Soil Organic Carbon Density in Hebei Province, China: Estimates and UncertaintyEnglish Full Text

ZHAO Yong-Cun1,4, SHI Xue-Zheng12, YU Dong-Sheng1, T. F. PAGELLA2, SUN Wei-Xia1 and XU Xiang-Hua3 1 State Key Laboratory of Soil and Sustainable Agriculture, Institute of Soil Science, Chinese Academy of Sciences, Nanjing 210008 (China), 2 School of Agricultural and Forest Sciences, University of Wales, Bangor (UK) 3 Department of Environmental Engineering, Zhejiang University, Hangzhou 310029 (China) 4 Graduate School of Chinese Academy of Sciences, Beijing 100039 (China)

Abstract: In order to improve the precision of soil organic carbon （SOC） estimates, the sources of uncertainty in soil organic carbon density （SOCD） estimates and SOC stocks were examined using 363 soil profiles in Hebei Province, China, with three methods: the soil profile statistics （SPS）, GIS-based soil type （GST）, and kriging interpolation （KI）. The GST method, utilizing both pedological professional knowledge and GIS technology, was considered the most accurate method of the three estimations, with SOCD estimates for SPS 10% lower and KI 10% higher. The SOCD range for GST was 84% wider than KI as KI smoothing effect narrowed the SOCD range. Nevertheless, the coefficient of variation for SOCD with KI （41.7%） was less than GST and SPS. Comparing SOCD’s lower estimates for SPS versus GST, the major sources of uncertainty were the conflicting area of proportional relations. Meanwhile, the fewer number of soil profiles and the necessity of using the smoothing effect with KI were its sources of uncertainty. Moreover, for local detailed variations of SOCD, GST was more advantageous in reflecting the distribution pattern than KI.

Keywords：

professional pedological knowledge-based database （PKD）; soil organic carbon （SOC）; soil profile database （SPD）; soil profile statistics （SPS）; uncertainty;

Series：
(D) Agriculture
Subject：
Fundamental Science of Agriculture; Agronomy
Classification Code：
S153;

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