[1]乔 婷,姚彩燕,于东升,等.水田土壤有机碳时空演变下的最优插值方法[J].福建农林大学学报(自然科学版),2020,49(05):683-694.[doi:10.13323/j.cnki.j.fafu(nat.sci.).2020.05.017]
 QIAO Ting,YAO Caiyan,YU Dongsheng,et al.Optimal interpolation method for spatial-temporal evolution of soil organic carbon in paddy fields[J].,2020,49(05):683-694.[doi:10.13323/j.cnki.j.fafu(nat.sci.).2020.05.017]
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水田土壤有机碳时空演变下的最优插值方法()
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福建农林大学学报(自然科学版)[ISSN:1671-5470/CN:35-1255/S]

卷:
49卷
期数:
2020年05期
页码:
683-694
栏目:
资源与环境
出版日期:
2020-09-18

文章信息/Info

Title:
Optimal interpolation method for spatial-temporal evolution of soil organic carbon in paddy fields
文章编号:
1671-5470(2020)05-0683-12
作者:
乔 婷12 姚彩燕12 于东升3 史学正3 邢世和12 张黎明12
1.福建农林大学资源与环境学院,福建 福州 350002; 2.土壤生态系统健康与调控福建省高校重点实验室,福建 福州 350002; 3.中国科学院南京土壤研究所土壤与农业可持续发展国家重点实验室,江苏 南京 210008
Author(s):
QIAO Ting12 YAO Caiyan12 YU Dongsheng3 SHI Xuezheng3 XING Shihe12 ZHANG Liming12
1.College of Resource and Environment, Fujian Agriculture and Forestry University, Fuzhou, Fujian 350002, China; 2.University Key Laboratory of Soil Ecosystem Health and Regulation in Fujian, Fuzhou, Fujian 350002, China; 3.State Key Laboratory of Soil and Sustainable Agriculture, Institute of Soil Science, Chinese Academy of Sciences, Nanjing, Jiangsu 210008, China
关键词:
水田 土壤有机碳 最优插值方法 时空演变 太湖地区
Keywords:
paddy field soil organic carbon optimal interpolation method spatial-temporal evolution Taihu Lake region
分类号:
S159.9
DOI:
10.13323/j.cnki.j.fafu(nat.sci.).2020.05.017
文献标志码:
A
摘要:
明确时空演变下水田土壤有机碳的最优插值方法可为合理制定农田碳汇动态变化管理措施提供理论依据.本研究以我国太湖地区37个县(市、区)23 200 km2水田土壤为例,利用1982年全国第2次土壤普查的1 096个剖面和2000年“973土壤质量研究”项目1 370个表层实测样点数据,分析目前常用的7种确定性和4种地统计插值方法对不同时期土壤有机碳预测精度的影响.结果表明:1982年和2000年整个太湖地区水田土壤有机碳最优插值方法分别为普通克里金和析取克里金.从不同亚类来看,1982年和2000年各水稻土亚类有机碳在确定性插值的局部多项式、全局多项式和反距离权重3种方法下的预测精度高于传统的地统计.从不同行政区来看,1982年和2000年各地区最优插值多为地统计方法,尤其普通克里金法有更高的适用性.总体而言,不同时期太湖地区水田土壤有机碳的最优插值方法因样点分布、人为活动和环境因素不同而差异很大.
Abstract:
Clarification the optimal interpolation method for paddy soil organic carbon(SOC)under spatial-temporal evolution provides important theoretical basis for formulating the management of the dynamic carbon sink of farmland rationally. For this reason, we analyzed 1 096 topsoil samples from the 2nd National Soil Survey conducted in 1982 and 1 370 topsoil samples from the “973 Soil Quality Research” Project conducted in 2000, which were based on paddy soil covering an area of 23 200 km2 across 37 counties(or cities)in the Taihu Lake region of China. The influence of different interpolation methods which included 7 commonly used deterministic and 4 geostatistical interpolation methods on the prediction accuracy of SOC in 1982 and 2000 were compared. Results showed that the optimal interpolation methods for paddy fields SOC prediction were ordinary Kriging and disjunctive Kriging at provincial level across the region in 1982 and 2000, respectively. But under different soil subgroups, 3 other deterministic methods, including local polynomial interpolation, global polynomial interpolation and inverse distance weighting, showed higher accuracies than the traditional geostatistical interpolations in both years, and deterministic interpolation method had higher applicability to soil subgroup regions. The optimal interpolation methods, in different administrative areas in both years,were the geostatistical method in most regions, and the applicability of ordinary Kriging interpolation method was particularly higher. Generally, the optimal interpolation method for paddy fields SOC prediction varies greatly in different periods with the influences of sample distribution, human activities and environmental factors in Taihu Lake region.

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备注/Memo

备注/Memo:
收稿日期:2019-12-30 修回日期:2020-05-19
基金项目:国家自然科学基金项目(41971050); 福建省自然科学基金项目(2019J01660); 福建省科技支撑项目(2017N5006).
作者简介:乔婷(1994-),女.研究方向:土壤碳氮循环与GIS应用.Email:tnqiao@163.com.通信作者张黎明(1979-),男,教授,博士生导师.研究方向:土壤碳氮循环与GIS应用.Email:fjaulmzhang@163.com.
更新日期/Last Update: 2020-09-20