| 河北省土壤有机碳密度的估算与不确定性来源研究 |
| |
| 作者姓名： | ZHAO Yong-Cun SHI Xue-Zheng YU Dong-Sheng T. F. PAGELLA SUN Wei-Xi XU Xiang-Hua |
| |
| 作者单位： | State Key Laboratory of Soil and Sustainable Agriculture, Institute of Soil Science, Chinese Academy of Sciences, Nanjing 210008 (China). E-mail:yczhao@issas.ac.cn;Graduate School of Chinese Academy of Sciences, Beijing 100039 (China);State Key Laboratory of Soil and Sustainable Agriculture, Institute of Soil Science, Chinese Academy of Sciences, Nanjing 210008 (China). E-mail:yczhao@issas.ac.cn;State Key Laboratory of Soil and Sustainable Agriculture, Institute of Soil Science, Chinese Academy of Sciences, Nanjing 210008 (China). E-mail:yczhao@issas.ac.cn;School of Agricultural and Forest Sciences, University of Wales, Bangor (UK);State Key Laboratory of Soil and Sustainable Agriculture, Institute of Soil Science, Chinese Academy of Sciences, Nanjing 210008 (China). E-mail:yczhao@issas.ac.cn;Department of Environmental Engineering, Zhejiang University, Hangzhou 310029 (China) |
| |
| 基金项目： | *1Project supported by the Knowledge Innovation Project in Leading Edge Fields, Chinese Academy of Sciences (No.ISSASIP0201), the National Key Basic Research Support Foundation of China (No.G1999011810) and the Knowledge Innovation Project in Resource and Environment Fields, Chinese Academy of Sciences (No.KZCX3-SW-427). |
| |
| 摘 要： | 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.
|
| 关 键 词： | professional pedological knowledge-based database (PKD) soil organic carbon (SOC) soil profile database (SPD) soil profile statistics (SPS) uncertainty |
Soil organic carbon density in Hebei Province, China: Estimates and uncertainty |
| |
| ZHAO Yong-Cun,SHI Xue-Zheng,YU Dong-Sheng,T. F. PAGELLA,SUN Wei-Xi,XU Xiang-Hua.Soil organic carbon density in Hebei Province, China: Estimates and uncertainty[J].Pedosphere,2005,15(3):293-300. |
| |
| Authors: | ZHAO Yong-Cun SHI Xue-Zheng YU Dong-Sheng T F PAGELLA SUN Wei-Xia and XU Xiang-Hua |
| |
| Institution: | State Key Laboratory of Soil and Sustainable Agriculture, Institute of Soil Science, Chinese Academy of Sciences, Nanjing 210008 (China). E-mail:yczhao@issas.ac.cn;Graduate School of Chinese Academy of Sciences, Beijing 100039 (China);State Key Laboratory of Soil and Sustainable Agriculture, Institute of Soil Science, Chinese Academy of Sciences, Nanjing 210008 (China). E-mail:yczhao@issas.ac.cn;State Key Laboratory of Soil and Sustainable Agriculture, Institute of Soil Science, Chinese Academy of Sciences, Nanjing 210008 (China). E-mail:yczhao@issas.ac.cn;School of Agricultural and Forest Sciences, University of Wales, Bangor (UK);State Key Laboratory of Soil and Sustainable Agriculture, Institute of Soil Science, Chinese Academy of Sciences, Nanjing 210008 (China). E-mail:yczhao@issas.ac.cn;Department of Environmental Engineering, Zhejiang University, Hangzhou 310029 (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 |
| 本文献已被 万方数据 等数据库收录！ |
| 点击此处可从《土壤圈》浏览原始摘要信息 |
| 点击此处可从《土壤圈》下载免费的PDF全文 |
|
