阿尔伯塔省土壤有机碳储量的双尺度抽样和三维预测土壤制图评估

IF 2.9 3区 综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES
Facets Pub Date : 2023-01-01 DOI:10.1139/facets-2023-0040
Tomislav Hengl, Preston Sorenson, Leandro L. Parente, Kimberly Cornish, Jeffrey Battigelli, Carmelo Bonannella, Monika Gorzelak, Kris Nichols
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引用次数: 0

摘要

高空间分辨率(30)下预测土壤有机碳(SOC)储量(t/ha)的三维预测土壤制图方法 m) 描述了阿尔伯塔省2020-2021年的情况。首先编制了覆盖艾伯塔省农业用地的遥感数据堆栈。艾伯塔省共有404个采样点,采用两级采样:(1)代表主要气候带的22个试点农场和(2)每个农场的条件拉丁超立方体采样。在4个标准深度(0–15、15–30、30–60、60–100 cm),并分析SOC。分别建立SOC含量和堆积密度的预测模型,然后用于预测0、15、30、60和100 cm,并计算每像素的总SOC存量。SOC含量和堆积密度模型的R平方分别为0.61和0.68。根据这些绘图结果,与农田相比,草原土壤在所有土壤类型中始终与更高的SOC储量相关。草地土壤的平均SOC储量为2.1 每公顷Mg,范围为2.17至6.09 每公顷镁取决于土壤类型。结果还显示,>15 % 总SOC储量的一半位于底土中,高于预期。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Assessment of soil organic carbon stocks in Alberta using 2-scale sampling and 3D predictive soil mapping
A three-dimensional predictive soil mapping approach for predicting soil organic carbon (SOC) stocks (t/ha) at high spatial resolution (30 m) for Alberta for 2020–2021 is described. A remote sensing data stack was first prepared covering Alberta’s agricultural lands. A total of 404 sampling locations were distributed across Alberta using 2-scale sampling: (1) 22 pilot farms representing main climatic zones and (2) conditioned Latin hypercube sampling at each farm. Soil samples were taken at four standard depths (0–15, 15–30, 30–60, 60–100 cm) using soil probes and analyzed for SOC. Predictive models for SOC content and bulk density were built separately and then used to predict at 0, 15, 30, 60, and 100 cm and calculate aggregated SOC stocks per pixel. The SOC content and bulk density models had R squares of 0.61 and 0.68, respectively. Based on these mapping results, grassland soils were consistently associated with higher SOC stocks across all soil types as compared to croplands. The average SOC stocks for grassland soils were 2.1 Mg per hectare, ranging from 2.17 to 6.09 Mg per hectare depending on soil type. Results also showed that >15 % of total SOC stocks were located in subsoil, which was higher than expected.
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来源期刊
Facets
Facets MULTIDISCIPLINARY SCIENCES-
CiteScore
5.40
自引率
6.50%
发文量
48
审稿时长
28 weeks
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