水稻土有机碳密度的空间预测分析--以浙江省长兴县为例  

Different Methods for Prediction of Spatial Patterns of Paddy Soil Organic Carbon Density in Changxing County,Zhejiang Province

作　　者：刘莎[1,2] 任红艳[2] 史学正[2] 潘剑君[1] 王洪杰[2] 

机构地区：[1]南京农业大学资源与环境科学学院,南京210095 [2]土壤与农业可持续发展国家重点实验室,中国科学院南京土壤研究所,南京210008

出　　处：《地球信息科学学报》2010年第2期180-185,共6页Journal of Geo-information Science

基　　金：博士后基金(2008441080);中国科学院知识创新工程领域前沿项目(ISSASIP0715);国家自然科学基金创新群体项目(40921061);中国科学院知识创新工程重要方面项目群(KZCX2-YW-Q1-07和15)

摘　　要：准确预测未采样区域SOC密度,是研究SOC演变趋势和探索土壤固碳作用对缓解全球气候变化的基础。采用泛克里格法(Universal Kriging,UK)和土壤类型法(pedological professional knowledge-based method,PKB),分别对长兴县水稻土有机碳密度进行了预测,其中,UK直接以长兴水稻土剖面资料为源数据、PKB以长兴水稻土剖面数据和长兴1∶5万数字土壤图为源数据进行预测。根据平均绝对误差(MAE)及均方根误差(RMSE)大小,评价了两种方法在县域尺度土壤有机碳密度空间预测效果。结果表明:UK的MAE(31.2)、RMSE(52.5)均大于PKB的MAE(24.7)、RMSE(43.1),说明PKB法的预测效果较好,UK法相对较差。研究表明,对土壤类型、土壤母质,以及剖面点位置等信息的综合考虑能使PKB法更好地表达土壤属性的空间特征,也更适于县域尺度土壤有机碳密度的空间预测。Soil organic carbon（SOC） plays an important role in conserving soil fertility,improving soil quality,and changing global climate.SOC is closely related to the spatial distribution pattern of soil organic carbon density（SOCD）.It is necessary to predict SOCD for the un-sampled points.Thus,it is really meaningful to derive accurately spatially data of SOCD from discrete data using spatial prediction methods for SOC evolution trend research and for the exploration of the role that SOC sequestration played in alleviating global climate change.Based on 87 paddy soil profiles collected from Changxing County,Zhejiang Province for the Second National Soil Survey,this paper attempted to predict the spatial patterns of paddy soil organic carbon density in Changxing County using two different methods.The data of paddy soil profiles were used directly by Universal Kriging（UK）,and the data of paddy soil profiles and 1？？0 000 digital map of Changxing County were used by pedological professional knowledge-based（PKB） method to predict the spatial patterns of paddy soil organic carbon density in Changxing County.Prediction was evaluated in virtue of mean absolute error（MAE） and root mean square error（RMSE）.MAE（24.7） and RMSE（43.1） of PKB method were lower than UK method.The sum squared error（ESS） of the UK method only can explain 20 % of the total variation.The PKB method widened the range of SOC density（49.6-650.1 t C hm-2） as compared with the UK method the range of SOC density（66.7-165.7 t C hm-2）.The prediction by PKB method had less smoothing effect and more details of depicting the local variation under complex terrain.Therefore,PKB method was a better method for predicting paddy soil organic carbon density in Changxing County in this study.

关 键 词：长兴县 水稻土 有机碳密度 普通克里格 土壤类型法 

分 类 号：S153.6[农业科学—土壤学]