock with high R2, which ranged from .67 to .83 for all the soil depths. To delineate three CMZs, modified partitioning entropy and the fuzzy performance index were used. In CMZ2, there was a significant increase in SOC stock, followed by CMZ1 and CMZ3. This zone (CMZ2) was located in the central region of the study area and was mostly covered by dense forest and perennial plantations (rubber). The CMZs provided the necessary foundation for the development of site‐specific carbon management techniques that can enhance ecosystem service and meet climate change mitigation goals.