基于随机森林模型的卡马兰河流域土壤有机碳储量空间分布研究
Research on the Spatial Distribution of Soil Organic Carbon Storage in the Kamalan River Basin Based on the Random Forest Model
摘要: 大兴安岭林区土壤有机碳储量对于区域碳源汇变化及气候响应研究具有重要意义。本文基于土壤剖面数据，结合多种环境变量，采用随机森林(RF)模型，估计了大兴安岭卡马兰河流域0~30 cm深度的土壤有机碳储量(SOCS)及其空间分布特征。结果表明：RF模型(R2 = 0.75, RMSE = 6.81)对小尺度区域的模拟细节表现较好，研究区0~30 cm的SOCS主要分布在地势相对平坦的河流沿岸，与河流走向基本保持一致。研究结果得出了相对精确的卡马兰河流域表层土壤有机碳储量及空间分布特征，该成果能够丰富大兴安岭多年冻土区土壤有机碳储量的认识，并为生态过程相关模拟研究提供数据支持。
Abstract: Soil organic carbon stocks in the forested areas of Great Khingan are of great significance for the study of regional carbon source and sink changes and climate response. In this paper, based on soil profile data and combining multiple environmental variables, we estimated the soil organic carbon stock (SOCS) and its spatial distribution characteristics at 0~30 cm depth in the Kamalan River watershed of Great Khingan by using the random forest (RF) model. The results showed that the RF model (R2 = 0.75, RMSE = 6.81) performed well in simulation details for small-scale areas, and the SOCS at 0~30 cm in the study area was mainly distributed along the river with relatively flat topography, which was basically consistent with the river course. The results of the study yielded a relatively accurate characterisation of the surface soil organic carbon stock and spatial distribution in the Kamalan River basin, which can enrich the understanding of soil organic carbon stock in the perennial permafrost region of the Great Khingan and provide data support for simulation studies related to ecological processes.
文章引用：孙威威. 基于随机森林模型的卡马兰河流域土壤有机碳储量空间分布研究[J]. 自然科学, 2024, 12(5): 1026-1032. https://doi.org/10.12677/ojns.2024.125113

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